Latest / The Capitalism and Freedom in the Twenty-First Century Podcast / Matteo Maggiori on China, Geoeconomics and Exchange Rates | Hoover Institution

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Matteo Maggiori on China, Geoeconomics and Exchange Rates | Hoover Institution · The Capitalism and Freedom in the Twenty-First Century Podcast

0:09
- This is The Capitalism and Freedom
0:10
in the 21st Century podcast, an official podcast
0:13
of the Hoover Institution Economic Policy Working group
0:15
where we talk about economics, markets and public policy.
0:17
I'm Jon Hartley, your host Today.
0:19
My guest is Matteo Maggiori,
0:21
who is the mug Hotham family professor
0:22
of finance at the Stanford Graduate School
0:24
of Business is a senior fellow at the Hoer Institution.
0:27
Thanks for joining us, Mateo.
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- Thank you for having me and
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join us. It's great to be here. Well,
0:31
- It's really an honor to have you on.
0:32
I think you're one of the leading international economists
0:35
in the world and really excited to talk to you
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and we've known each other a long time
0:40
and I, I think the work that you're doing is,
0:43
is really fascinating on
0:45
all the big issues in international finance.
0:48
You know, talking about international hegemons, you know,
0:52
it's, you know, the rise of China exchange rates.
0:56
So many topics, you know, capital flows that I think are
0:59
so interesting to people that are
1:02
global macro practitioners on Wall Street
1:04
or are economists in academia.
1:06
I wanna first talk about your personal origins.
1:09
I mean, how do you originally get interested in economics?
1:11
Growing up in Italy, working at JP Morgan
1:13
and London, going to do a PhD at Berkeley.
1:16
And tell us about your personal origins
1:18
and how you got into international finance and economics.
1:22
- Oh, my, that's a, that's a long story,
1:24
but I, I guess I'll try to give you the, the quick version
1:28
in part of my interest, which is common, for example,
1:32
with economists also from Latin America was the big
1:35
crisis of the nineties.
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So Italy underwent several economic crisis that had to do
1:41
with the exchange rate system when I was growing up.
1:45
And that seems such a huge topic.
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It affected everybody's life.
1:48
It was clearly like on TV a lot.
1:50
It was something that people will discuss at dinner.
1:53
And I sort of felt, well, this is interesting.
1:55
It seems like a big deal and potentially quite interesting.
1:58
And my grandfather was not an economist,
2:00
was very interested in financial issues
2:03
and sort of stuck there explaining to me the basics.
2:05
And that sort of stuck with me.
2:07
But I didn't know that you could actually do the job of,
2:11
you know, a researcher, this,
2:12
you could make a living doing this.
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So I went to college, I did study economics,
2:16
but I interpreted, you know, a re you know, career research
2:20
to be totally out of the question.
2:22
I thought the professors were people that would teach
2:24
and then would have a private sector job
2:26
or some, you know, one of the liberal professions.
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So it was not really, you know, it was really,
2:32
I was graduating and an economist called Lucia Sarno came
2:36
to visit and told me which
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- Schools is that?
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- Yeah, I was at Morris, an undergrad university in Rome.
2:45
And it's a good university,
2:46
but it, you know, at least back at the,
2:49
at the time was much more teaching focused.
2:52
Today they're doing a lot more
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and they have a lot more research.
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But, you know, I didn't come from a family background where
2:58
research and being a university professor was something
3:01
that people could explain to me. And
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- Did you grow up in Rome or, or?
3:05
- I grew up in Rome, so I was born and I grew up in Rome.
3:08
I then went to do an exchange in London
3:12
through the Erasmus program,
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but I really didn't think
3:16
that I was gonna put through this career.
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I thought I, you know, best case I was gonna be a banker at
3:20
JP Morgan or, or something like that.
3:22
And then Lucio was now a, a close friend,
3:26
he's a professor at Cambridge University in the uk.
3:29
He came to give a seminar
3:30
and we met, they told him
3:33
that I had finished all my exams very fast
3:35
and that I didn't know what to do.
3:38
And he explained to me that you could actually put career,
3:41
like the one that I ended up doing,
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which was a big change for me.
3:45
So I ended up doing a master with him, actually in the uk.
3:51
And then, because UK masters are only one year,
3:55
you really cannot get the lectures for PhD
3:58
by the time you want to apply in the
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fall 'cause you just started.
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And so I ended up doing a year at JP Morgan.
4:06
Well eventually ended up being two,
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but at the beginning I thought it was gonna be just one year
4:11
trading currents and interest rates.
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But by that time I was pretty sure I wanted
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to go and do a doctorate.
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But I was sort of waiting
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and it was such an interesting experience actually exposed.
4:22
It was wonderful. But at the time I didn't know.
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And that's when I decided to apply to grad school.
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And then I came to the, to the US I came to Berkeley
4:31
'cause it was very strong in international.
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Marty Al was there, purely was there, Barry was there.
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It was just like a, an incredible,
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well actually rich Lions at the time was also, you know,
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more involved in research and it became a university
4:45
administrator and it's another chancellor, the university.
4:49
It, it was just a good environment to do international.
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But I'm one of those people that stumbled onto this career.
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I think the conditional probability being born in Rome
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and from the background I was coming from
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that I was gonna be a professor at Stanford,
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was pretty close to zero.
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- That's fascinating. I mean, I guess growing up in Europe,
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you know, this is still, I guess prior to the,
5:12
the formation of the Euro.
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I mean, was it things like the European exchange rate
5:16
mechanism and, and the sort of early stages of the Euro that
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that was, I mean, part of your interest in
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- Yeah, the ERM crisis of the nineties, what a big deal
5:25
for me, you know,
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those were happened when I was clearly very young.
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I didn't quite understand what was going on,
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but it was such a huge economic event that
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that's when I just first got sort
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of interested in these issues.
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Then of course, for a while I wanted
5:38
to be a marine biologist or something else, like all kids.
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But eventually when you came close to university,
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I would say that that experience
5:47
of those crisis was probably a big driver of my decision
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to get into economics.
5:52
- That's fascinating. You had the whole Soros
5:55
and sen I guess who, who played a role in
5:56
- Yeah, - In the bank, bank of England.
5:58
It's, it's fascinating I guess how influential that, that
6:01
that moment has, has been.
6:04
You know, you've had an amazing career, you know, at,
6:07
at Harvard and, and now Stanford
6:09
and really wanna talk to you about a lot of your research
6:11
because I think people, people really, you know,
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anyone who's interested in international affairs or,
6:16
or international economics, I think
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is very much interested in these issues.
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And, and I wanna just start
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by talking a little bit about China.
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I mean, it's one international topic that's attracted a lot
6:27
of interest in recent decades with rise of its economy,
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you know, since the Deng champing era, you know,
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liberalizing in its economy, you know, growing into,
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you know, being a potential hegemon, competing, competing
6:39
with the us It's, it's growing mil,
6:42
military might and so forth.
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You've written a, a really great paper on China.
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It's title internationalizing like China.
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I mean, could you explain, you know,
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what we've really learned in the data about
6:52
how far along China's come in your mind in terms of
6:55
achieving or or seeking to achieve hegemon status?
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I remember when I was working at Goldman, it was a big deal
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that China was increasingly entering big benchmark indices,
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whether they're equity or bond indices.
