August 14, 2023 • 51 mins
Why do some countries become rich while others stagnate? And can you predict which countries become wealthy in advance of them actually increasing their collective GDP? The answer may lie in the complexity of each nation's domestic economy. On this episode we speak with Ricardo Hausmann, a professor and director of the Growth Lab at Harvard University. He helps us understand what economic complexity is, how it's measured, and the process by which countries can move from being less complex to more complex over time.
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Speaker 1 (00:10):
Hello, and welcome to another episode of the Odd Lots Podcast.
Speaker 2 (00:14):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 1 (00:16):
Tracy, I'm super late to everything. First of all, did
you play Wordle?
Speaker 2 (00:21):
I did. I didn't get obsessed with it like some
people did, but I think we were all fairly bored
during that time period and on the lookout for any
sort of entertainment.
Speaker 1 (00:31):
And it never clicked. But I'm always late to everything.
Like a year ago, people were telling me it's like, oh,
you gotta play this game trade all, and I did end,
but like three or four months ago, I started really
getting into it, and I think you're into it now too.
Speaker 3 (00:44):
Yeah.
Speaker 2 (00:44):
I think we both started playing around the same time,
probably because we heard about it from the same person.
It is a fun game, so for those who don't
know it is like Wordle. It basically presents a sort
of graphic schematic of an unnamed country's exports, and you
have to try to guess what country it is.
Speaker 1 (01:06):
Yeah, exactly, And I'm not very good at geography, so
often it'll say like, Okay, you're close, but it's like
you have to go fifteen hundred kilometers to the northwest.
I'm pretty bad at geography, so I'm not good. But
as playing this game and watching the way the different
shapes of different countries export mix, I feel like I've
really started to learn things about the world.
Speaker 2 (01:29):
I have learned so much about the economy of Angola.
Speaker 3 (01:32):
Right.
Speaker 1 (01:33):
So you see a country and it's like eighty percent
of their exports are like coffee in gold, right or
something like that, and you're like, Okay, this is a
relatively poor country. It has a lot of growth left
to do. And then you see another country and it's
like advanced circuits and medicine and hangars and bananas and
(01:56):
all this stuff, and like, oh, and you start to
see these shapes and these distributions. That's sort of like
tell you things. It's like, Okay, I can guess maybe
this is in Europe, or maybe they have a lot
of things, maybe it's in Eastern Europe. You suddenly sort
of learn like how rich countries goods exports really differ
from poorer countries goods exports.
Speaker 2 (02:12):
Yeah, totally. There are three clues that it gives you.
One is distance, as you just mentioned, and the other
is total size of exports. So that gives you an
indication of how big or small that economy is. And
then that third thing is the nature of the exports,
and it sort of divides them up into different categories,
but it gives you a really good snapshot of a
(02:34):
country's economy. And as you play the game, you start
to recognize I guess certain economic export attributes. Yeah, go
with certain types of countries or economies.
Speaker 1 (02:47):
Right, so integrated circuits and palm oil, probably Southeast Asia, right,
something like that. Anyway, this game that you and I
have become obsessed with, it's sort of based on this
work related to economic complexity, the Atlas of Economic Complexity,
this sort of idea, and this is something that's come up.
It came up in an episode we did with Henry
Williams and David Os. It came up with the episode
(03:10):
we did with Dan Wong and why some countries can
develop airline industries and other countries can't. This idea that
complexity of goods exports complexity is in itself a sort
of predictor of wealth.
Speaker 2 (03:24):
Yeah, and maybe it's also a desirable model for countries
to sort of aspire to, this idea that maybe they
want to get away from simply producing a bunch of
t shirts, So like fifty percent of their economy is
T shirt exports or something like that. They want to
get to a place where they have expertise across a
broad and value added sort of realm of exports.
Speaker 1 (03:48):
Or maybe they export a lot of nickel and they
want to be in like refined nickel, right, some nickel
relatais the commodity just pure Anyway, this has sort of
like really opened up a lot of these conversations playing
like thinking about the world. So I'm really excited about
our guest because our guest has done more work on
this idea of economic complexity and why nations are able
(04:08):
to develop complex, rich economies. He's also the creator of
that at list of economic complexity. We're going to be
speaking with Ricardo Housman. He's a professor at the Harvard
Kennedy School and the founding director of the Harvard Growth Lab.
All of my trade off friends are super excited about
listening to this conversation. Doctor Husman. Thank you so much
(04:29):
for coming on odd Lats.
Speaker 3 (04:31):
Oh, it's a pleasure to be with you. Thank you
for inviting me.
Speaker 1 (04:34):
Absolutely. What is economic complexity?
Speaker 3 (04:38):
Economic complexity is an attempt to measure how much countries
or places know what to do, so like I try
to measure no. How Now, if you want to think
about knowledge and say, well, and I know people who
have a bachelor's degree, people who will hire high school dropouts,
people who have a PhD. That sort of tells you
(05:01):
how much a person knows. But if you ask yourself,
how much does a society know, well, that would be different.
That would not be characterized by the average, say the
average number of years of schooling that the society has.
Not A society that is full of just dentists will
know less than a society that is half dentists and
(05:24):
half lawyers, or a society that is a third dentist,
a third lawyer, or third engineers. So in some sense
you want to know how much the whole of society knows.
And one of the important things about knowledge is that
knowledge at the societal level has been exploding exponentially, but
(05:46):
our mental capacity to know has not. So the way
the economy has been adapting and adopting growing amounts of
knowledge is by putting different bits of knowledge in different heads,
sort of like parallel processing. You know, if you want
to run a company, you will need somebody who knows
(06:07):
about accounting, about finance, about marketing, about human resource management,
about contracts, about taxes, about procurement, about engineering. So you
want to have a lot of knowledge to run these things,
but you cannot stuff that knowledge into a single head.
You have to spread it into a bunch of heads,
(06:27):
and then you have to bring those heads together back again.
You have to kind of put humpty dumpty back together again.
So the way in which a society grows is it
grows its knowledge by putting different bits of knowledge in
different heads and then by bringing those heads together. Now,
if a society makes very simple things, it makes things
(06:50):
that can be done by few people, because the knowledge
that is needed to make one of those things, you know,
fits in just a few heads. But if you're going
to do stuff that requires not a lot of knowledge,
you'll have to bring many, many more of these heads together.
You'll have to network these brains together to make that thing.
So complexity emerges as the consequence of distributed knowledge in society.
(07:14):
You have different bits of people knowing different things, and
then you have to bring those things together, and then
these complex networks emerge from that process. So, in some sense,
what is really driving growth is this growth of knowledge
and the growth of using that knowledge, and consequently it's
in this spread of different bits of knowledge in different
(07:36):
heads and the ability to bring those heads together to
make relatively long chains of brains.
Speaker 2 (07:43):
I have a bunch of questions already about comparing and
contrasting measuring complexity versus the way economics has traditionally handled
some of this. But maybe a step back question why
did you decide to start looking into this? What is
the benefit of looking at complexity within a particular society
or economy.
Speaker 3 (08:04):
It goes back to the question and when Adam Smith
asked himself what's the source of the wealth of nations?
He said it was the division of labor? But why
the hell would the division of labor matter? And he
gives a thin factory example that if you split the
work and this guy does the head and this guy
does the body, et cetera, that increased productivity. That idea,
(08:26):
I think has a kernel of what the story is.
But this stuff becomes incredibly powerful when you're talking about
knowledge driving the economy and driving society. So it's really
about the division of knowledge that's what drives growth. It's
the division of knowledge that allows the whole to know
(08:46):
more than its parts. And so how would you go
about measuring what a society knows how to do. Well,
let's look at what they do, because if they do something,
it means that they know how to do it right,
So it's proof that they know how to do it.
So we can look at what a society does to
figure out what is it that they know how to do.
(09:09):
So when you look at a country and say, okay,
this country is only good at doing a few things,
and this other country is good at doing many more things.
And this country here is making things that seem to
be simple things that can be done in small groups.
This other country that has to do things that require
this very broad network of brains coming together to make something.
(09:30):
It tells you something about how those economies are managing knowledge.
Speaker 1 (09:35):
Tracy is sort of hinting at this, and I want
to sort of drill down on this before moving on.
You know, there are various traditional ways in which we
measure economies. GDP is more or less a different way
of like you just add up everyone's income and you say, okay,
this country is richer than this country, and this country
is richer than the next. Give us the basics. You
know you have country A and country B. How do
(09:56):
you like measure? Okay, this country is more comp more
complex economy capable of more complexity than country be.
Speaker 3 (10:04):
So let me first say you can measure GDP and
so GPS how much countries are able to make in
terms of income. That doesn't tell you why they are
able to make it. Economic complexity is trying to get
at why is it that you are able to generate
more income? What's underpinning that? And for that, we like
to measure how much a society knows in our standard measure.
(10:28):
We've now applied it to a whole different bunch of fields,
not just in exports but other things. But we started
with exports, and the reason why we started with exports
is because we needed a data set that included all
the countries in the world, so we could benchmark all
the countries in the world with a standardized classification. And
since international trade it involves different countries, they've all agreed
(10:49):
on some common classification scheme, so it was expedient for us.
But experts are also something that tells you whether a
society is good enough at making something that it is
able to sell abroad, So it's kind of like a
litmus test that you're pretty good at making something. So
I don't really care how much they make. I just
(11:12):
care that they are able to make it, so that
that knowledge is somewhere in that society. So the way
you would think about calculating how much knowledge of society
has would say, tell me how many different things that
are they able to make? You're mentioning angola, or they
make mostly oils essentially that's their thing, or do they
do many things? So the diversity of their export basket
(11:34):
is kind of like a first cut, right, But you
would say, well, but products differ in how knowledge intensive
they are and how difficult they are to make. So
we found a trick on how to measure how difficult
it is to make a product by simply asking the
question how many countries are able to make this product.
