Hello, everybody. Today we have Brian Arthur
for our guest spot. Brian is one of the founders
of what is now called complexity economics, that is
viewing the economy as a complex adaptive system. Brian has
spent many years as a professor at Stanford, and then as a
faculty member -- research professor at the Santa Fe Institute.
We overlapped by several years in the early days.
And Brian was the very first director of the SFI Economics Program
He’s currently a visiting researcher at the Palo Alto
Research Center in California and he’s an external professor at the Santa Fe Institute.
Brian has written many papers and books
on economics and complexity. I’ve put a link to one of his
recent papers on complexity economics on the course materials page
so you can download it. Brian’s most recent book is called The Nature
of Technology -- What it is, and how it evolves.
So welcome, Brian. Thank you, I’m delighted to be here.
Brian -- why do you think the economy is
a complex adaptive system? Well,
I think it’s a very
old way, actually to look at the economy
In economics we tend to think of the various actors or agents
in the economy, the players in the economy, if you like,
as together creating some outcome
that they react to, so
could be investors in the stock market, they’re buying and selling a particular stock
and that creates how much is bought
and sold and how the price adjusts, and then they react
to that new prize. So I tend
to see complex systems as systems of multiple
elements creating some pattern or outcome
that those elements react to, and
economics is certainly very highly
interactive system of that sort. Also
it’s true that economics has seen itself that way for
a long, long time. When Adam Smith was writing
economics in the 1770s he pointed out that
what we would now call the agents in the economy, he mentioned
butcher and baker and candlestick maker
they’re all creating something that they’re reacting to
so at least 200
or 230 years ago, 240 years ago,
people were looking at the economy as a complex system.
A little bit after that, a hundred or so years after that, things changed.
How did they change? Well,
there was much more tendency after about
1870 the idea was to mathemetize the economy
and to make sure that we could analyze that with
equations and do that. Things got quite a bit
simplified. So economists in the
Victorian times in England anyway began
and in Switzerland, places like that, began to look at the economy
as more like a machine
something like a perfectly ordered
machine with all these interacting parts and all these
parts were working together to create something that was
consistent or in balance. So the emphasis
was on being in balance.
Everything was in a sort of stasis, a bit like
not that it was static and not going anywhere, but more like the surface
of a lake reaches a certain level, occasionally
there’s ripples and it comes back to that level again. So
for at least the last 100 or more years, 120 or 30 years
we’ve been looking at the economy
as an equilibrium, perfectly
designed or perfectly
equilibrated machine in equilibrium
with everything in balance, moving but everything very
finely balanced in some sort of perfection
Now we’re getting away from that again.
People are looking at the economy in a much more organic
sort of -- almost biological way. That’s right
We’re starting to see the economy again, I think the way
people did two or three -- two and a half hundred years ago.