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I'm just curious what one, like what are the facts as
7:11
as they're evolving and, you know, could a multipolar world,
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you know, led by the US and China work if it were
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to come into existence and,
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and what might that look like if,
7:21
if it, if it were to happen?
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- Yeah, I mean these are fantastic questions.
7:27
We first got interested in
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China opening up the capital markets
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'cause we were seeing more
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and more foreign mutual funds holding domestic assets,
7:38
domestic bonds in China.
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And right now the situation is very peculiar.
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I would say we have this gigantic bond market
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domestically in China.
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It's, you know, depending on
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how you count the capitalization, it's, you know,
7:53
the second, the third largest bond market in the world that
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for many years was totally shut off from
8:00
international capital markets.
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It was actually surprisingly difficult if you were a foreign
8:04
investors to hold these bonds on shore.
8:08
Over time, China has gradually opened up this market.
8:12
So the paper that you references with Justice Schrager
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and Chris Clayton was an attempt
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to think about this opening up process.
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They clearly started originally with programs
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that were almost bespoke.
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You have to apply, you had to be a qualified investors.
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There was a holding period, you know, you, you would think
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of it as almost testing the waters for China,
8:37
getting familiar with
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what a foreign investor participating in their domestic
8:42
market would look like.
8:43
And then it progressively opened up more and more.
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So the big watershed moment was in 2017,
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they instituted a program called the Bond Connect
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that allows foreign investors through Hong Kong
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to enter the domestic market of China, the bond market,
9:01
hold their assets and get out potentially quite quickly.
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And this was a much faster application process,
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much lighter requirements
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and correspondingly so a big sort of
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inflow coming from foreign private investors,
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the investors that we normally associate
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as being a little flight here,
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like the mutual funds or a hedge fund.
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Not the very long term passive investors
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or the official creditors like, you know,
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foreign central banks, foreign sovereign wealth funds.
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So we started thinking about this process
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and we also wanted a model
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to think about if you are a new entrant like China,
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you might have many of the characteristics
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that are associated with a potential reserve
9:47
currency down the line.
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You're a large country, you have a deep market,
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you have a lot of fiscal capacity,
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you have military powerful, many of the things
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that we normally associate
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with a possible contender China has.
10:00
But currently you have a very low reputation.
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You're a, you know, you're a new borrower on the block,
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nobody knows how you're gonna behave.
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Everybody might be worried that if too much capital comes in
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and the next crisis you might lock the gates for example.
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You might not let them get the capital out.
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And so we started thinking about
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how you would slowly build the reputation towards competing
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with the US And it's really like a trial by fire.
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You sort of start with, you let in very, very few investors,
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a crisis will eventually happen.
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They will get scared about you.
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They'll try to pull out, if you don't do anything,
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if you don't impair the process
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and suffer through a crisis when eventually passes,
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they would've learned that, you know,
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you might be the good type
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and they will bring in more capital
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and you sort of keep going.
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But one of the things that this process shows you is
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most countries give up somewhere along the way you have
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to suffer through a lot of crisis to build up the reputation
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for being a country like the us.
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And most countries can take that pain
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and give up somewhere along the way
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and get stuck with a relatively bad reputation.
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And then we started thinking about other issues,
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which I'm happy to touch on, which are, you know,
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why would China want to do this in particular, what does it,
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you know, does he impact the current account?
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And I really ended up thinking of it as they're trying
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to generate two way flows.
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They're trying to have the foreigners potentially come into
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their domestic market,
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but they don't necessarily want to move the trade balance
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or the current account.
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So what do you do? You let some
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of the locals take capital abroad so the net doesn't have
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to change, at least not mechanically.
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And you sort of, you're building up gross flows.
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And I think it, it's probably for two motives.
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One is what we just described.
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You're trying to slowly build a reputation on global markets
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as a potentially investible asset
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and eventually as a very safe one.
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The other one, which is probably a more immediate concern is
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if you wanted to generate a financial infrastructure
12:02
that is separate from the one that the US
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or the west controls, you need liquidity, you know,
12:08
not all payments net immediately.
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Not everything has a counterparty.
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So you need a liquid store of value.
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And the domestic bond market of China is really the only one
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with a size big enough to do it.
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But to do that you need to progressively relax the
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capital controls.
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And I think that that's probably a big motive in their
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mind right now.
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Particularly given all of the financial sanctions.
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- So have they largely
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just been focusing on I guess stocks and bonds?
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Like I, I remember, you know,
12:40
the China a share h share difference.
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I mean, you know, they, they've historically,
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I mean Hong Kong at some level has sort of been this
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intermediary to attract capital into mainland China
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and you know, they, they'll have eight shares in in
12:53
Hong Kong and, and
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or they'll list some, some Chinese companies there.
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But I'm, I'm curious like on the real estate side,
13:02
my my sense is that things are,
13:04
are still pretty closed in the sense that I,
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I couldn't buy a house in China, for example, if I wanted
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to a meal in China, could, could I own a house there?
13:10
- Yes, there are, you know,
13:12
across asset classes from real estate to FDI to bonds
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and equities, the restriction, the restrictions differ.
13:20
Part of the recently liberalization was really the bond
13:22
market very, very recently.
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There has been also more attempts to even liberalize the use
13:28
of derivatives, particularly with the swap connect
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in some sense it comes hand in end with the bond market
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because it's the derivatives over those instruments.
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We're still at the beginning of this, you know,
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it's still a difficult country to invest in.
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There are liquidity issues, there are credit risk issues,
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but you know, it's unusual to have a country with markets of
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that size that starts to open up.
13:54
So I almost think of it as the reverse
13:56
of the bernanki saving glass story.
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The bernanki saving glass story, the early 2000 was, look,
14:01
China's opening up.
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It's really a, an amount of savings
14:05
that are entering the global asset classes
14:07
and are chasing, for example, US treasuries
14:10
and are pushing down yields,
14:12
what we might see over the next few years.
14:15
It's sort of a reverse shock where China's opening up
14:19
and it's creating a set of investible assets
14:22
that is expanding a lot for, for global savings
14:25
where you could potentially invest in
14:27
and it, it'd be interesting to see if China manages
14:30
to do this successfully,
14:31
are these bonds gonna crowd out emerging
14:34
markets like Brazil?
14:36
Are they gonna crowd out the weaker, you know,
14:38
develop sovereigns like Italy
14:40
or are they really gonna show up as competing
14:44
with super high
14:45
and sort of very safe bonds in the us Probably
14:49
that's gonna change through time.
14:50
That's gonna have large effects on yields.
14:53
So far that hasn't happened in, you know,
14:55
in particular the geopolitical tensions have meant that
15:00
western investors like US Europe
15:03
have largely not reentered China after pulling out in 2022.
15:08
- That, that's fascinating.
15:10
I mean it, it's interesting how, I guess how much
15:15
it feels like a reversion that we've seen under Xi Jinping
15:18
in, in terms of, I guess not being completely on the
15:23
sort of liberalization train that past
15:26
Chinese leaders ha have been.
15:28
But you know, at, at some level what's kind of, I think a,
15:31
a bit of a, a wanting to have a cake
15:33
and eat to two kind of issue of, you know, obviously wanting
15:36
to have all the economic benefits of, you know,
15:38
free capital flows and, and international investors,
15:40
but also wanting to have,
15:41
have very strong state control at the same time.
15:44
I think it's, it's can be a bit difficult.
15:46
I think that sort of segues into this ne next sort of topic
15:49
of geoeconomics and you've recently sort of pioneered this,
15:52
this topic and and concept in area of study geoeconomics.