So if you talk about raw wood, many many countries
(11:56):
export raw wood. If you tell me about microscopes or
X raymage, very few countries are able to export those things.
So that tells you something already about how difficult it
is to make these things, right, So we call that
the ubiquity of a product. And then you can ask
yourself the question, Okay, on average, how ubiquitous are the
(12:17):
products that this country makes? That is this country making
mostly things that are simple to do that everybody knows
how to do, or or they make things that are
hard to do, things that are done in few places.
So that's kind of like a different cut out of
the data. And you simply repeat this process an infinite
number of times and it generates an algorithm that ranks
(12:40):
both the countries in terms of how complex they are
and the products in terms of how complex they are.
So essentially, it's an operation on this matrix if you
want that relates countries to the products that they make.
It is an eigenvector of that matrix. Essentially, if you
want to get fancy at the mouth, but it captures
(13:00):
this idea how many things are we able to do
and how complicated it is to do those things.
Speaker 2 (13:21):
So is it possible to have a good economic outcome
with low complexity? Or I guess another way of saying
this is is complexity as synonym for development or wealth here?
Or capturing something different? Could you have a country that
scores low on complexity but is still a relatively good
(13:43):
place to live from an economic perspective.
Speaker 3 (13:47):
So one major thing that economic complexity does not capture
is natural resource wealth. Okay, so when you make a graphs, say,
of the relationship between how complex you are are and
how rich you are, the outliers tend to be countries
that are natural resource rich. So they get their income
(14:08):
not so much by what they know how to do,
but from the natural resource wealth that they happen to have.
Speaker 2 (14:16):
So a place like the United Arab Emirates or Saudi
Arabia perhaps might score low on complexity, but they have
a ton of oil wealth and so they're still quite
prosperous on a GDP per capita basis that sort of
thing exactly.
Speaker 3 (14:32):
So, or you could say, tell me, controlling for their
natural resource wealth, they have a lot of complexity or not.
And let me tell you a few of the things
we have established. The first one is that the complexity
correlates very highly with how rich you are, and if
you control for your natural resource wealth, it correlates even better.
(14:52):
So there's a very strong relationship between economic complexity and
natural resource and your GDP per capita in level. So
that's a very strong relationship. But more importantly than that,
countries that are more complex than you would have expected
them to be given their income level tend to grow
(15:13):
faster in the future, and countries that have relatively low
complexity relatives to their income level tend to grow less
in the future. So your economic complexity relative to your
income level is a predictor of how fast you will
be able to grow. And typically when we look at
how good these predictions are, they tend to be best
(15:34):
at a horizon of about ten years, So it tells
you something about what your next decade is likely to
look like.
Speaker 1 (15:41):
What's an example of maybe something in history in which
at some point a country scored significantly high complexity and
then did it over the next several years. It's like, yeah,
this country really boomed. What's an example that stands.
Speaker 3 (15:55):
Out of this, Well, there are many examples, but suppose
if you have take the picture in two thousand and eight,
two outliers were India and Greece. India had extremely low
income levels for its level of complexity, and Greece had
extremely high income levels for their level of complexity. And
what happened is that India has been the fastest growing
(16:18):
large country in the world since then, and Greece collapsed.
So we also see countries that increase their complexity initially
by moving into a new set of products. In the
case of Thailand, they first moved into garments and spent
a whole decade adding a bunch of different garments to
their export baskets. Suddenly they got into electronics and then
(16:41):
started to add a bunch of electronics to their export basket,
and then they got into cars and machines and so on.
So they have been increasing their complexity and have very
sustained high growth rates in the process. In general, what
we find is that only about a fifth of the
countries that were poorer than the US, say, in nineteen
(17:02):
seventy have really caught up narrowed the gap with the US. Okay,
since nineteen seventy onwards, only twenty percent of countries narrowed
their income gap with the US. Those twenty percent of
countries that narrow their income gap with the US increase
their complexity very significantly. The other eighty percent did not.
(17:25):
So I would tell you that sustained growth implies this
process of absorbing knowledge, distributing in a your society, mobilizing
that knowledge to make more things and more complex things.
Because you get more complex. Things are essentially things that
require more knowledge, and things that require more knowledge require
(17:46):
deeper networks of humans collaborating, whether it's in a single
firm or in a longer value chain.
Speaker 2 (17:52):
Can you talk a little bit more about how you
build complexity and diffuse that knowledge within a society, because
I am imagine if you're a developing country, maybe you
find that you have a competitive advantage in one type
of thing. I'm going to go back to the T
shirt example. You can make T shirts cheaper than anyone
(18:12):
else and more efficiently, I guess, And then I would
imagine the temptation is to just stick with that specialization
and just do the thing that you are currently really
good at. So how do countries actually break out of
that dynamic and start developing expertise in other areas.
Speaker 3 (18:31):
There are essentially three mechanisms that I would like to mention.
The first one is that countries tend to move from
where they're good at to what I like to call
or Stuart Kaufman coin the phrase the adjacent possible. When
we look at countries adding products to their export basket,
(18:53):
those products tend to be cognitively near. If you want
the products that they were making before. And one of
the contributions we've made is we've developed a technique to
measure this cognitive proximity for all the products in the world.
And you can locate every country in the world and
(19:14):
find out what's in their adjacent possible So countries tend
to move from the things that they are currently good
at to things that are in their adjacent possible And
we call this cognitive map of the products of the world.
We call it the product space. And this product space
is very heterogeneous. There are some parts of the product
space there where you have products that are tightly connected
(19:37):
to each other. So if you know how to make
one kind of product is kind of like easy to move.
You have a rich adjacent possible. You have many ways
of reorganizing that knowledge to make other things. We like
to use the metaphor that products are like trees, and
firms are like monkeys. They live on trees, they exploit
certain trees. So the product space is like the map
(19:59):
of the forests. And so you can, by the way,
if you go to the Atlas and Economic complexity, we
have the we choose a country, we have the product space.
We will tell you where in that forest, does this
country have its monkeys, and then it can tell you
know which trees are close to those monkeys, and it
(20:20):
can tell you so you know, what are other characteristics
of those trees that might make it sexier or less
sexy to move in that direction. Okay, so the first
thing I want to say is that countries tend to
diversify by moving to their adjacent possible depending on where
they started, and not every country starts with the same
deck of cards. They don't start with their monkeys in
(20:42):
the same place. Some countries start with their monkeys in
very very promising parts of the product space because their
trees are very closely connected to each other there, so
it's easy for the monkeys to jump from tree to tree,
and other parts of the product space are very sparse
with their trees are very far from each other, so
(21:03):
it's hard for those monkeys to move. Okay, So that's
mechanism one, move towards the adjacent possible. Mechanism two is
that you have to solve this chicken and neck problem.
You don't know how to do the things you don't do,
but you need to know how to do things to
start doing things you are not doing before. So you
(21:25):
need watchmakers to make watches. But how do you become
a watchmaker in a country that doesn't make watches. How
do you solve this chicken and egg problem. We think
that this solving the chicken and eck problem is the
thing that forces countries into moving just to the adjacent
possible because it's hard for them to solve too many
(21:47):
of these chicken and egg problems at the same time.
But one way to accelerate the solution of these chicken
and eck problems is to bring watchmakers from outside your country.
That is, you may not have what makers in your country,
but maybe you start with a group of Swiss watchmakers
and they'll train the next generation of watchmakers and now
suddenly you do watchmaking right. So migration plays an outsized
(22:11):
role in diversification because you need to add knowledge that
was not in the system before. So if you can
attract people that had knowledge that was not in the
country and you can engage them having worked there and
have that knowledge spread, that seems to be very important.
There's a very nice story about Bangladesh here where you know,
(22:33):
if you look at Bangladesh in the ATHLETs of economic complexity,
you'll tell you that ninety percent of their exports are
garments and that they all started in the eighties. These
exports of garments, Well, what underpinned that was a company
which was called Desh and that company sent one hundred
and twenty six of its workers for six months training
program in Korea. Because the program that company was created
(22:56):
by Dai Wu. So these guys went to Korea. Yeah,
trained in Korea, came back, started the company and started
to produce. Fifty six of those people left the company
to create their own startups, and those fifty six children
of this company DSH are the core of the export
(23:17):
industry of garments in Bangladesh. So in some sense you
have to infect the system with knowledge and assure that
the mechanisms are going to allow that knowledge to spread.
Speaker 1 (23:29):
Tracy prefaced the question. She talked about a country that
exports a lot of cheap T shirts and we sort
of think of a T shirts as being low value,
and you just mentioned the beginning of Bangladesh's process to
become wealthier and had a textile export company. But even
at least a T shirt, there's going to be some machinery,
there's going to be this something of a commodity supply
(23:50):
chain that has to be organized. There are certain engineering
aspects of it versus say, another country that may export
cocoa and coffee, in which I imagine that maybe it's
roughly the same level in terms of income, but strikes
me as a simpler process of selling coffee, beans or cocoa.
Are there certain goods like that consistently that, even though
(24:14):
they may seem rudimentary our early predictors of okay, at
least this country has some capacity to have monkeys jump
from tree to tree, so to speak.
Speaker 3 (24:24):
You have given a fantastic example of what makes parts
of the product space denser and what makes parts of
the product space sparser, because garments are in a dense
part of the product space. If you know how to
make one kind of garment, you can make very different
kinds of garments. But in order to make garments and
(24:44):
export them competitively, right, you need to have an industrial
zone where materials can go in and out, where workers
can go in and out, where there's power, where there's water,
where there's a good logistic election to a port or
to an airport, right where the custom service works more
(25:06):
or less well, and maybe has to do complex sophisticated
things like letting the textiles come in in bond without
paying VAT and tariffs so that if they are going
to be exported, so you save on these transaction costs.