We’re starting to see that
people -- that there are new opportunities coming along
all the time. It’s a bit like the biosphere, new species
arrive all the time, and that changes the outcome
so the difference actually between
how we look at the economy now and under
as a complex adaptive system versus equilibrium
economics, is a little bit like the difference in
possibly in biology. If you choose
to look at species, you know the number of
wolves and the number of spruce trees
and the number of sheep in the economy, you can see
maybe that they’re in some sort of overall equilibrium,
and have an equilibrium biology based on that. But if you look
over the long term, that’s not the way it works at all. You see new species
in fact, whole new orders of species coming in
all the way from primitive times, slime molds
building up into some primitive types
of plants and fish and so on, and
radiating into very different things, and then
we get dinosaurs and reptiles and mammals
bringing in different eras and so we’re starting to look at the economy
this way again, that there’s new things coming along
those are creating new structures, the players
in the economy are constantly reacting, and they're
themselves bringing -- those reactions bring along yet fresh
opportunities, so the economy is evolving as
behaving very much like an ecology. It’s interesting that
Darwin used ideas from economics to understand
biology, and now people are
going the opposite direction, right? It’s amazing, Darwin
was reading Malthus in I guess
the 1830s and
so was Wallace, by the way, they came up with
their theory of evolution
by reading economics, and now I think the
traffic’s in both directions very much. What we’re looking at
now is that players in the economy, the agents in the economy
people in firms and so on, are
exploring, always exploring new opportunities
and exploring new strategies, new ways to forecast
new ways to think, new types of actions, in
some sort of situation that is created by
all those actions and strategies
and forecasts, so we’re tending to think of people
trying out different strategies in an ecology that consists of
other strategies. The view of economics
is very ecological, and so we’re having conversations with
ecologists, people like Robert May
many, many others as well. And ecologists, I hope
are learning from economists as well, because
we’ve been looking at this sort of thing for a couple of hundred years
This point of view, what I want to emphasize is
that the point of view harks back 200 years
ago, viewing the economy as evolving, changing
always changing, always adapting
but we have a lot of new tools that we’re bringing on
and those are helping redefine the
economy as a complex adaptive system. That was actually my next
question, because you’ve coined this term complexity economics
which is now getting a lot of press and attention
and I was wondering -- maybe you’ve already answered this -- but
what characterizes complexity economics versus, you know,
economics? Versus standard economics?
Is it the tools of complex systems modeling, do you think?
No, I think it’s -- complexity economics
means taking the interactions in the economy seriously, and
we’re not seeing the economy as always static or as always in equilibrium
The economy is full of opportunities and
the players or the agents in the economy, be they banks or
firms or consumers are always adapting
and so
when you see people or players in
the economy always adapting to the situation they create
that may or may not settle down into an equilibrium,
so we’re beginning to see very much in many, many parts of the economy
finance, international trade, that
an equilibrium isn’t reached. It’s one thing leads to another.
I think it was Churchill, he was asked about history
and how would he define history, and he said, history?
History is one damned thing after another.
And in one sense the economy is like that, too.
We’re looking at the economy as being open, as creating
opportunities, the agents are always reacting to that
and in doing so they’re changing the situation again
If you want to look at everything that’s happening
as being in a balanced equilibrium, you get standard economics
and you can do a lot of analysis that way
It’s a simplification, and it has served its purpose
very well for about a hundred years, but if you want to
generalize and say it’s always open and changing
other things adapt in that particular part of the economy you’re looking at
then you’ve complexity economics. It generalizes standard economics.
And the reason we can do that now, by the way, is because
we have stochastic nonlinear
stochastic process theory, i.e.
fancy probability theory, we have nonlinear
dynamics, and we’ve computation. We can do a lot
by closely specifying these
problems with models and then
looking at those models in the way you’d look at a lab experiment.
Creating a model where there is
some sort of interaction that may not necessarily lead to an
equilibrium and then watching carefully what happens
and the interesting thing, and this is what connects everything
with complexity, the interesting thing is you start to see
phenomena that you see in other fields.
You get multiple possible outcomes,
so if you play the experiment once you might head over
this way, everybody’s driving on the left side
of the road, if it’s left up to chance, or
play history again, small events, you might wind up
with all cars drive on the right side of the road just by chance.
We’re speaking English, or at least I hope so,
but we could equally have been speaking French or something if small events had
steered us into different paths a couple of hundred
years ago. So you see phenomena that you
see in physics, or you might see in immunology
different patterns coming
out, small events steering into different ones
certain patterns that repeat, you
can’t perfectly predict, but what you can do is study the structures and patterns
that come out. And you see plenty of phase transitions, and I’m sure
that -- your course takers, I’m sure
are very familiar with that, in some regimes
the system can go chaotic, in other regimes
it settles into some unique attractor, and
in the middle, quite wonderful complex things
can happen with long correlation lengths and things like that.
So not surprisingly in economics we’re seeing
a lot of phenomena that you’re seeing in other fields.