15:57
Can you explain to us a little bit about
15:58
what Geoeconomics is exactly
16:01
and what your approach to thinking about it is?
16:04
- Yeah, so I would define it simply as
16:07
big countries like China, the US
16:10
that are hegemons using the existing trade
16:13
and finance relationships from their economies
16:16
to achieve political or economic goals abroad.
16:19
So lemme give you some very quick example.
16:21
One is I'm the US I'm trying to get European banks not
16:26
to finance trade with Iran for a geopolitical reason.
16:30
And one of the things I can threaten them
16:32
with is losing access to the US banking system.
16:36
If they don't comply, that's a very powerful threat.
16:38
If you're a European bank, that's a death sentence.
16:41
If you get shut off from doing business
16:43
with the US financial system,
16:45
and so you're very likely to comply.
16:47
Or if you're China, you could think of a lot of the belt
16:50
and road initiative as I'm providing you infrastructure,
16:54
I'm providing you loans,
16:56
but I'm also asking in return for you
16:58
to give a financial treatment to some of my exporters,
17:01
I might want to control one of the,
17:03
your key infrastructures like a port
17:05
or I might ask you to have a particular, you know,
17:08
leaning in un votes.
17:10
Those are all typical examples of this kind
17:13
of economic statecraft.
17:15
And it's something that economists were keenly aware of
17:18
and working on in the 1950s.
17:21
Then we dropped a little bit of bull on this.
17:23
The political scientists have actually kept thinking
17:26
about this very hard.
17:27
And so geoeconomics has a long history.
17:31
I think what we've been doing is trying
17:33
to bring modern economics into it,
17:36
just thinking hard about, you know, clarity.
17:39
Like from a theoretical perspective, when do you have power?
17:43
Why do you have power? How do you use optimal policy?
17:47
But also once you make it precise, you can go
17:49
and measure things and you can do policy counterfactuals.
17:53
So I, you know, our argument has been that a lot
17:56
of macro international
17:58
and finance theory that it was developed in the last 30
18:00
years has very good things to say about these topics.
18:04
We just haven't really focused
18:05
and so we're trying to bring it to bear.
18:07
And it has been, it's been great actually.
18:09
It's been exciting.
18:11
- And, and I think at some level too,
18:12
I mean just the whole topic or or
18:14
or tool of sanctions seems to grown a lot.
18:19
I, I feel like maybe 20 years ago there's, you know,
18:21
be Iran sanctions that would kind of go back and forth.
18:25
But even recently,
18:26
I remember maybe in 20 17 18 when I was working at Goldman
18:31
Sachs, I remember
18:33
that Venezuelan bonds were being sanctioned
18:36
by OFAC at the time, which is the treasury office
18:39
of Foreign Asset Control.
18:41
And so, you know, that had had a huge effect on
18:44
Venezuelan bond prices.
18:46
And, and now there's, you know,
18:48
we often hear about sanctioned individuals.
18:50
I mean there's all sorts of, and
18:53
and of course places like China and
18:55
and Russia counter sanctions on, on American individuals or,
18:58
or people are banned from entering those countries.
19:00
And so it's, it does feel like with the sort of rise
19:04
of China or, and,
19:05
and also with, with what's been happening with Russia,
19:09
particularly since the Ukraine in invasion,
19:13
that there, there's been, i I guess a lot more discussion
19:16
of these sorts of things, you know, what should the US or,
19:18
or the allies do with the, that the frozen
19:22
Russian reserve assets and so forth.
19:24
So it seems like you, you've, your timing couldn't be better
19:28
in in, in this, I mean, what, I guess what would be the,
19:31
explain, I guess maybe how, how does that work?
19:34
Is this largely like a, I guess theoretical frameworks?
19:37
How would you, I guess maybe empirically think about
19:41
certain sets of geoeconomics, I feel like the,
19:43
the toolbox is so broad in the sense that, you know,
19:45
you've got individuals, you've got financial assets,
19:48
you've got, you know, countries that you can just sort of,
19:50
I guess ban flows of some form of assets into, or,
19:54
or ban, you know, a certain country from accessing banks.
19:59
What do you think about the various variety
20:01
of geo-economic tools in, in, in the work
20:04
that you've been doing in this subject?
20:06
- Yeah, so I mean, lemme give you an answer in three part
20:08
first, you know, touching
20:10
to your earlier argument is you're totally correct.
20:12
There has been a resurgence of the use of these instruments
20:16
probably, you know, particularly in the last few years
20:18
of which really, I mean the recent past, the last three
20:21
or four years, this is the biggest change we've seen
20:24
to the world order, certainly in our lifetime
20:27
and probably since the Cold War.
20:29
So this is a, a pretty drastic change, you know,
20:33
shown up in sanctions, in export controls,
20:36
it's certainly shown up in the number of threats,
20:39
the use of tariffs.
20:40
It's really a big change.
20:43
The, the second part is you are also correct that the,
20:48
you know, the canvas
20:49
and the set of tools that has been used is quite varied.
20:52
So a lot of what our theoretical work has been doing is
20:57
trying to put this in all in one framework
21:00
where you're really thinking about threats
21:03
that could be threats not to buy, for example, like a,
21:06
a tariff or an, or a boycott.
21:09
They could be threats not to sell like an export control.
21:13
They could be financial aid,
21:16
they could be enforcement tools.
21:19
It's actually quite possible to take
21:22
all these different tools and bring them together
21:25
and figure out how they enter like an economic model
21:29
that generally I would say enter
21:31
through a participation constraint.
21:33
Now I'm trying to get you to do something
21:35
that you don't wanna do and either I'm moving your
21:37
inside option, so I'm trying to make the world better
21:40
for you and asking you something in return,
21:43
or I'm trying to worse your outside option.
21:46
I'm telling you that I'll make your life very difficult
21:49
if you don't comply.
21:50
And you know, a lot of our standard toolkit
21:54
fits into this.
21:56
Now to make it concrete, it's probably easier
21:59
to follow at least one example.
22:00
So let's suppose that we focus on the threat not
22:04
to give you access to something like an input.
22:07
Okay? And we can make it semiconductors
22:09
or we can make it financial services.
22:13
So it's something that you need that is part
22:15
of your production function.
22:17
It's how you sustain economic activity in your country.
22:20
And I would like you to do something
22:22
that you don't wanna do.
22:24
So my threat is gonna be that if you don't comply
22:26
with my ask, I'm gonna cut you off from these inputs.
22:30
Well, the first thing that becomes pretty clear is I can try
22:34
to compute how bad is this for you at the end of the day,
22:38
whether you're not gonna comply
22:39
or not depends on the distance between the
22:42
inside and the outside option.
22:44
If I ask you for the moon over something
22:47
that doesn't cost you anything to lose access to,
22:49
clearly you're not going to comply.
22:51
So a very simple concept of power, which we call micropower,
22:54
it's just trying to measure this gaps.
22:56
Now if you think about it as an economist,
22:58
then it becomes clear that what matters is,
23:01
well can you get this from somewhere else?
23:04
So that's a elastic substitution versus other varieties
23:07
that are produced by other countries.
23:10
The typical example I give is oil.
23:13
If under producer of one variety of oil,
23:16
I have no power If I cut you off,
23:18
other varieties are sub sufficiently closed substitutes.