So getting government industry going is pretty complicated, and it
(25:26):
has taken fifteen years for Ethiopia to get into it,
and they're ballion. They had to build these industrial zones,
they had to provide electricity to these industrial zones. They
had to build a railway to Djibouti. An incredible number
of things that were not there that were part of
so like the ecosystem that garments require. But once you
(25:49):
have that ecosystem, well in the same industrial zone, maybe
with the same port and the same electricity and the
same water and maybe even the same workers, you could
s electronics. Maybe you can do some auto parts. In
the end. What's the difference between a car seat and
another leather product, So you may start producing things for
(26:11):
the auto industry and so on. So these things, so
garments would have many neighbors. It's easier to move from
garments to other things then to move from co co
to other things. Because you know, if you make coffee, well,
coffee grows in the tropics between nine hundred meters above
sea level and thirteen hundred meters above sea level let's say,
(26:32):
between three thousand and four thousand feet, And it requires
a tree to provide shadow. And so if you suddenly say,
you know what, I'm not going to grow coffee anymore,
I'm going to do something else, well, what else are
you going to do between three thousand and four thousand
feet altitude? It's in a mountainous region. So it does
(26:53):
not make diversification from coffee into other things very easy.
But diversifying in an an industrial song from one kind
of manufacturer to another kind of manufacturer is much easier.
Speaker 2 (27:05):
You know, I kind of enjoy it just hearing the
specific examples of how this works. Do you have a
favorite example of this sort of monkey's jumping from trees
dynamic or maybe even one going in reverse? Like, I'm
curious how that happens as well, how an economy would
maybe lose complexity over time.
Speaker 3 (27:24):
Okay, so let me maybe give you an example of both.
You know, a lot to increase in complexity in Japan
and Korea did not happen because new companies were created
to do more things, but because established companies, these chiballs
in Korea, these kde etsus in Japan, diverse to fight
internally into more things. So a company like Samson started
(27:47):
in sugar trading, and you know now they are the
largest producer of semiconductors and s grams and TV screens
and smartphones. That process of transformation happened inside the company,
and it happened by adding capabilities to their capabilities. So
for example, you'd say Finland is a country that had
(28:08):
a lot of trees, and traditional development economists would have said,
cut those trees and sell wood. And then they would say, no,
don't don't sell wood. Make furniture with that wood, or
make paper with that wood. Add value to your raw materials.
But that's not where the story really went. It's sort
of like Finland had a lot of trees, so they
have to cut the trees. But to cut the trees,
(28:28):
you need tools to cut trees. You need machines to
cut trees. So they became good at tools and machines
that cut wood, and from there they moved to tools
and machines that cut because not everything is made out
of wood, and from there they made they went to
automated machines that cut, because cutting everything by hand can
be either boring or imprecise. And then they said, you know,
(28:51):
from automated machines that cut, they want to just automated machines.
Why do we need to cut? There's more to life
than just cutting, right, And then from autumnate machines they
ended up in Nokia. So the process is a process
of adding capabilities to your capabilities, because once you know
how to do something, there is something in that cognitive
(29:12):
vicinity that you could do. Now. An interesting example of
going backwards is let me give you the example of
South Africa. South Africa is a country that has a
lot of coal mineral resources, and they knew how to
transform that coal into cheap electricity, and that cheap electricity
(29:35):
made them very competitive in mining and in metal processing
and in relatively energy intensive manufacturing. Now they messed up
their electricity company. Their electricity company lost the capacity to
sell cheap electricity, and now they not only have expensive electricity,
(29:56):
they have very lousy electricity with a lot of blackout
and something called load shedding, so like plan shutdowns, and
that has made manufacturing activity very very complicated, and that
has caused them to lose a lot of complexity, so
in say nineteen ninety, they have the same complexity as China,
(30:17):
and now China has increased its complex complexity dramatically and
South Africa has gone in the opposite record.
Speaker 2 (30:41):
Since you mentioned the Japanese and Korean conglomerates just then,
that reminds me of something I want to ask you,
which is, is there a point at which there can
be too much complexity? I'm imagining, for instance, a big
company and suddenly they have their fingers in a thousand
different parts, and maybe they're okay at doing a bunch
(31:02):
of those things, but maybe they're not particularly good at it,
and it becomes inefficient and the sort of like lumbering
everything everywhere, all at once. Entity is that a concern
at all, either on a corporate level or on an
economy wide level.
Speaker 3 (31:18):
I think it's more on a corporate level than on
an economy white level. I would say, if you're a company,
maybe you realize that there's this adjacency that you could exploit,
and maybe you start exploiting that adjacency, But then you
realize that managing the two organizations might be too complex,
so you spin it off, and spin offs sell part
(31:40):
so that you keep a coherent entity that's easier to manage.
That's great, But if you spun it off, it means
that somebody else bought it, and somebody else is using
that knowledge to produce those things. So I think it's
a concern for firms. How do you keep your coherence?
I would say, still explore. I think there's a lot
(32:00):
of value in exploring your adjacency, developing that adjacency, and
maybe spinning it off later on, and it will add
to the value of the company. At the societal level,
I don't see any evidence of that. I see societies
that are relatively small and are amazingly complex. I'll give
you the example of Slovenia. Who would have thought a
(32:20):
country of two million people, they export thirty five billion
dollars or more and an incredibly large diversity of things.
They're super plugged in to value chains in Austria, value
chains in Germany. In they do pretty sophisticated stuff and
with only two million people. So I don't think there's
(32:42):
too much limit to the growth of complexity because there
isn't that much limit to the growth of knowledge in
a society, and you don't have to be big, to
be very knowledgeable as a society.
Speaker 1 (32:55):
I have so many questions. I loved your sort of
like brief industrial history of Finland. And it's like, you
go from exporting wood, then you have tools that cut wood,
then you have tools that cut, and then you have
things that do things that don't just cut, and then
you have no suddenly of no can it makes a
lot of sense you describe it. I'm curious. Generally speaking,
we've seen countries lately who are major exporters of raw
(33:18):
commodities attempt to move up the value chaine, so to speak,
by insisting that, say, a mining company in Indonesia can't
just come and take the nickel and sell it, that
they need to set up some sort of domestic refining
operation in Indonesia, so that something more complex than just
selling the nickel. What is your history teach us about
(33:40):
countries that have done a better job or not of
getting out of, say the so called resource curse. Are
there certain strategies that work better than others in terms
of a country not just being dependent on a single
commodity that does not have many adjacencies.
Speaker 3 (34:00):
So let me say that one of the most passtrating
ideas in the field of economic development is the idea
that you should focus on adding value to your raw
materials because there's so much more you can do. Then
the things that can be done by relying only on
the raw materials that you happen to have. Your opportunity
(34:22):
set is much much wider than that. So, suppose you
have nickel, It may make a lot of sense to
process the nickel locally because when your mind something, you know,
if it's a good mind, it might have two percent
nickel or three percent nickel. So you want to separate
ninety eight ninety seven percent stuff so you don't have
(34:44):
to transport that much stuff that is worthless, right, so
you want to do the refining and some of the
processing nearby, just to save on transportation costs. But if
you're going to do a lithium ion battery, well you
might have the nickel, but you don't have the lithium,
you don't have the chromium, you don't have the other
minerals that go into it. So you will have some
(35:08):
of them, but you will have to import the other ones. Now,
think if you're trying to make a cell phone, Well,
what is the raw material that you have to have
locally that will make the cell phone, well, I mean
too many none. So if you are going to be
making cell phones, it's because you are going to be
able to connect to a bunch of value chains between
(35:30):
the people who are able to make the memory and
the processors and the screen and the touch screen, you know,
the surface that can detect where your finger is and
all these different parts. So that that doesn't happen in
a single company, that happens in a bunch of many companies.
(35:51):
So if you want to get into that kind of thing,
which might be possible. So say you are in Legos, Nigeria. Well,
Legos is a port city, so anything you need you
can bring into the port. You don't have to have
that raw material in your country. So in general, I
would say, if you have raw materials, maximize the value
of your raw materials. But most of the things that
(36:12):
you could do next may have nothing to do with
processing those raw materials. And the best example here is Dubai.
Dubai long many moons ago had oil, it no longer
has oil. Abu Dhabi has oil, but Dubai doesn't have
oil anymore. But Dubai has an airport that is a
major hub. It has Emmerate Airlines, which is a major airline.
(36:34):
It has Dubai Ports, which is a network of global ports.
It has a lot of logistics. It has the regional
headquarters of multinational corporations, It has universities where people go
to study there, et cetera. So they have added a
lot of stuff to their If you want export basket
that is super distantly related to oil, they would probably
(36:56):
not have gotten there had they not have oil. That
allowed them to build that infrastructure, that to build the amenities,
to build the things that are attracted and the other activities.
But they are not about oil refinding, they're not about plastics,
they're not in the value chain.
Speaker 2 (37:11):
Avoid the way you described the way that diversification or
development works, this idea of monkeys jumping from tree to tree.
It sounds very naturalistic, like a natural progression of expertise.
But I'm curious what role you think government policy could
play in that process, particularly in the context of what
(37:35):
we see nowadays, which really seems to be a resurgence
in some parts of the world in industrial policy that
is aimed at developing specific new types of technology or capabilities.
Speaker 3 (37:47):
Well, definitely, I think that the government has a lot
of useful things that it can do. First of all,
every technology, every industry lives in a environment of relatively
specific public goods that the government needs to provide. So,
for example, suppose the society adopts the car as a technology,
(38:11):
and for transportation, well, cars need roads, Cars need traffic rules,
Cars need traffic lights and traffic signs. They need traffic
cops to enforce those rules. So the car technology lives
in an environment of public goods that make that car useful.