23:22
Now if I, if I'm OPEC
23:23
and I control at least in the seventies potentially all
23:27
of the varieties, then I might have a lot of power
23:30
because the next thing that matters is, okay,
23:32
if you cannot get it, how important is this
23:35
for your production function?
23:37
Does he enter as a substitute for many other things
23:40
or is it close to like a Leon F input, something
23:43
that without it a lot of production collapse.
23:47
The other things that you start thinking about is,
23:49
do you have a domestic alternative?
23:50
Maybe you cannot get it anywhere else in the world,
23:53
but you can get it in your own country.
23:54
In fact, normally the first port
23:57
of call when you get cut off is your own domestic economy
24:00
can, do you have it or can you easily produce it?
24:04
You know, a typical example is semiconductors in China right
24:07
now, if we tell them that they cannot have access
24:09
to advanced semiconductors, they're clearly gonna try
24:12
to produce them domestically.
24:13
And the question is how quickly
24:15
and how efficiently can you produce them?
24:17
So if you take this very, very basic framework, one thing
24:21
that you can do is you can use
24:23
sufficient statistics approach.
24:25
You can say, look with us
24:26
with a model, I'm gonna figure it out.
24:28
If in a large class of these questions, all I need
24:32
to figure it out is expenditure shares
24:34
and elastic substitutions.
24:36
And then the model might tell me which
24:39
of these things are essential to you or not.
24:42
It's something that, you know, trade economists have done
24:44
for a lifetime, but you can bring it
24:47
to both of these questions.
24:48
So that's one approach.
24:50
And you can see that you're going from a theory
24:54
to measurement
24:55
and to counterfactuals where you're thinking about a world
24:58
where I might cut you off,
25:00
but we're measuring it from data
25:02
that we see on the equilibrium path recently.
25:06
So we've been experimenting a lot with that recently.
25:08
We're taking also a different approach, which is closer to
25:11
what our colleague Nick Bloom, for example, has done
25:14
for years thinking about text from the firms,
25:18
the firms themself might be talking about it.
25:21
What are they doing in response, how expensive is this?
25:24
And so we've been experimenting
25:25
with artificial intelligence, which is really the,
25:29
the way I think about it is there's nothing else that
25:32
a technology that lets us extract
25:34
so much more information out of the text compared
25:37
to a simple common find
25:39
or you know, if you're more sophisticated like a gram.
25:42
And that has been fun. We've been sort
25:44
of looking at all the firms around the world
25:46
and how they're responding to these issues.
25:50
- That's fascinating.
25:51
And I, I, I guess just to get into, you know, the,
25:56
these big data projects you, you've been working on,
26:00
you know, what's called the Global Capital Allocation
26:02
Project that you run with your co-authors for,
26:06
for a good number of years now.
26:07
And my understanding of it,
26:09
and correct me if I'm wrong, you know,
26:10
you're collecting all this fantastic data on capital flows,
26:15
and I'm just curious, you know, what are the, you know, some
26:20
of the challenges, what are some of the challenges been
26:22
with international economic data
26:24
that's usually compiled from the IMF, the BIS,
26:27
the World Bank and so forth?
26:28
And what's been missing in this data
26:31
on things like capital flows?
26:32
I know that with things like tax havens, you know, there's,
26:35
there's some issues and,
26:36
and sometimes, you know, there, there's just some challenges
26:39
with, with actually getting, getting good data or,
26:42
but sometimes these sort
26:44
of big international institutions kind of fall short.
26:46
I, I'm curious what, what's the,
26:49
how does the Global Capital allocation project fit into that
26:51
and, and what w do we not know,
26:53
or what are the things that those big multinational
26:56
institutions, what are the data that's, or,
26:58
or pieces of data that they're not tracking?
27:00
- This is a great question. So we, you know,
27:01
we started the lab back in 2017.
27:06
It was myself, Jesse Schrager and Brian Niman.
27:10
And the, we had really two interests.
27:13
The first one was micro data, and immediately
27:18
after the financial crisis,
27:19
and then with the sovereign debt crisis in Europe,
27:22
it became very clear that who owned which asset
27:25
around the world was an important macro question,
27:28
not just a micro question, you know,
27:30
and like when I went to grad school,
27:32
at least when I started, which was, you know, the year
27:34
of the financial crisis, there was this attitude
27:37
of the Central bank moves the interest rate,
27:39
financial markets do some no arbitrage stuff,
27:42
we don't really have to care about the plumbing.
27:45
And then a IG happened
27:47
and we kind of realized that knowing who is exposed to what
27:51
or lemon made a huge difference to macro.
27:55
And of course, you know, people like Bernanki it talking
27:58
more and company, those models were there,
28:01
but they weren't really as core to the inter, you know,
28:04
to the macro finance profession as we think of them now.
28:09
And, and they were still very aggregate, particularly
28:13
with the sovereign debt crisis in Europe,
28:16
it became very obvious that you wanna know
28:18
who holds those bonds, where are the losses gonna show up?
28:22
Are the losses gonna be absorbed by the investors
28:25
or they're gonna get massively amplified
28:27
'cause it's gonna cause a, a cascade of failures.
28:31
So the response to this was both in the private sector,
28:35
in academia
28:37
and in the policy institutions,
28:39
a massive effort to collect data.
28:42
All of a sudden we wanted to know positions.
28:45
You know, even in finance traditionally we focused on
28:50
prices on returns.
28:52
We didn't spend much time thinking about positions
28:57
that data was becoming available.
28:58
And so at the time we decided with just
29:01
and Brent, that we wanted to jump in on this
29:04
and we got a little lucky, you know, a lot
29:05
of research is you try your best,
29:07
but you also need to get lucky.
29:09
Our luck was that one of the largest data sets of micro data
29:13
around the world had become available commercially.
29:16
This was the data from Morningstar.
29:18
We had convinced them to give us their entire data.
29:21
And that was a treasure trove of,
29:24
because all of a sudden, you know, you could go very,
29:27
very deep on questions that traditionally only
29:30
with the aggregate statistics you couldn't really answer.
29:34
And so for example, we, we worked a lot on home currency
29:37
bias, which it's pretty obvious once you have the micro
29:40
data, but without the micro data,
29:41
it was very difficult to see.
29:44
That eventually led us to think about, okay,
29:47
once you can manipulate the data
29:49
and see what's going on,
29:51
what's the right lens to look at the data?
29:53
One thing that appeared very obvious to us is that a lot
29:57
of positions were in tax sevens.
30:00
Like you look at the Cayman Islands,
30:02
the British Virgin Islands, Luxembourg, so much
30:06
of the world financial assets, either on the investor side
30:09
or on the issue side, are in these countries.
30:13
Now, every economist understood
30:15
that there's no economic activity,
30:17
there's very little economic activity going on in the Cayman
30:19
Islands compared to the assets and liability.
30:21
So the capital is going somewhere else.
30:23
But you know, when I did my dissertation,
30:27
you kind of had to live with this.
30:29
You sort of could decide whether to drop it, dumb it,
30:32
do something about it, but you couldn't unwind it.
30:35
And then it became more obvious to us
30:37
that you can unwind it.
30:40
And that led to a lot of research or a,
30:43
or a pipeline for us thinking about
30:46
how do you get the facts straight
30:49
when you have all these layers of, of obfuscation.
30:52
And that has also led to a lot of collaboration
30:55
with the policy institutions.
30:57
So you, you know, the BIS, the IMF, the Fed,
31:01
the ECB, they have people
31:03
that do fantastic work on these issues.
31:06
And there's been a collective effort to produce data
31:10
that is much more representative of
31:11
what an economist will want to look at compared to
31:16
a simpler statistical approach.
31:17
So we now, we have a long-term collaboration with the ECB,
31:21
where we look at like Luxembourg in Ireland,
31:23
they're like massive mutual fund centers.
31:26
They show up as the biggest holders
31:28
of pretty much most assets worldwide.
31:31
It's very clear it's not on behalf of the residents,
31:34
but where do you stick this data?
31:36
Like is it Italians, is it Germans?
31:38
Is it the rest of the world? So that has been a lot of fun.
31:42
I would say that, you know, traditionally the lab,
31:44
our first wave of research was all on financial positions.
31:48
Now we're working a lot more with text, which I mentioned.
31:51
One frontier of research that is still out there to crack
31:56
is, you know, really good data on how firms trade
31:59
with each other around the world.
32:01
Like that data, and particularly in goods
32:03
and services, that data is very spotty.
32:07
There are some data sets here and there,
32:08
but if you think that, you know,
32:10
if tomorrow we get sanctions
32:11
and we want to know what is the exposure of every US firm
32:15
to foreign inputs, how does he aggregate that
32:18
that data doesn't exist?
32:19
We get glimpses in some data sets.
32:21
And so my sense is that with everything
32:23
that is going on in Geoeconomics,
32:25
that's gonna be one big sort of next frontier that needs
32:28
to be tackled.
32:30
- Yeah, I mean my sense just as,
32:32
as a researcher is like data on firms.
32:35
Yeah. Especially
32:36
with the us I mean internationally we have Orbis,
32:38
which terrific,
32:40
but you know, US data is, it can be challenging to work
32:44
with, you know, even just like the Dun
32:45
and Bradstreet data, you know, you might have some sort
32:49
of imputed number of employees or, or, or, or,
32:53
or establishments, but it, it, it's pretty limited.
32:56
We don't know too much about firms and,
32:58
and it's also hard to find, you know, their
33:01
information about their exposure to, to various,
33:04
- It's pretty difficult.
33:05
But you know, my sense is that it's gonna become doable
33:08
and a little bit like the financial positions
33:10
and now are very routine
33:13
and 10 years ago were different here.
33:15
You know, it's kind of amazing how over an article 10 years,
33:19
the profession collectively makes a lot of pro progress.
33:22
So I'm sort of somewhat hopeful that 10 years from now,
33:25
a lot of these issues will look like routine research.
33:29
- Well you've also done a lot of work on a lot
33:31
of great empirical work on, on beliefs and portfolios and,
33:36
and I think you've shed a lot
33:37
of really amazing light on, on, on investors.
33:41
And I, my understanding is I think you run a lot
33:44
of surveys partnering, I think with Vanguard
33:47
asking questions of Vanguard clients,
33:49
about their market expectations.
33:50
I mean, what, what did you learn from that line
33:52
of research when you,
33:53
you're actually going in asking questions
33:56
about retail investors
33:58
and you know, there there's a lot of, I think,
33:59
discussion recently about, you know, to what degree,
34:02
you know, flows and quantities matter.
34:04
This is a huge question I think in financial
34:06
economics right now.
34:08
Are, you know, equity markets in elastic
34:10
or elastic, you know,
34:12
if you had a $1 billion exogenous flow into equity markets,
34:16
would, what would the effect of that be?
34:18
And some like Quebec sequoian argue that's, it's a $5
34:22
effect, I'd argue it's it's much less than that and
34:26
and Mark's probably more elastic in in the long run
34:28
that then in elastic as they might claim.
34:31
But I'm, I'm curious, like, so so much of these sort
34:33
of behavioral things in venture markets are, are,
34:36
are driven by beliefs.
34:37
What have you learned from that line of research?
34:40
- Yeah, this was fun. This was with Stefan Olio, Johan Rabo
34:44
and Steve Ku, who at the time was a, was at Vanger
34:48
and the head of one of the research functions.
34:50
And it was really stimulated from this perspective.
34:55
So I guess two things got us into this.
34:57
The first was intellectually there was all this work on
35:01
expectations moving around a ton
35:04
and potentially leading people to trade a lot.
35:07
And therefore to explain the volatility of price is like one
35:10
of the most classic questions of, you know,
35:13
financial economics is why are prices so volatile compared
35:17
to the fundamentals.
35:19
The second thing that was interesting is
35:22
survey technology was changing.
35:25
Like it was clearly very possible
35:27
to run large scale survey surveys, get people
35:31
to answer on their phone, on their laptop.
35:34
You know, that was becoming more and more available
35:36
and by now it's totally routine.
35:39
And even when we did it, I mean I'm certainly,
35:41
we didn't pioneer this,
35:43
but it, it was sort of clear that we, it could be done
35:46
and sometimes you just have to again be a little lucky
35:49
and a little bit ambitious.
35:51
So we thought like, okay, the thing that is missing is
35:54
to see people like me
35:56
and you when we actually make our financial decisions in
35:59
real life and not in a lab experiment, how do we react
36:03
to our own reported beliefs
36:06
and can we get high quality data
36:08
that links actions in a setup that is in,
36:11
in some sense is the real world.
36:13
These people are making their decisions on the actual
36:15
savings to high quality survey data.
36:18
And you know, we just got lucky like Vanger was willing
36:21
to do it and there'd been a wonderful partner as,
36:23
as an institutions on this, you know, I would love to do it
36:26
with many more institutions
36:28
so far no other financial institutions said, great,
36:32
we'll let, we'll let you do it.
36:34
And so we ended up designing I would say a
36:38
medium scale survey.
36:39
Medium scale for me means the following.
36:41
It's not one that says, Hey Jonah,
36:43
you bullish about the market.
36:45
The problem with that one is it's very easy for you
36:48
to understand what I have in mind.
36:50
It's very difficult for me
36:51
as an economist when I get the answer
36:53
to translate it into something that will constrain a model.
36:56
So on the other hand, you can do very large scale surveys
37:00
where you have to be a professional economist
37:02
to even understand what it is that they're asking you.
37:04
So we spent a lot of time designing in a way that we felt
37:08
a relatively unsophisticated retail investor will understand
37:12
what, what you're asking and has a view on this.
37:15
And on the other end, the answers are quite informative for
37:18
how we design our models.
37:20
And the, the thing
37:21
that jumped out immediately was were really two facts.
37:25
The first one is that beliefs do move a lot.
37:28
People have all sorts of views,
37:31
but portfolios don't move that nearly that much.
37:34
So the sensitivity of portfolio locations to beliefs,
37:38
it's way low.
37:41
Now that's a little bit different and,
37:42
and not to be interpreted directly
37:45
as the elasticity you have in mind
37:47
because in some senses an elasticity to report the beliefs
37:50
that are not margin more volatile than, you know,
37:54
a rational expectation model would tell you would be the,
37:59
at, at least for a representative agent,
38:01
they expect the returns.
38:03
So that sensitivity was way too low.
38:04
Now that one, if you take it at face value,
38:07
it's not great news for the behavioral approach.
38:09
'cause it tells you the police could move a ton,
38:12
very little training occurs and
38:14
therefore the, you know, this is unlikely
38:16
to generate at least in a very naive model,
38:18
huge price for questions.
38:20
Now, there are ways to go around it, which is
38:22
to think about like different sizes of investors.