(38:32):
A car with no roads it would be useless. A
car in roads with no rules and no traffic signs
and so on may be too dangerous. So that technology
lives in an environment of public goods. And typically governments
are pretty lousy at producing the public goods that are
needed by the industries that exist. They are typically hopeless
(38:56):
in producing the public goods of the industries that don't
yet exist. So if you want that industry to exist,
you need to make sure that the public goods that
that industry will require are provided. So, for example, it's
going to be extremely difficult to sell electric vehicles in
a society that cannot assure people that they are going
(39:19):
to be charging stations, but nobody is going to build
charging stations for a market of electric vehicles that does
not yet exist. So these things can be addressed through policy,
these chicken and egg problems, these coordination problems, this provision
of public goods that industries are going to need. For example,
(39:41):
suppose that you want to export a fresh blueberries the
way Peru does, Okay, and they're the major exporter of
blueberries these days. An industry that started in Chile and
then moved to Argentina and now it's in Peru. Well,
you cannot export fresh produce if you do not have
(40:02):
a green lane in customs, if you don't have a
cold storage transportation chain what they call a cold chain,
if you don't have fit to sanitary agreements with the market,
you're going to be selling this stuff too. So that
industry is only going to exist in the context of
these public goods that make that industry feasible. So I
(40:24):
think governments have to engage in the nitty gritty of
the public goods that new industries need, and they'll have
to get engaged in the nitty gritty of chicken and
egg problems. Even within the private sector that could like
the example I gave you of the charging stations and
the eeds so that markets are able to develop. So
(40:46):
I do think that there's an important contributing role that
industrial policies can play to facilitate monkeys moving.
Speaker 2 (40:54):
I have just one more question, which is a very
important one. How good are you at trade all the
fact that you know that Peru is one of the
biggest exporters of blueberries nowadays?
Speaker 1 (41:04):
Is it just super nice history of which countries where
the blueberry exporters in the past.
Speaker 3 (41:11):
Well, I mean it's a bit unfair. This is my
day job, this is what I do, so it's not
on my hobby. So this is what I think about
all day.
Speaker 1 (41:22):
We talk a lot about and trade again, goods exports,
and there's a really good reason to look at exports
because there's that sort of like discipline of like you
can't force another country to buy your goods, and so
like looking at goods exports is really interesting. I'm curious
about work you've done of looking at services through the
complexity lens and can countries rise up and become rich
(41:44):
if they never go through the manufacturing process, because as
you talk about, you know, manufacturing links all different kinds
of things supply chains, ports, electricity systems, cutting, and various
things like that. Can it be done through the services.
Speaker 3 (41:56):
Room, I think? So let me give you the example
of Panama. Panama had a canal and the canal was
run by the Americans, and the Americans just wanted the
ships to go through. So when the Panama can became
Panamanian in nineteen ninety seven, so they started to think, okay,
what can we do with the canal. Well, we want
the ships to not just go through, but to stop,
(42:18):
So let's build some ports. Maybe, let's do some logistics,
some transshipment. They said, well, what do these people need?
They need a financial services, so why don't we create
an offshore financial center. And then they decided, you know what,
why don't we become a hub for regional multinational headquarters.
And they happened to stumble into having a very successful airline,
(42:42):
Copa Airline. It's the more successful company in the region.
So that made having regional headquarters and multinational corporations very
practical because from Panama City you can go to anywhere
in Latin America and the US and a bunch of
other destinations. So suddenly you have a bunch of people.
They have some forty thousand people who work at multinational
(43:04):
corporations under special visas that work in Panama, and they
want to have amenities, restaurants and museums, cultural activities, good schools,
good healthcare. So guess what. You become a good destination
to attract other people and other talent, and you become
a good tourist destination. So in the example I've just
(43:24):
given you, it's a bunch of service industries that are
connected to each other. And by the way, Panama is
the country in Latin America that has had this has
dispost over the last thirty years.
Speaker 1 (43:35):
I realized I have one more really important question that
we can't leave a I'm curious, like you have new
research out, So is there anything that jumps out at
you right now in terms of which countries are on
the move, what is the big picture trends in her
who's moving? And like what is happening here in the
richest country in the world, or I think are pretty
close to it in terms of trends in our own complexity.
Speaker 3 (43:59):
Here. First of all, let me invite your listeners to
all visit the aplus of economic complexity we have just
updated it with twenty twenty one data and we run
growth projections for the following decade, and there you'll find
that countries like China, Vietnam, Uganda, India, we expect to
(44:20):
be growing a lot. The US has had in the
past a very significant decline in its complexity, and you
see it a little bit in how reliant the US
is on value chains outside the US, even for sophisticated
products like semiconductors and stuff. So in our current research,
we're also exploring a major change that is coming that
(44:42):
we know is coming, it's in the process, it's already happening,
which is this decarbonization process. What is de carbonization going
to do to the world, to global economy. Obviously, countries
that export oil and natural gas and coal are going
to face headwinds, But countries are going to to need
solar panels and windmills and fertilizers that are green and electoralizers,
(45:06):
and so there's a lot of stuff that will be growing.
So the structure of global demand will be shifting, and
we're trying to exploit ways in which we can help
countries figure out how they can grow in a world
that is attempting to decarbonize, and that is a very
different frame from the current frame. The current frame is
countries are being asked by the Paris Agreement, tell me
(45:29):
what are your commitments to lower your emissions. In our framework,
we are asking countries, look, the world wants to decarbonize.
What can your country do to enable the rest of
the world to buy the things that they will need
to decarbonize. Those are going to be your export industries.
(45:49):
Those are going to be the large, fast growing products
of the future. How can you get into them? And
we are putting that in the context of our product
space and our methods, et cetera, to figure out to
help countries figure out paths to growth that will help
the world of.
Speaker 1 (46:05):
Carbonis Ricardo Houseman. This was such a great conversation. Can
we do a live episode with you at some point
where people just throw goods and countries at you and
we on stage and you just sort of tell a
little bit of competition. Can we can we do that
at some point in the future, will come to you
wherever you are and make it happen. I think it
would be really a lot of fun.
Speaker 3 (46:25):
I would definitely have fun.
Speaker 1 (46:27):
Okay, I'm so. I actually had tons of more questions
like how random like little islands become like helicopter export hubs.
But this was so great. Really appreciate you coming on.
Fascinating conversation. Thank you so much for coming on outline.
Speaker 3 (46:41):
Thank you, thank you, thank you.
Speaker 1 (46:42):
For having me, Tracy. I really want to do that
where we get Ricardo out of stage and someone goes,
like men's suits, and then he tell us the history
(47:02):
of like which country is sell the most men's suits,
so what they used to sell, and why one country
stopped because they started producing some get the soccer cleats
whatever it is, and which are whatever it is. I
think that would be really fun.
Speaker 2 (47:15):
The evolution of those manufacturing and lunch capabilities. I will
say that, I think for the rest of my days,
whenever I think of economic development and diversification, I'm going
to be envisioning monkeys swinging from tree to treat a tree.
Speaker 1 (47:29):
Yeah, grabbing all these I love it. Such a vivid
image of how like an economic ecosystem works.
Speaker 3 (47:35):
Now.
Speaker 1 (47:35):
I really enjoyed that. And it's sort of like all
these things that like sort of like a bunch of
things clicked in that conversation.
Speaker 2 (47:41):
Well, here's the most important question. Do you think it's
going to help you be better at trade all No,
because I'm not.
Speaker 1 (47:47):
Good at geography, and so like maybe I don't know,
maybe it will. I think I just need to study
the map.
Speaker 2 (47:53):
You don't need the geography.
Speaker 3 (47:54):
Hint.
Speaker 2 (47:54):
If you get it in your first go, Joe, that's
what you should be aiming for.
Speaker 3 (47:58):
You know.
Speaker 1 (47:58):
What I thought was really interesting was like this idea
of like getting out of the resource curse is not
as straightforward as just oh, we're going to do more
with the thing that we already sell. So yeah, and
his point about Dubai was really interesting, how like there
are things that might go into selling a resource, like
having a port or having cold storage chain, or certain
(48:20):
things that aren't necessarily the thing itself, and that often
these sort of like the new trajectory of development may
not be that thing, but some of the other goods
and services that went into making the thing.
Speaker 2 (48:31):
Well, the other thing that is sort of important in
that conversation is the idea of governments making specific decisions
about this, and that certainly comes into play with Dubai.
You know, Dubai made a very conscious decision acknowledged that
it wouldn't have oil forever and so it needed to
diversify its economy and then proceeded to do so. I
(48:52):
think it's true in places like South Korea that also
score very high on complexity nowadays, they had a lot
of different types of industrial paul and also media policy, yeah,
to make k pop a thing, which we've discussed previously
on the show, and even some small island nations that
become helicopter manufacturers. To your point, Joe, I think there's
(49:13):
a lot of direction taking place there as well.
Speaker 1 (49:15):
The world is so interesting now. I think I'm going
to spend the rest of the day looking at the
atlas of economic complexity and just like clicking from country
to country.
Speaker 2 (49:23):
It is really fun. And I know Ricardo spoke about this,
but you can look at sort of suggestions or feasible
opportunities for future economic development, which is really really fun.
Speaker 1 (49:34):
That is really fun. And maybe I just might memorize
every single one so that I could get all the
tradells in one.
Speaker 2 (49:40):
Do we need to do competitive trade all competition?
Speaker 3 (49:42):
Yes?
Speaker 2 (49:43):
I think that should be our next live event. All right,
shall we leave it there, Let's leave it there. This
has been another episode of the ad Thoughts podcast. I'm
Tracy Alloway. You can follow me on Twitter at Tracy
Alloway and.
Speaker 1 (49:54):
I'm Joe Wisenthal. You can follow me on Twitter at
the Stalwart. Follow our guest Ricardo Houseman on Twitter. He's
at Ricardo Underscore Houseman. Follow our producers Carman Rodriguez at
Carmen Arman 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 dot
(50:15):
com slash odd Lots, where we have transcripts, a blog
in a newsletter, and we have a trade all room
in the discord where you Discord dot gg slash odd
Lots listeners are in their twenty four to seven talk
about all these topics, and there is a room where
everyone posts how they did on the Trader that day.