38:26
Maybe there's a small fringe of investors.
38:29
The the statements need a lot more to be complete.
38:32
But that fact was pretty, pretty surprising,
38:37
pretty interesting.
38:38
And as you know, has surfaced in different fashions
38:42
by now in, in lots of different studies.
38:44
The other thing that showed up is
38:47
how people changed their mind over time.
38:50
So when we started, we had the following question, is
38:54
that right view of the data that you
38:57
and I change our mind a lot over time?
39:00
Or is the right view of the data is
39:02
that you are always very optimistic.
39:04
I'm always very pessimistic. We both change our mind.
39:08
But the first third effect is just
39:10
how far are we in our beliefs to begin with
39:13
The world is really the second,
39:15
like these individual fixed effects absorb a tremendous
39:19
amount of the panel of beliefs.
39:21
So there's really optimist and pessimist.
39:23
It's a very persistent effect
39:26
and we never found it easy
39:27
to explain based on observable characteristics.
39:30
Why in the first place is John so optimistic
39:33
and Mateo so pessimistic.
39:35
That's still an open question,
39:37
but that has been a, you know, it has been a very fun,
39:39
somewhat unusual line of research for me.
39:42
'cause there's not any international,
39:44
but I thought it, I thought it was fascinating
39:45
and we, we keep working on this, we keep sort
39:48
of adding pieces of evidence over time
39:52
- That, that's fascinating.
39:53
I mean, I'm, I'm curious, like I I do follow like some
39:56
of the behavioral literature and,
39:59
and some of the, you know, both intersections with sort
40:01
of macro and finance and like,
40:03
I remember there's all these papers, you know,
40:05
by I think Ian and Sufi and,
40:07
and there's a whole literature out there that tries
40:09
to look at like con you know, consumer confidence
40:11
and how much does consumer confidence actually matter
40:14
for really economic variables.
40:16
And I'd say this is kind of maybe analogous to that.
40:18
And sometimes they look at like elections for example,
40:21
and this is almost like a, I feel like a universal law,
40:24
but basically following an election you can see, I mean,
40:28
around these periods, you know, if for example,
40:32
an incumbent gets thrown of office,
40:34
there's a massive shift in expectations or
40:38
or in consumer sound.
40:39
Basically people feel very good when their own, you know,
40:43
preferred candidates in office and,
40:46
and they, they generally have positive economic sentiment,
40:49
you know, for, for people that
40:50
belong to that political party.
40:51
Like for example, you know, maybe
40:54
after the most recent election, you know, you'd,
40:56
I'm sure you'd observe that, you know,
40:57
the consumer sentiment of Trump voters would be very high
41:00
probably right now versus, you know, democrats and, and so,
41:02
and, and these things flip
41:03
around elections like pretty mela mechanically and,
41:06
and using that for identification, I, I think some
41:09
of these studies like the Ian
41:10
and Sufi studies basically found like
41:11
no real economic effect.
41:13
So I, I think that kind of maybe speaks
41:15
to some of your findings.
41:17
I I'd be interested if, if you've ever looked at
41:19
how these sorts of beliefs change around elections
41:21
that maybe people sell their portfolios around.
41:23
- So we, we looked a little bit,
41:24
but part of the problem is it's not easy for us
41:28
to identify who's a Republican, who's a Democrat.
41:31
You know, one of the great things with working
41:34
with this type of data sets is I get to see all your wealth
41:37
and all of that, but precisely
41:38
because of that, there is a strong limit on not being able
41:42
to identify people.
41:44
So that's, you know, i I guess part part of what you get
41:48
and part of what you don't get.
41:50
But in general, I'm a huge fan of studies that are trying
41:52
to figure out how my beliefs
41:54
or my perceptions really translate into actions.
41:58
One thing that for example, was shocking to us is
42:01
during COVID
42:04
and then more recently during April 2nd, the announcements
42:07
of tariffs, we looked at changes in beliefs
42:11
and there were massive changes like, you know,
42:13
people became very pessimistic about the
42:15
economy, the stock market.
42:17
But when you look at their portfolios, it was shocking to me
42:21
how little they sold.
42:23
You know, you would think if people become so pessimistic,
42:26
you would find in the data massive attempt
42:28
to liquidate equity positions.
42:31
In reality that's actually pretty small.
42:34
And you know, I was speaking to my Xavier
42:37
and we haven't worked on this together,
42:39
but Xavier Gbe has worked on, on this with in another setup,
42:42
and it, it's sort of shocking how little it is now whether
42:47
that translates from big
42:49
or small asset price movements, that requires a whole sort
42:52
of different set of assumptions
42:53
and baggage that comes with it.
42:55
But just as a, as an economist compared to at least my,
42:58
my informed prior year, these flows are pretty small.
43:02
The question is are we mis measuring beliefs
43:05
or it is the problem, the way they're responding.
43:09
It's just interesting.
43:10
It's a mapping that I think is gonna take more time
43:13
for the profession to fully absorb,
43:16
but it it's certainly striking
43:20
how big our largest differences are.
43:23
- Yeah, it's fascinating.
43:24
I think behavioral macroeconomics
43:26
and behavioral macro finance, I mean, if, if you
43:29
call out a field, I mean it, it certainly is one finding,
43:32
you know, good answers to that.
43:33
I, I think is, it's such a diff difficult thing to do and,
43:37
and it's, you know, certainly huge gains if,
43:42
if, if people can make even I think marginal improvements in
43:45
our, in our understanding in, in that space that, you know,
43:48
that's commencing.
43:50
I I wanna just spend, I I guess last,
43:53
last moments here together talking about exchange rates
43:57
and you know, one core, it's really a core area
44:00
of international finance
44:02
and you published a, a length about exchange rates.
44:05
I'm curious, like, one,
44:07
tell us a bit about your own research on exchange rates,
44:09
but I I'm just curious in general, you know,
44:11
what in your mind have, have we learned about exchange rates
44:13
in the past maybe 20 to 30 years and,
44:16
and maybe it's, it's we've learned more,
44:18
I guess from getting better data.
44:20
I feel like we've had okay, exchange rate data in general.
44:23
Maybe we have more high frequency data now,
44:25
but we, we kind of had had these periods where, you know,
44:29
one, like I I think a lot of international economics is,
44:31
you know, born out of, you know, the Bretton Woods era,
44:35
I think, you know, Mundell Fleming, the Mundell Fleming tri
44:38
of, you know, the idea that you can only have two out of,
44:42
you know, fixed exchange rate, independent monetary policy
44:45
and free capital flows was an idea that was developed out
44:48
of the IMF when, when, when Fleming was working there.
44:52
And, and I think Mondell was, was maybe visiting,
44:56
but you know, obviously the world's moved away from the
44:58
Bretton Woods system in the seventies, you know,
45:01
closing the gold window
45:02
and the Brenton Woods system breaking up
45:06
Kane's obviously in the, I think fifties when he was helping
45:10
to create the IMF
45:12
and the World Bank, he was in favor
45:14
of having one international currency being the bankcorp.
45:18
And I feel like we've sort of gone all over the place
45:20
and you know, there's, in terms of
45:21
what we believe about exchange rates in the sixties,
45:25
mil Friedman went head to head
45:26
with MONDELL about should we have
45:28
fixed or flow exchange rates.