So a play the Trade oll and b post your scores.
Speaker 2 (50:37):
And if you enjoy all thoughts, please leave us a
positive review on your favorite podcast platform. Thanks for listening,
Hello, and welcome to another episode of the Odd Lots Podcast.
Speaker 2 (00:14):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 1 (00:16):
Tracy, I'm super late to everything. First of all, did
you play Wordle?
Speaker 2 (00:21):
I did. I didn't get obsessed with it like some
people did, but I think we were all fairly bored
during that time period and on the lookout for any
sort of entertainment.
Speaker 1 (00:31):
And it never clicked. But I'm always late to everything.
Like a year ago, people were telling me it's like, oh,
you gotta play this game trade all, and I did end,
but like three or four months ago, I started really
getting into it, and I think you're into it now too.
Speaker 3 (00:44):
Yeah.
Speaker 2 (00:44):
I think we both started playing around the same time,
probably because we heard about it from the same person.
It is a fun game, so for those who don't
know it is like Wordle. It basically presents a sort
of graphic schematic of an unnamed country's exports, and you
have to try to guess what country it is.
Speaker 1 (01:06):
Yeah, exactly, And I'm not very good at geography, so
often it'll say like, Okay, you're close, but it's like
you have to go fifteen hundred kilometers to the northwest.
I'm pretty bad at geography, so I'm not good. But
as playing this game and watching the way the different
shapes of different countries export mix, I feel like I've
really started to learn things about the world.
Speaker 2 (01:29):
I have learned so much about the economy of Angola.
Speaker 3 (01:32):
Right.
Speaker 1 (01:33):
So you see a country and it's like eighty percent
of their exports are like coffee in gold, right or
something like that, and you're like, Okay, this is a
relatively poor country. It has a lot of growth left
to do. And then you see another country and it's
like advanced circuits and medicine and hangars and bananas and
(01:56):
all this stuff, and like, oh, and you start to
see these shapes and these distributions. That's sort of like
tell you things. It's like, Okay, I can guess maybe
this is in Europe, or maybe they have a lot
of things, maybe it's in Eastern Europe. You suddenly sort
of learn like how rich countries goods exports really differ
from poorer countries goods exports.
Speaker 2 (02:12):
Yeah, totally. There are three clues that it gives you.
One is distance, as you just mentioned, and the other
is total size of exports. So that gives you an
indication of how big or small that economy is. And
then that third thing is the nature of the exports,
and it sort of divides them up into different categories,
but it gives you a really good snapshot of a
(02:34):
country's economy. And as you play the game, you start
to recognize I guess certain economic export attributes. Yeah, go
with certain types of countries or economies.
Speaker 1 (02:47):
Right, so integrated circuits and palm oil, probably Southeast Asia, right,
something like that. Anyway, this game that you and I
have become obsessed with, it's sort of based on this
work related to economic complexity, the Atlas of Economic Complexity,
this sort of idea, and this is something that's come up.
It came up in an episode we did with Henry
Williams and David Os. It came up with the episode
(03:10):
we did with Dan Wong and why some countries can
develop airline industries and other countries can't. This idea that
complexity of goods exports complexity is in itself a sort
of predictor of wealth.
Speaker 2 (03:24):
Yeah, and maybe it's also a desirable model for countries
to sort of aspire to, this idea that maybe they
want to get away from simply producing a bunch of
t shirts, So like fifty percent of their economy is
T shirt exports or something like that. They want to
get to a place where they have expertise across a
broad and value added sort of realm of exports.
Speaker 1 (03:48):
Or maybe they export a lot of nickel and they
want to be in like refined nickel, right, some nickel
relatais the commodity just pure Anyway, this has sort of
like really opened up a lot of these conversations playing
like thinking about the world. So I'm really excited about
our guest because our guest has done more work on
this idea of economic complexity and why nations are able
(04:08):
to develop complex, rich economies. He's also the creator of
that at list of economic complexity. We're going to be
speaking with Ricardo Housman. He's a professor at the Harvard
Kennedy School and the founding director of the Harvard Growth Lab.
All of my trade off friends are super excited about
listening to this conversation. Doctor Husman. Thank you so much
(04:29):
for coming on odd Lats.
Speaker 3 (04:31):
Oh, it's a pleasure to be with you. Thank you
for inviting me.
Speaker 1 (04:34):
Absolutely. What is economic complexity?
Speaker 3 (04:38):
Economic complexity is an attempt to measure how much countries
or places know what to do, so like I try
to measure no. How Now, if you want to think
about knowledge and say, well, and I know people who
have a bachelor's degree, people who will hire high school dropouts,
people who have a PhD. That sort of tells you
(05:01):
how much a person knows. But if you ask yourself,
how much does a society know, well, that would be different.
That would not be characterized by the average, say the
average number of years of schooling that the society has.
Not A society that is full of just dentists will
know less than a society that is half dentists and
(05:24):
half lawyers, or a society that is a third dentist,
a third lawyer, or third engineers. So in some sense
you want to know how much the whole of society knows.
And one of the important things about knowledge is that
knowledge at the societal level has been exploding exponentially, but
(05:46):
our mental capacity to know has not. So the way
the economy has been adapting and adopting growing amounts of
knowledge is by putting different bits of knowledge in different heads,
sort of like parallel processing. You know, if you want
to run a company, you will need somebody who knows
(06:07):
about accounting, about finance, about marketing, about human resource management,
about contracts, about taxes, about procurement, about engineering. So you
want to have a lot of knowledge to run these things,
but you cannot stuff that knowledge into a single head.
You have to spread it into a bunch of heads,
(06:27):
and then you have to bring those heads together back again.
You have to kind of put humpty dumpty back together again.
So the way in which a society grows is it
grows its knowledge by putting different bits of knowledge in
different heads and then by bringing those heads together. Now,
if a society makes very simple things, it makes things
(06:50):
that can be done by few people, because the knowledge
that is needed to make one of those things, you know,
fits in just a few heads. But if you're going
to do stuff that requires not a lot of knowledge,
you'll have to bring many, many more of these heads together.
You'll have to network these brains together to make that thing.
So complexity emerges as the consequence of distributed knowledge in society.
(07:14):
You have different bits of people knowing different things, and
then you have to bring those things together, and then
these complex networks emerge from that process. So, in some sense,
what is really driving growth is this growth of knowledge
and the growth of using that knowledge, and consequently it's
in this spread of different bits of knowledge in different
(07:36):
heads and the ability to bring those heads together to
make relatively long chains of brains.
Speaker 2 (07:43):
I have a bunch of questions already about comparing and
contrasting measuring complexity versus the way economics has traditionally handled
some of this. But maybe a step back question why
did you decide to start looking into this? What is
the benefit of looking at complexity within a particular society
or economy.
Speaker 3 (08:04):
It goes back to the question and when Adam Smith
asked himself what's the source of the wealth of nations?
He said it was the division of labor? But why
the hell would the division of labor matter? And he
gives a thin factory example that if you split the
work and this guy does the head and this guy
does the body, et cetera, that increased productivity. That idea,
(08:26):
I think has a kernel of what the story is.
But this stuff becomes incredibly powerful when you're talking about
knowledge driving the economy and driving society. So it's really
about the division of knowledge that's what drives growth. It's
the division of knowledge that allows the whole to know
(08:46):
more than its parts. And so how would you go
about measuring what a society knows how to do. Well,
let's look at what they do, because if they do something,
it means that they know how to do it right,
So it's proof that they know how to do it.
So we can look at what a society does to
figure out what is it that they know how to do.
(09:09):
So when you look at a country and say, okay,
this country is only good at doing a few things,
and this other country is good at doing many more things.
And this country here is making things that seem to
be simple things that can be done in small groups.
This other country that has to do things that require
this very broad network of brains coming together to make something.
(09:30):
It tells you something about how those economies are managing knowledge.
Speaker 1 (09:35):
Tracy is sort of hinting at this, and I want
to sort of drill down on this before moving on.
You know, there are various traditional ways in which we
measure economies. GDP is more or less a different way
of like you just add up everyone's income and you say, okay,
this country is richer than this country, and this country
is richer than the next. Give us the basics. You
know you have country A and country B. How do
(09:56):
you like measure? Okay, this country is more comp more
complex economy capable of more complexity than country be.
Speaker 3 (10:04):
So let me first say you can measure GDP and
so GPS how much countries are able to make in
terms of income. That doesn't tell you why they are
able to make it. Economic complexity is trying to get
at why is it that you are able to generate
more income? What's underpinning that? And for that, we like
to measure how much a society knows in our standard measure.
(10:28):
We've now applied it to a whole different bunch of fields,
not just in exports but other things. But we started
with exports, and the reason why we started with exports
is because we needed a data set that included all
the countries in the world, so we could benchmark all
the countries in the world with a standardized classification. And
since international trade it involves different countries, they've all agreed
(10:49):
on some common classification scheme, so it was expedient for us.
But experts are also something that tells you whether a
society is good enough at making something that it is
able to sell abroad, So it's kind of like a
litmus test that you're pretty good at making something. So
I don't really care how much they make. I just
(11:12):
care that they are able to make it, so that
that knowledge is somewhere in that society. So the way
you would think about calculating how much knowledge of society
has would say, tell me how many different things that
are they able to make? You're mentioning angola, or they
make mostly oils essentially that's their thing, or do they
do many things? So the diversity of their export basket
(11:34):
is kind of like a first cut, right, But you
would say, well, but products differ in how knowledge intensive
they are and how difficult they are to make. So
we found a trick on how to measure how difficult
it is to make a product by simply asking the
question how many countries are able to make this product.
So if you talk about raw wood, many many countries
(11:56):
export raw wood. If you tell me about microscopes or
X raymage, very few countries are able to export those things.
So that tells you something already about how difficult it
is to make these things, right, So we call that
the ubiquity of a product. And then you can ask
yourself the question, Okay, on average, how ubiquitous are the
(12:17):
products that this country makes? That is this country making
mostly things that are simple to do that everybody knows
how to do, or or they make things that are
hard to do, things that are done in few places.
So that's kind of like a different cut out of
the data. And you simply repeat this process an infinite
number of times and it generates an algorithm that ranks
(12:40):
both the countries in terms of how complex they are
and the products in terms of how complex they are.
So essentially, it's an operation on this matrix if you
want that relates countries to the products that they make.
It is an eigenvector of that matrix. Essentially, if you
want to get fancy at the mouth, but it captures
(13:00):
this idea how many things are we able to do
and how complicated it is to do those things.
Speaker 2 (13:21):
So is it possible to have a good economic outcome
with low complexity? Or I guess another way of saying
this is is complexity as synonym for development or wealth here?
Or capturing something different? Could you have a country that
scores low on complexity but is still a relatively good
(13:43):
place to live from an economic perspective.
Speaker 3 (13:47):
So one major thing that economic complexity does not capture
is natural resource wealth. Okay, so when you make a graphs, say,
of the relationship between how complex you are are and
how rich you are, the outliers tend to be countries
that are natural resource rich. So they get their income
(14:08):
not so much by what they know how to do,
but from the natural resource wealth that they happen to have.
Speaker 2 (14:16):
So a place like the United Arab Emirates or Saudi
Arabia perhaps might score low on complexity, but they have
a ton of oil wealth and so they're still quite
prosperous on a GDP per capita basis that sort of
thing exactly.
Speaker 3 (14:32):
So, or you could say, tell me, controlling for their
natural resource wealth, they have a lot of complexity or not.
And let me tell you a few of the things
we have established. The first one is that the complexity
correlates very highly with how rich you are, and if
you control for your natural resource wealth, it correlates even better.
(14:52):
So there's a very strong relationship between economic complexity and
natural resource and your GDP per capita in level. So
that's a very strong relationship. But more importantly than that,
countries that are more complex than you would have expected
them to be given their income level tend to grow
(15:13):
faster in the future, and countries that have relatively low
complexity relatives to their income level tend to grow less
in the future. So your economic complexity relative to your
income level is a predictor of how fast you will
be able to grow. And typically when we look at
how good these predictions are, they tend to be best
(15:34):
at a horizon of about ten years, So it tells
you something about what your next decade is likely to
look like.
Speaker 1 (15:41):
What's an example of maybe something in history in which
at some point a country scored significantly high complexity and
then did it over the next several years. It's like, yeah,
this country really boomed. What's an example that stands.
Speaker 3 (15:55):
Out of this, Well, there are many examples, but suppose
if you have take the picture in two thousand and eight,
two outliers were India and Greece. India had extremely low
income levels for its level of complexity, and Greece had
extremely high income levels for their level of complexity. And
what happened is that India has been the fastest growing
(16:18):
large country in the world since then, and Greece collapsed.
So we also see countries that increase their complexity initially
by moving into a new set of products. In the
case of Thailand, they first moved into garments and spent
a whole decade adding a bunch of different garments to
their export baskets. Suddenly they got into electronics and then
(16:41):
started to add a bunch of electronics to their export basket,
and then they got into cars and machines and so on.
So they have been increasing their complexity and have very
sustained high growth rates in the process. In general, what
we find is that only about a fifth of the
countries that were poorer than the US, say, in nineteen
(17:02):
seventy have really caught up narrowed the gap with the US. Okay,
since nineteen seventy onwards, only twenty percent of countries narrowed
their income gap with the US. Those twenty percent of
countries that narrow their income gap with the US increase
their complexity very significantly. The other eighty percent did not.
(17:25):
So I would tell you that sustained growth implies this
process of absorbing knowledge, distributing in a your society, mobilizing
that knowledge to make more things and more complex things.
Because you get more complex. Things are essentially things that
require more knowledge, and things that require more knowledge require
(17:46):
deeper networks of humans collaborating, whether it's in a single
firm or in a longer value chain.
Speaker 2 (17:52):
Can you talk a little bit more about how you
build complexity and diffuse that knowledge within a society, because
I am imagine if you're a developing country, maybe you
find that you have a competitive advantage in one type
of thing. I'm going to go back to the T
shirt example. You can make T shirts cheaper than anyone
(18:12):
else and more efficiently, I guess, And then I would
imagine the temptation is to just stick with that specialization
and just do the thing that you are currently really
good at. So how do countries actually break out of
that dynamic and start developing expertise in other areas.
Speaker 3 (18:31):
There are essentially three mechanisms that I would like to mention.
The first one is that countries tend to move from
where they're good at to what I like to call
or Stuart Kaufman coin the phrase the adjacent possible. When
we look at countries adding products to their export basket,
(18:53):
those products tend to be cognitively near. If you want
the products that they were making before. And one of
the contributions we've made is we've developed a technique to
measure this cognitive proximity for all the products in the world.
And you can locate every country in the world and
(19:14):
find out what's in their adjacent possible So countries tend
to move from the things that they are currently good
at to things that are in their adjacent possible And
we call this cognitive map of the products of the world.
We call it the product space. And this product space
is very heterogeneous. There are some parts of the product
space there where you have products that are tightly connected
(19:37):
to each other. So if you know how to make
one kind of product is kind of like easy to move.
You have a rich adjacent possible. You have many ways
of reorganizing that knowledge to make other things. We like
to use the metaphor that products are like trees, and
firms are like monkeys. They live on trees, they exploit
certain trees. So the product space is like the map
(19:59):
of the forests. And so you can, by the way,
if you go to the Atlas and Economic complexity, we
have the we choose a country, we have the product space.
We will tell you where in that forest, does this
country have its monkeys, and then it can tell you
know which trees are close to those monkeys, and it
(20:20):
can tell you so you know, what are other characteristics
of those trees that might make it sexier or less
sexy to move in that direction. Okay, so the first
thing I want to say is that countries tend to
diversify by moving to their adjacent possible depending on where
they started, and not every country starts with the same
deck of cards. They don't start with their monkeys in
(20:42):
the same place. Some countries start with their monkeys in
very very promising parts of the product space because their
trees are very closely connected to each other there, so
it's easy for the monkeys to jump from tree to tree,
and other parts of the product space are very sparse
with their trees are very far from each other, so
(21:03):
it's hard for those monkeys to move. Okay, So that's
mechanism one, move towards the adjacent possible. Mechanism two is
that you have to solve this chicken and neck problem.
You don't know how to do the things you don't do,
but you need to know how to do things to
start doing things you are not doing before. So you
(21:25):
need watchmakers to make watches. But how do you become
a watchmaker in a country that doesn't make watches. How
do you solve this chicken and egg problem. We think
that this solving the chicken and eck problem is the
thing that forces countries into moving just to the adjacent
possible because it's hard for them to solve too many
(21:47):
of these chicken and egg problems at the same time.
But one way to accelerate the solution of these chicken
and eck problems is to bring watchmakers from outside your country.
That is, you may not have what makers in your country,
but maybe you start with a group of Swiss watchmakers
and they'll train the next generation of watchmakers and now
suddenly you do watchmaking right. So migration plays an outsized
(22:11):
role in diversification because you need to add knowledge that
was not in the system before. So if you can
attract people that had knowledge that was not in the
country and you can engage them having worked there and
have that knowledge spread, that seems to be very important.
There's a very nice story about Bangladesh here where you know,
(22:33):
if you look at Bangladesh in the ATHLETs of economic complexity,
you'll tell you that ninety percent of their exports are
garments and that they all started in the eighties. These
exports of garments, Well, what underpinned that was a company
which was called Desh and that company sent one hundred
and twenty six of its workers for six months training
program in Korea. Because the program that company was created
(22:56):
by Dai Wu. So these guys went to Korea. Yeah,
trained in Korea, came back, started the company and started
to produce. Fifty six of those people left the company
to create their own startups, and those fifty six children
of this company DSH are the core of the export
(23:17):
industry of garments in Bangladesh. So in some sense you
have to infect the system with knowledge and assure that
the mechanisms are going to allow that knowledge to spread.
Speaker 1 (23:29):
Tracy prefaced the question. She talked about a country that
exports a lot of cheap T shirts and we sort
of think of a T shirts as being low value,
and you just mentioned the beginning of Bangladesh's process to
become wealthier and had a textile export company. But even
at least a T shirt, there's going to be some machinery,
there's going to be this something of a commodity supply
(23:50):
chain that has to be organized. There are certain engineering
aspects of it versus say, another country that may export
cocoa and coffee, in which I imagine that maybe it's
roughly the same level in terms of income, but strikes
me as a simpler process of selling coffee, beans or cocoa.
Are there certain goods like that consistently that, even though
(24:14):
they may seem rudimentary our early predictors of okay, at
least this country has some capacity to have monkeys jump
from tree to tree, so to speak.
Speaker 3 (24:24):
You have given a fantastic example of what makes parts
of the product space denser and what makes parts of
the product space sparser, because garments are in a dense
part of the product space. If you know how to
make one kind of garment, you can make very different
kinds of garments. But in order to make garments and
(24:44):
export them competitively, right, you need to have an industrial
zone where materials can go in and out, where workers
can go in and out, where there's power, where there's water,
where there's a good logistic election to a port or
to an airport, right where the custom service works more
(25:06):
or less well, and maybe has to do complex sophisticated
things like letting the textiles come in in bond without
paying VAT and tariffs so that if they are going
to be exported, so you save on these transaction costs.