45:29
And Friedman I think kind of won out for a while,
45:32
but there's still many, many countries around the world,
45:34
even today that ha still have fixed exchange rates
45:37
that are pegged to the dollar or some cases to the Euro.
45:41
But I'm just curious what, you know,
45:42
there's all these exchange rate puzzles that are out there.
45:45
I'm curious, what do you think we've learned as,
45:48
as a discipline in the past few
45:50
decades about exchange rates?
45:52
- Well, I mean this is a huge question.
45:53
So you know, I'm gonna tell you a little bit of
45:58
what I've worked on or what I found fascinating also
46:00
because it's a good study next to, you know,
46:03
your very first question.
46:04
So it's a good wrap up of how I got into economics
46:08
because in, I mentioned I worked for a while
46:12
as a trade currencies in interest rates and at JPB Morgan,
46:16
and that was before my PhD.
46:18
And then what happened is I was on the job market,
46:21
I had a paper that was on international, was on the roll
46:24
of the dollar and you know, the US as a world banker
46:29
vie Beckon, Emanuel Fadi at the time I had a paper on
46:32
exchange rates and rare disasters
46:35
and I was in on the job market
46:37
and I ended up speaking to Xavier on a flyout.
46:41
And we were both pretty unsatisfied with
46:43
how exchange rate modeling worked even in our own papers.
46:47
And we sort of had in mind a different model
46:50
and we couldn't really, you know, that model,
46:53
we couldn't make it work.
46:54
And so we thought like, oh, why don't we
46:56
work together on this?
46:57
Which of course for me at the time was a great opportunity,
46:59
was already like an incredibly
47:01
established and talented economist.
47:02
It still is, but I was just a rookie on the job market
47:06
and I thought, okay, great, let's do it.
47:08
And I ended up thinking about this through the lenses of
47:11
what I had seen trading exchange rates,
47:14
which was a very simple idea of suppose that, you know,
47:17
today we wake up in the US
47:19
and there's a bunch of people that really want
47:21
to hold Brazilian AWA risk
47:24
and they're very excited about the prospects of Brazil.
47:27
They wanna buy those bonds, well, who's supply them.
47:30
It's not gonna be some long-term issue in Brazil,
47:33
probably it's gonna be, you know,
47:35
before a financial crisis, some bank like JP Morgan
47:38
or Goldman, now it's probably some mutual fund that is
47:42
the marginal intermediary, somebody that is willing
47:45
to take the other side of that trade.
47:47
And so it's giving up Brazilian real
47:50
and it's getting dollars and it's using their balance sheet.
47:53
I mean these, these institutions are big,
47:55
they have large balance sheets,
47:56
but you know, if you're trading a few billions,
47:58
you're kind of moving the risk.
47:59
And so they're thinking equilibrium,
48:01
do I make enough money outta this rate
48:04
to justify betting the risk?
48:05
And so we ended up designing a model
48:07
where the limited risk betting capacity
48:10
of these intermediaries in the middle, it's sort
48:12
of crucial if you're pushing dollar risk ment
48:16
and you're taking away real risk, the exchange rate has
48:19
to move to guarantee enough returns to these intermediaries
48:23
to hold the flows in particular,
48:25
that's gonna cause an immediate appreciation of the real, so
48:28
that over time you can depreciate
48:30
generating gains from them.
48:32
And so it's a model that linked of flows
48:34
and financial frictions
48:36
and intermediation to exchange rate determination.
48:39
And it's an idea that actually had been around
48:41
for a long time, like Penti Kuri was an economist in the
48:44
seventies talking about this,
48:46
but it was surprisingly difficult
48:48
to make it stick in a mother micro founded
48:52
general equilibrium model.
48:53
And so that's what we ended up designing with.
48:55
Xavier has been a very popular model ever since, has been,
49:00
you know, adopted a lot in academic research.
49:02
The IMF, when they revise their policy framework,
49:05
the financial market side of that exchange
49:07
with determination comes, builds on that paper.
49:11
So it that, you know, a fair amount of impact over the last,
49:14
I guess it's already been more than 10 years,
49:17
it's almost 15, but for me it was fun.
49:20
It was, it was a paper that sort
49:22
of translated an industry experience into an academic,
49:27
you know, framework that holds together.
49:32
And I, you know, I didn't go to the industry thinking that
49:36
that was gonna help me write those papers,
49:37
but that paper was a, was a pretty direct
49:41
descendant of that experience.
49:43
So that, that has been fun.
49:44
And you asked me what have we learned
49:46
and what we've not learned.
49:47
I, I think I would say that we've learned that these
49:51
market segmentation, it's pretty important
49:55
that these flows do matter there.
49:56
They do move exchange rates around,
49:58
it opens up a toolbox also for policy.
50:02
We still don't have a lot of imp empirical success.
50:07
I would say that there's plenty of evidence
50:09
of financial frictions being important
50:11
for exchange rate determination.
50:14
I wouldn't say it's overwhelming.
50:17
And I think that that's where there's excitement about
50:19
positions, data exchange rates are particularly tricky
50:23
because you would think that some
50:25
of the financial institutions that are most likely
50:28
to be marginal in these markets are those whose data is the
50:31
hardest to get, like hedge funds, you know,
50:34
very levered player.
50:36
These are probably pretty important
50:39
and it's pretty difficult to get a complete
50:41
picture of what they're doing.
50:42
But again, there's been an incredible amount
50:44
of progress on this.
50:47
- Yeah, it's a great question
50:48
and in some level, you know, I think it's
50:51
just very difficult questions in terms of what, you know,
50:54
what, what actually predicts exchange rates
50:57
in in the short to medium run.
50:59
I think it's, it's, it's very hard.
51:01
You know, I I think in the two thousands there were a lot of
51:05
both currency and commodity hedge funds out there
51:07
that now largely don't exist.
51:11
There's a lot of multi-strategy funds that trade various
51:15
currency strategies and I mean, FX carry being one,
51:18
one big strategy and there's been tons of work in academia
51:22
that's been done on covered interest rate parity
51:25
and arbitrage that's sort of broken apart.
51:27
I mean, it's one big area and,
51:28
and I I think maybe one theme in, in your work,
51:30
which I think is terrific and, and,
51:32
and in my sort of young research career here try to do some
51:37
of this, which is, you know, I I think there's so many,
51:40
there's, there's such a big chasm
51:42
between academia and and practice.
51:45
And I think if, you know, as researchers we knew everything
51:48
that practitioners knew,
51:50
we could write better research papers and,
51:52
and it's challenging in part
51:54
because, you know, there's a lot of data
51:55
that they can't share or don't wanna share,
51:57
and they also don't wanna give away their trade
51:59
secrets at some level.
52:01
But I think there's, there's still so much to
52:03
to be learned there, so it's fantastic to hear,
52:05
I read Quebec's imagery, I think it's a fantastic paper
52:08
and I hadn't quite realize how important it was
52:10
by your JP Morgan experience, so I think that's terrific.
52:12
I guess like one last sort of just question, I guess sort
52:15
of big think here is any thoughts on, I guess, you know,
52:19
just the future of the world you've written in, in sort
52:22
of these hegemons, you know,
52:23
you've written really the canonical papers with, on,
52:28
on the sort of topic of hegemons with E Emmanuel far
52:30
and, and, and others.
52:32
You, you wrote a great paper several years ago
52:34
that talked about the decline of the euro,
52:37
which something we're continuing to see.
52:39
I I think the US dollar has held up quite a
52:41
bit, held up pretty well.