So getting government industry going is pretty complicated, and it
(25:26):
has taken fifteen years for Ethiopia to get into it,
and they're ballion. They had to build these industrial zones,
they had to provide electricity to these industrial zones. They
had to build a railway to Djibouti. An incredible number
of things that were not there that were part of
so like the ecosystem that garments require. But once you
(25:49):
have that ecosystem, well in the same industrial zone, maybe
with the same port and the same electricity and the
same water and maybe even the same workers, you could
s electronics. Maybe you can do some auto parts. In
the end. What's the difference between a car seat and
another leather product, So you may start producing things for
(26:11):
the auto industry and so on. So these things, so
garments would have many neighbors. It's easier to move from
garments to other things then to move from co co
to other things. Because you know, if you make coffee, well,
coffee grows in the tropics between nine hundred meters above
sea level and thirteen hundred meters above sea level let's say,
(26:32):
between three thousand and four thousand feet, And it requires
a tree to provide shadow. And so if you suddenly say,
you know what, I'm not going to grow coffee anymore,
I'm going to do something else, well, what else are
you going to do between three thousand and four thousand
feet altitude? It's in a mountainous region. So it does
(26:53):
not make diversification from coffee into other things very easy.
But diversifying in an an industrial song from one kind
of manufacturer to another kind of manufacturer is much easier.
Speaker 2 (27:05):
You know, I kind of enjoy it just hearing the
specific examples of how this works. Do you have a
favorite example of this sort of monkey's jumping from trees
dynamic or maybe even one going in reverse? Like, I'm
curious how that happens as well, how an economy would
maybe lose complexity over time.
Speaker 3 (27:24):
Okay, so let me maybe give you an example of both.
You know, a lot to increase in complexity in Japan
and Korea did not happen because new companies were created
to do more things, but because established companies, these chiballs
in Korea, these kde etsus in Japan, diverse to fight
internally into more things. So a company like Samson started
(27:47):
in sugar trading, and you know now they are the
largest producer of semiconductors and s grams and TV screens
and smartphones. That process of transformation happened inside the company,
and it happened by adding capabilities to their capabilities. So
for example, you'd say Finland is a country that had
(28:08):
a lot of trees, and traditional development economists would have said,
cut those trees and sell wood. And then they would say, no,
don't don't sell wood. Make furniture with that wood, or
make paper with that wood. Add value to your raw materials.
But that's not where the story really went. It's sort
of like Finland had a lot of trees, so they
have to cut the trees. But to cut the trees,
(28:28):
you need tools to cut trees. You need machines to
cut trees. So they became good at tools and machines
that cut wood, and from there they moved to tools
and machines that cut because not everything is made out
of wood, and from there they made they went to
automated machines that cut, because cutting everything by hand can
be either boring or imprecise. And then they said, you know,
(28:51):
from automated machines that cut, they want to just automated machines.
Why do we need to cut? There's more to life
than just cutting, right, And then from autumnate machines they
ended up in Nokia. So the process is a process
of adding capabilities to your capabilities, because once you know
how to do something, there is something in that cognitive
(29:12):
vicinity that you could do. Now. An interesting example of
going backwards is let me give you the example of
South Africa. South Africa is a country that has a
lot of coal mineral resources, and they knew how to
transform that coal into cheap electricity, and that cheap electricity
(29:35):
made them very competitive in mining and in metal processing
and in relatively energy intensive manufacturing. Now they messed up
their electricity company. Their electricity company lost the capacity to
sell cheap electricity, and now they not only have expensive electricity,
(29:56):
they have very lousy electricity with a lot of blackout
and something called load shedding, so like plan shutdowns, and
that has made manufacturing activity very very complicated, and that
has caused them to lose a lot of complexity, so
in say nineteen ninety, they have the same complexity as China,
(30:17):
and now China has increased its complex complexity dramatically and
South Africa has gone in the opposite record.
Speaker 2 (30:41):
Since you mentioned the Japanese and Korean conglomerates just then,
that reminds me of something I want to ask you,
which is, is there a point at which there can
be too much complexity? I'm imagining, for instance, a big
company and suddenly they have their fingers in a thousand
different parts, and maybe they're okay at doing a bunch
(31:02):
of those things, but maybe they're not particularly good at it,
and it becomes inefficient and the sort of like lumbering
everything everywhere, all at once. Entity is that a concern
at all, either on a corporate level or on an
economy wide level.
Speaker 3 (31:18):
I think it's more on a corporate level than on
an economy white level. I would say, if you're a company,
maybe you realize that there's this adjacency that you could exploit,
and maybe you start exploiting that adjacency, But then you
realize that managing the two organizations might be too complex,
so you spin it off, and spin offs sell part
(31:40):
so that you keep a coherent entity that's easier to manage.
That's great, But if you spun it off, it means
that somebody else bought it, and somebody else is using
that knowledge to produce those things. So I think it's
a concern for firms. How do you keep your coherence?
I would say, still explore. I think there's a lot
(32:00):
of value in exploring your adjacency, developing that adjacency, and
maybe spinning it off later on, and it will add
to the value of the company. At the societal level,
I don't see any evidence of that. I see societies
that are relatively small and are amazingly complex. I'll give
you the example of Slovenia. Who would have thought a
(32:20):
country of two million people, they export thirty five billion
dollars or more and an incredibly large diversity of things.
They're super plugged in to value chains in Austria, value
chains in Germany. In they do pretty sophisticated stuff and
with only two million people. So I don't think there's
(32:42):
too much limit to the growth of complexity because there
isn't that much limit to the growth of knowledge in
a society, and you don't have to be big, to
be very knowledgeable as a society.
Speaker 1 (32:55):
I have so many questions. I loved your sort of
like brief industrial history of Finland. And it's like, you
go from exporting wood, then you have tools that cut wood,
then you have tools that cut, and then you have
things that do things that don't just cut, and then
you have no suddenly of no can it makes a
lot of sense you describe it. I'm curious. Generally speaking,
we've seen countries lately who are major exporters of raw
(33:18):
commodities attempt to move up the value chaine, so to speak,
by insisting that, say, a mining company in Indonesia can't
just come and take the nickel and sell it, that
they need to set up some sort of domestic refining
operation in Indonesia, so that something more complex than just
selling the nickel. What is your history teach us about
(33:40):
countries that have done a better job or not of
getting out of, say the so called resource curse. Are
there certain strategies that work better than others in terms
of a country not just being dependent on a single
commodity that does not have many adjacencies.
Speaker 3 (34:00):
So let me say that one of the most passtrating
ideas in the field of economic development is the idea
that you should focus on adding value to your raw
materials because there's so much more you can do. Then
the things that can be done by relying only on
the raw materials that you happen to have. Your opportunity
(34:22):
set is much much wider than that. So, suppose you
have nickel, It may make a lot of sense to
process the nickel locally because when your mind something, you know,
if it's a good mind, it might have two percent
nickel or three percent nickel. So you want to separate
ninety eight ninety seven percent stuff so you don't have
(34:44):
to transport that much stuff that is worthless, right, so
you want to do the refining and some of the
processing nearby, just to save on transportation costs. But if
you're going to do a lithium ion battery, well you
might have the nickel, but you don't have the lithium,
you don't have the chromium, you don't have the other
minerals that go into it. So you will have some
(35:08):
of them, but you will have to import the other ones. Now,
think if you're trying to make a cell phone, Well,
what is the raw material that you have to have
locally that will make the cell phone, well, I mean
too many none. So if you are going to be
making cell phones, it's because you are going to be
able to connect to a bunch of value chains between
(35:30):
the people who are able to make the memory and
the processors and the screen and the touch screen, you know,
the surface that can detect where your finger is and
all these different parts. So that that doesn't happen in
a single company, that happens in a bunch of many companies.
(35:51):
So if you want to get into that kind of thing,
which might be possible. So say you are in Legos, Nigeria. Well,
Legos is a port city, so anything you need you
can bring into the port. You don't have to have
that raw material in your country. So in general, I
would say, if you have raw materials, maximize the value
of your raw materials. But most of the things that
(36:12):
you could do next may have nothing to do with
processing those raw materials. And the best example here is Dubai.
Dubai long many moons ago had oil, it no longer
has oil. Abu Dhabi has oil, but Dubai doesn't have
oil anymore. But Dubai has an airport that is a
major hub. It has Emmerate Airlines, which is a major airline.
(36:34):
It has Dubai Ports, which is a network of global ports.
It has a lot of logistics. It has the regional
headquarters of multinational corporations, It has universities where people go
to study there, et cetera. So they have added a
lot of stuff to their If you want export basket
that is super distantly related to oil, they would probably
(36:56):
not have gotten there had they not have oil. That
allowed them to build that infrastructure, that to build the amenities,
to build the things that are attracted and the other activities.
But they are not about oil refinding, they're not about plastics,
they're not in the value chain.
Speaker 2 (37:11):
Avoid the way you described the way that diversification or
development works, this idea of monkeys jumping from tree to tree.
It sounds very naturalistic, like a natural progression of expertise.
But I'm curious what role you think government policy could
play in that process, particularly in the context of what
(37:35):
we see nowadays, which really seems to be a resurgence
in some parts of the world in industrial policy that
is aimed at developing specific new types of technology or capabilities.
Speaker 3 (37:47):
Well, definitely, I think that the government has a lot
of useful things that it can do. First of all,
every technology, every industry lives in a environment of relatively
specific public goods that the government needs to provide. So,
for example, suppose the society adopts the car as a technology,
(38:11):
and for transportation, well, cars need roads, Cars need traffic rules,
Cars need traffic lights and traffic signs. They need traffic
cops to enforce those rules. So the car technology lives
in an environment of public goods that make that car useful.
(38:32):
A car with no roads it would be useless. A
car in roads with no rules and no traffic signs
and so on may be too dangerous. So that technology
lives in an environment of public goods. And typically governments
are pretty lousy at producing the public goods that are
needed by the industries that exist. They are typically hopeless
(38:56):
in producing the public goods of the industries that don't
yet exist. So if you want that industry to exist,
you need to make sure that the public goods that
that industry will require are provided. So, for example, it's
going to be extremely difficult to sell electric vehicles in
a society that cannot assure people that they are going
(39:19):
to be charging stations, but nobody is going to build
charging stations for a market of electric vehicles that does
not yet exist. So these things can be addressed through policy,
these chicken and egg problems, these coordination problems, this provision
of public goods that industries are going to need. For example,
(39:41):
suppose that you want to export a fresh blueberries the
way Peru does, Okay, and they're the major exporter of
blueberries these days. An industry that started in Chile and
then moved to Argentina and now it's in Peru. Well,
you cannot export fresh produce if you do not have
(40:02):
a green lane in customs, if you don't have a
cold storage transportation chain what they call a cold chain,
if you don't have fit to sanitary agreements with the market,
you're going to be selling this stuff too. So that
industry is only going to exist in the context of
these public goods that make that industry feasible. So I
(40:24):
think governments have to engage in the nitty gritty of
the public goods that new industries need, and they'll have
to get engaged in the nitty gritty of chicken and
egg problems. Even within the private sector that could like
the example I gave you of the charging stations and
the eeds so that markets are able to develop. So
(40:46):
I do think that there's an important contributing role that
industrial policies can play to facilitate monkeys moving.
Speaker 2 (40:54):
I have just one more question, which is a very
important one. How good are you at trade all the
fact that you know that Peru is one of the
biggest exporters of blueberries nowadays?
Speaker 1 (41:04):
Is it just super nice history of which countries where
the blueberry exporters in the past.
Speaker 3 (41:11):
Well, I mean it's a bit unfair. This is my
day job, this is what I do, so it's not
on my hobby. So this is what I think about
all day.
Speaker 1 (41:22):
We talk a lot about and trade again, goods exports,
and there's a really good reason to look at exports
because there's that sort of like discipline of like you
can't force another country to buy your goods, and so
like looking at goods exports is really interesting. I'm curious
about work you've done of looking at services through the
complexity lens and can countries rise up and become rich
(41:44):
if they never go through the manufacturing process, because as
you talk about, you know, manufacturing links all different kinds
of things supply chains, ports, electricity systems, cutting, and various
things like that. Can it be done through the services.
Speaker 3 (41:56):
Room, I think? So let me give you the example
of Panama. Panama had a canal and the canal was
run by the Americans, and the Americans just wanted the
ships to go through. So when the Panama can became
Panamanian in nineteen ninety seven, so they started to think, okay,
what can we do with the canal. Well, we want
the ships to not just go through, but to stop,
(42:18):
So let's build some ports. Maybe, let's do some logistics,
some transshipment. They said, well, what do these people need?
They need a financial services, so why don't we create
an offshore financial center. And then they decided, you know what,
why don't we become a hub for regional multinational headquarters.
And they happened to stumble into having a very successful airline,
(42:42):
Copa Airline. It's the more successful company in the region.
So that made having regional headquarters and multinational corporations very
practical because from Panama City you can go to anywhere
in Latin America and the US and a bunch of
other destinations. So suddenly you have a bunch of people.
They have some forty thousand people who work at multinational
(43:04):
corporations under special visas that work in Panama, and they
want to have amenities, restaurants and museums, cultural activities, good schools,
good healthcare. So guess what. You become a good destination
to attract other people and other talent, and you become
a good tourist destination. So in the example I've just
(43:24):
given you, it's a bunch of service industries that are
connected to each other. And by the way, Panama is
the country in Latin America that has had this has
dispost over the last thirty years.
Speaker 1 (43:35):
I realized I have one more really important question that
we can't leave a I'm curious, like you have new
research out, So is there anything that jumps out at
you right now in terms of which countries are on
the move, what is the big picture trends in her
who's moving? And like what is happening here in the
richest country in the world, or I think are pretty
close to it in terms of trends in our own complexity.
Speaker 3 (43:59):
Here. First of all, let me invite your listeners to
all visit the aplus of economic complexity we have just
updated it with twenty twenty one data and we run
growth projections for the following decade, and there you'll find
that countries like China, Vietnam, Uganda, India, we expect to
(44:20):
be growing a lot. The US has had in the
past a very significant decline in its complexity, and you
see it a little bit in how reliant the US
is on value chains outside the US, even for sophisticated
products like semiconductors and stuff. So in our current research,
we're also exploring a major change that is coming that
(44:42):
we know is coming, it's in the process, it's already happening,
which is this decarbonization process. What is de carbonization going
to do to the world, to global economy. Obviously, countries
that export oil and natural gas and coal are going
to face headwinds, But countries are going to to need
solar panels and windmills and fertilizers that are green and electoralizers,
(45:06):
and so there's a lot of stuff that will be growing.
So the structure of global demand will be shifting, and
we're trying to exploit ways in which we can help
countries figure out how they can grow in a world
that is attempting to decarbonize, and that is a very
different frame from the current frame. The current frame is
countries are being asked by the Paris Agreement, tell me
(45:29):
what are your commitments to lower your emissions. In our framework,
we are asking countries, look, the world wants to decarbonize.
What can your country do to enable the rest of
the world to buy the things that they will need
to decarbonize. Those are going to be your export industries.
(45:49):
Those are going to be the large, fast growing products
of the future. How can you get into them? And
we are putting that in the context of our product
space and our methods, et cetera, to figure out to
help countries figure out paths to growth that will help
the world of.
Speaker 1 (46:05):
Carbonis Ricardo Houseman. This was such a great conversation. Can
we do a live episode with you at some point
where people just throw goods and countries at you and
we on stage and you just sort of tell a
little bit of competition. Can we can we do that
at some point in the future, will come to you
wherever you are and make it happen. I think it
would be really a lot of fun.
Speaker 3 (46:25):
I would definitely have fun.
Speaker 1 (46:27):
Okay, I'm so. I actually had tons of more questions
like how random like little islands become like helicopter export hubs.
But this was so great. Really appreciate you coming on.
Fascinating conversation. Thank you so much for coming on outline.
Speaker 3 (46:41):
Thank you, thank you, thank you.
Speaker 1 (46:42):
For having me, Tracy. I really want to do that
where we get Ricardo out of stage and someone goes,
like men's suits, and then he tell us the history
(47:02):
of like which country is sell the most men's suits,
so what they used to sell, and why one country
stopped because they started producing some get the soccer cleats
whatever it is, and which are whatever it is. I
think that would be really fun.
Speaker 2 (47:15):
The evolution of those manufacturing and lunch capabilities. I will
say that, I think for the rest of my days,
whenever I think of economic development and diversification, I'm going
to be envisioning monkeys swinging from tree to treat a tree.
Speaker 1 (47:29):
Yeah, grabbing all these I love it. Such a vivid
image of how like an economic ecosystem works.
Speaker 3 (47:35):
Now.
Speaker 1 (47:35):
I really enjoyed that. And it's sort of like all
these things that like sort of like a bunch of
things clicked in that conversation.
Speaker 2 (47:41):
Well, here's the most important question. Do you think it's
going to help you be better at trade all No,
because I'm not.
Speaker 1 (47:47):
Good at geography, and so like maybe I don't know,
maybe it will. I think I just need to study
the map.
Speaker 2 (47:53):
You don't need the geography.
Speaker 3 (47:54):
Hint.
Speaker 2 (47:54):
If you get it in your first go, Joe, that's
what you should be aiming for.
Speaker 3 (47:58):
You know.
Speaker 1 (47:58):
What I thought was really interesting was like this idea
of like getting out of the resource curse is not
as straightforward as just oh, we're going to do more
with the thing that we already sell. So yeah, and
his point about Dubai was really interesting, how like there
are things that might go into selling a resource, like
having a port or having cold storage chain, or certain
(48:20):
things that aren't necessarily the thing itself, and that often
these sort of like the new trajectory of development may
not be that thing, but some of the other goods
and services that went into making the thing.
Speaker 2 (48:31):
Well, the other thing that is sort of important in
that conversation is the idea of governments making specific decisions
about this, and that certainly comes into play with Dubai.
You know, Dubai made a very conscious decision acknowledged that
it wouldn't have oil forever and so it needed to
diversify its economy and then proceeded to do so. I
(48:52):
think it's true in places like South Korea that also
score very high on complexity nowadays, they had a lot
of different types of industrial paul and also media policy, yeah,
to make k pop a thing, which we've discussed previously
on the show, and even some small island nations that
become helicopter manufacturers. To your point, Joe, I think there's
(49:13):
a lot of direction taking place there as well.
Speaker 1 (49:15):
The world is so interesting now. I think I'm going
to spend the rest of the day looking at the
atlas of economic complexity and just like clicking from country
to country.
Speaker 2 (49:23):
It is really fun. And I know Ricardo spoke about this,
but you can look at sort of suggestions or feasible
opportunities for future economic development, which is really really fun.
Speaker 1 (49:34):
That is really fun. And maybe I just might memorize
every single one so that I could get all the
tradells in one.
Speaker 2 (49:40):
Do we need to do competitive trade all competition?
Speaker 3 (49:42):
Yes?
Speaker 2 (49:43):
I think that should be our next live event. All right,
shall we leave it there, Let's leave it there. This
has been another episode of the ad Thoughts podcast. I'm
Tracy Alloway. You can follow me on Twitter at Tracy
Alloway and.
Speaker 1 (49:54):
I'm Joe Wisenthal. You can follow me on Twitter at
the Stalwart. Follow our guest Ricardo Houseman on Twitter. He's
at Ricardo Underscore Houseman. Follow our producers Carman Rodriguez at
Carmen Arman 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 dot
(50:15):
com slash odd Lots, where we have transcripts, a blog
in a newsletter, and we have a trade all room
in the discord where you Discord dot gg slash odd
Lots listeners are in their twenty four to seven talk
about all these topics, and there is a room where
everyone posts how they did on the Trader that day.
So a play the Trade oll and b post your scores.
Speaker 2 (50:37):
And if you enjoy all thoughts, please leave us a
positive review on your favorite podcast platform. Thanks for listening,
Hosts And Creators
Joe Weisenthal
Tracy Alloway
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