52:43
I think even through you, the Russian invasion, Ukraine
52:48
through COVID through the recent early 2020s inflation,
52:51
the dollar I think is a share
52:53
of global reserve assets is pretty much still the same.
52:57
And, and I think this is the same across invoicing, a number
52:59
of things China I think hasn't made at least as a share
53:03
of FX reserves the same kind of,
53:06
I think progress that some people had hoped.
53:08
There's all this talk about Bricks Bank, you know,
53:11
d dollarization, which I think is not well founded in the
53:14
data, but, you know, so many of these things also are sort
53:17
of proactive and are new and,
53:19
and maybe it takes time for, for things to change.
53:22
But I'm just curious, I mean,
53:23
what your thoughts are about the trajectories of, of China,
53:27
of, of Europe, of, of the US and, and of elsewhere.
53:32
And I, I, I just, I think back to this one speech that I,
53:35
I once heard from Sam Druckenmiller, you know, he's been
53:38
around for a long time and investing, you know,
53:41
played a role in the breaking the Bank of England.
53:43
And he said at one point, you know,
53:44
everyone thought the USSR was gonna take over the
53:46
world, they were wrong.
53:48
Paul Samuelson wrote in a textbook, he thought that the GDP
53:51
of the USSR was gonna eclipse the US
53:52
and that was obviously wrong
53:53
and he updated his textbook at one point in the eighties.
53:57
People thought that Japan was gonna surpass the us that
53:59
that obviously was wrong.
54:01
It's been wrong since the nineties.
54:02
And and next is sort of the China question,
54:05
and I'm just curious, you, you study this,
54:08
you study all, all these areas.
54:09
I'm just curious if you sort of had any
54:10
sort of big think thoughts.
54:12
Obviously, you know, forecasting is always challenging,
54:15
but I'm just curious, what, what do you think in terms of
54:18
how these big hegemons are are shifting?
54:21
- Yeah, so I mean one thing is for sure, which connects to
54:24
what we discuss in, in reputation models is
54:27
that challengers come up,
54:29
but it's very, very difficult
54:31
to displace the us I mean ultimately the institutional
54:35
strength of sustaining large markets
54:38
with big foreign participations
54:40
where even in a crisis like oh eight,
54:43
you don't essentially try to put through policies
54:46
that intentionally reduce value for foreigners.
54:49
It's an incredible promise to maintain.
54:52
It takes a lot of institutional strength
54:54
and most countries want to make that promise exam
54:57
as you get good terms on your borrowing
54:59
and when the time comes can't fulfill it.
55:02
So it, it's not easy to build the reputation
55:05
and maintain reputation at these levels.
55:09
So I'm certainly skeptical of
55:13
each time there is some promising young entrant thinking
55:17
that it's gonna be so easy to displace the incumbent.
55:21
The on the other end it's very clear
55:24
that we're seeing a big deterioration in the us.
55:27
I mean the fiscal situation has changed dramatically.
55:31
You know, we're not quite in trouble,
55:32
but we're starting to approach that levels
55:34
where these issues are gonna come up.
55:36
If interest rates spike, the cost of service
55:39
and the debt is gonna go up
55:40
and you know, you also don't want
55:42
to go to the other extreme.
55:43
If you look through history, it's not as if,
55:47
if you once establish yourself to be a cornerstone
55:50
of markets, you will always be one.
55:52
In fact, you can be one for a very long time.
55:54
But history shows us that you can often put through policies
55:58
that lead to your own demise.
56:01
So I think the truth is somewhere in the middle,
56:04
but one aspect that I think I'm,
56:05
I'm focusing on these days is the difference
56:08
between the implications of our eyes of sort example
56:11
and alternative like China for market versus power balances.
56:16
Lemme put it this way, which is, you know,
56:18
a little simplistic, but makes the point.
56:21
You mentioned that China is somewhere around like two
56:24
or 3% of the international user currency depending on which
56:28
exact measure you use.
56:31
Now let's the us, which is like 50% in this I sixties,
56:34
60, 70%.
56:35
Now let's quickly agree to a scenario
56:38
where 10 years from now,
56:41
the US is still in the high fifties.
56:43
China's gone from three to let's say 7% to 10%. Okay?
56:49
I have no idea whether this is likely or not likely,
56:52
but we're not talking about neck to neck.
56:54
We're not talking, we're 50 50. Now.
56:58
What's the consequence of that?
57:00
Now, I would say for macro, relatively little,
57:04
I don't think it's gonna change the transmission
57:06
of monetary policy the way change rate works.
57:08
Tons of the usual stuff. Very, very little.
57:11
But now go back to the question of sanctions
57:14
or exerting power to the financial system for
57:17
that question is an absolute disaster.
57:20
Why? Because imagine functioning account the size of Brazil
57:24
or Russia, if China is 10% of the usage, that's plenty
57:29
of liquidity for them to conduct business with.
57:31
So in power is really about concentration of the shares
57:35
and coming down from having 95% of the shares
57:39
to 85 is a big loss in your power compared from 85
57:44
to 75 and so on.
57:45
So I think in, you know, I always invite people
57:48
to be careful about how we interpret those shares
57:52
because what they mean really depends on the question.
57:54
So if China, for example, develops a successful payment
57:58
and settlement system that is pretty liquid
58:01
and can easily accommodate a small open economy using it,
58:07
that's a big loss to Western power.
58:09
Does it make a huge difference
58:11
to many other questions in matter?
58:13
Probably not. So those are also much more realistic than a
58:16
world where in the next five years China has 50%
58:21
of the world financial system, which, you know, who knows,
58:25
but seems rather unlikely.
58:27
And I think it leads to a bit of a policy mistake
58:29
because if you're thinking that none
58:31
of those issues are gonna arise until we're really neck
58:34
to neck financially,
58:36
then you can com be very complacent about the development
58:40
that China financial is gonna look small
58:42
for a very long period of time.
58:43
But those small shares can make a very large difference,
58:46
particularly in Geoeconomics, even if not in market.
58:50
- I think it's just so hard, I think at some level
58:52
to dislodge a hegemon.
58:54
You, you think about, you know, the last time you, the,
58:58
the world hegemon, you know,
59:00
global Reserve currency changed.
59:03
You know, it took a couple world wars to basically dislodge
59:07
the UK from having the pound as you know,
59:09
the world reserve currency.
59:10
And in, in a world where we have, you know, nuclear weapons
59:14
and, and across many countries, you know,
59:17
war becomes increasingly less likely to happen.
59:21
- We might end up living in a world
59:22
where fragmentation really means on the hedges
59:27
and where the US is still very, very dominant,
59:30
but all, all of a sudden there are two oth, two
59:32
or three other players that can provide meaningful,
59:35
for example, financial services.
59:38
Now that world for power makes a big difference even if it
59:41
doesn't look at all like a complete reversal
59:44
of the current equilibrium.
59:47
- Fascinating. Yeah, absolutely.
59:48
Well, it's a, a real honor to have you on Mateo and,
59:51
and talking about your amazing career
59:52
and contributions to international finance.
59:54
- Fantastic. Well it was great to do it.
59:56
I'm glad that we got to do it.
59:57
- This is the Capitalism Freedom, the 21st Century podcast
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and official podcast of the Hoover Institution Economic
1:00:02
Policy Working Group where we talk about economics,
1:00:04
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I'm John, he your host. Thanks so much for joining us.