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This Economy Does Not Compute
Source Jim Devine
Date 08/10/04/19:49

www.nytimes.com
Op-Ed Contributor
This Economy Does Not Compute
By MARK BUCHANAN
Notre-Dame-de-Courson, France

A FEW weeks ago, it seemed the financial crisis wouldn't spin
completely out of control. The government knew what it was doing at
least the economic experts were saying so and the Treasury had taken
a stand against saving failing firms, letting Lehman Brothers file for
bankruptcy. But since then we've had the rescue of the insurance giant
A.I.G., the arranged sale of failing banks and we'll soon see, in one
form or another, the biggest taxpayer bailout of Wall Street in
history. It seems clear that no one really knows what is coming next.
Why?

Well, part of the reason is that economists still try to understand
markets by using ideas from traditional economics, especially
so-called equilibrium theory. This theory views markets as reflecting
a balance of forces, and says that market values change only in
response to new information the sudden revelation of problems about
a company, for example, or a real change in the housing supply.
Markets are otherwise supposed to have no real internal dynamics of
their own. Too bad for the theory, things don't seem to work that way.

Nearly two decades ago, a classic economic study found that of the 50
largest single-day price movements since World War II, most happened
on days when there was no significant news, and that news in general
seemed to account for only about a third of the overall variance in
stock returns. A recent study by some physicists found much the same
thing financial news lacked any clear link with the larger movements
of stock values.

Certainly, markets have internal dynamics. They're self-propelling
systems driven in large part by what investors believe other investors
believe; participants trade on rumors and gossip, on fears and
expectations, and traders speak for good reason of the market's
optimism or pessimism. It's these internal dynamics that make it
possible for billions to evaporate from portfolios in a few short
months just because people suddenly begin remembering that housing
values do not always go up.

Really understanding what's going on means going beyond equilibrium
thinking and getting some insight into the underlying ecology of
beliefs and expectations, perceptions and misperceptions, that drive
market swings.

Surprisingly, very few economists have actually tried to do this,
although that's now changing if slowly through the efforts of
pioneers who are building computer models able to mimic market
dynamics by simulating their workings from the bottom up.

The idea is to populate virtual markets with artificially intelligent
agents who trade and interact and compete with one another much like
real people. These "agent based" models do not simply proclaim the
truth of market equilibrium, as the standard theory complacently does,
but let market behavior emerge naturally from the actions of the
interacting participants, which may include individuals, banks, hedge
funds and other players, even regulators. What comes out may be a
quiet equilibrium, or it may be something else.

For example, an agent model being developed by the Yale economist John
Geanakoplos, along with two physicists, Doyne Farmer and Stephan
Thurner, looks at how the level of credit in a market can influence
its overall stability.

Obviously, credit can be a good thing as it aids all kinds of creative
economic activity, from building houses to starting businesses. But
too much easy credit can be dangerous.

In the model, market participants, especially hedge funds, do what
they do in real life seeking profits by aiming for ever higher
leverage, borrowing money to amplify the potential gains from their
investments. More leverage tends to tie market actors into tight
chains of financial interdependence, and the simulations show how this
effect can push the market toward instability by making it more likely
that trouble in one place the failure of one investor to cover a
position will spread more easily elsewhere.

That's not really surprising, of course. But the model also shows
something that is not at all obvious. The instability doesn't grow in
the market gradually, but arrives suddenly. Beyond a certain threshold
the virtual market abruptly loses its stability in a "phase
transition" akin to the way ice abruptly melts into liquid water.
Beyond this point, collective financial meltdown becomes effectively
certain. This is the kind of possibility that equilibrium thinking
cannot even entertain.

It's important to stress that this work remains speculative. Yet it is
not meant to be realistic in full detail, only to illustrate in a
simple setting the kinds of things that may indeed affect real
markets. It suggests that the narrative stories we tell in the
aftermath of every crisis, about how it started and spread, and about
who's to blame, may lead us to miss the deeper cause entirely.

Financial crises may emerge naturally from the very makeup of markets,
as competition between investment enterprises sets up a race for
higher leverage, driving markets toward a precipice that we cannot
recognize even as we approach it. The model offers a potential
explanation of why we have another crisis narrative every few years,
with only the names and details changed. And why we're not likely to
avoid future crises with a little fiddling of the regulations, but
only by exerting broader control over the leverage that we allow to
develop.

Another example is a model explored by the German economist Frank
Westerhoff. A contentious idea in economics is that levying very small
taxes on transactions in foreign exchange markets, might help to
reduce market volatility. (Such volatility has proved disastrous to
countries dependent on foreign investment, as huge volumes of outside
investment can flow out almost overnight.) A tax of 0.1 percent of the
transaction volume, for example, would deter rapid-fire speculation,
while preserving currency exchange linked more directly to productive
economic purposes.

Economists have argued over this idea for decades, the debate usually
driven by ideology. In contrast, Professor Westerhoff and colleagues
have used agent models to build realistic markets on which they impose
taxes of various kinds to see what happens.

So far they've found tentative evidence that a transaction tax may
stabilize currency markets, but also that the outcome has a surprising
sensitivity to seemingly small details of market mechanics on
precisely how, for example, the market matches buyers and sellers. The
model is helping to bring some solid evidence to a debate of extreme
importance.

A third example is a model developed by Charles Macal and colleagues
at Argonne National Laboratory in Illinois and aimed at providing a
realistic simulation of the interacting entities in that state's
electricity market, as well as the electrical power grid. They were
hired by Illinois several years ago to use the model in helping the
state plan electricity deregulation, and the model simulations were
instrumental in exposing several loopholes in early market designs
that companies could have exploited to manipulate prices.

Similar models of deregulated electricity markets are being developed
by a handful of researchers around the world, who see them as the only
way of reckoning intelligently with the design of extremely complex
deregulated electricity markets, where faith in the reliability of
equilibrium reasoning has already led to several disasters, in
California, notoriously, and more recently in Texas.

Sadly, the academic economics profession remains reluctant to embrace
this new computational approach (and stubbornly wedded to the
traditional equilibrium picture). This seems decidedly peculiar given
that every other branch of science from physics to molecular biology
has embraced computational modeling as an invaluable tool for gaining
insight into complex systems of many interacting parts, where the
links between causes and effect can be tortuously convoluted.

Something of the attitude of economic traditionalists spilled out a
number of years ago at a conference where economists and physicists
met to discuss new approaches to economics. As one physicist who was
there tells me, a prominent economist objected that the use of
computational models amounted to "cheating" or "peeping behind the
curtain," and that respectable economics, by contrast, had to be
pursued through the proof of infallible mathematical theorems.

If we're really going to avoid crises, we're going to need something
more imaginative, starting with a more open-minded attitude to how
science can help us understand how markets really work. Done properly,
computer simulation represents a kind of "telescope for the mind,"
multiplying human powers of analysis and insight just as a telescope
does our powers of vision. With simulations, we can discover
relationships that the unaided human mind, or even the human mind
aided with the best mathematical analysis, would never grasp.

Better market models alone will not prevent crises, but they may give
regulators better ways for assessing market dynamics, and more
important, techniques for detecting early signs of trouble. Economic
tradition, of all things, shouldn't be allowed to inhibit economic
progress.

Mark Buchanan, a theoretical physicist, is the author, most recently,
of "The Social Atom: Why the Rich Get Richer, Cheaters Get Caught and
Your Neighbor Usually Looks Like You."

Copyright 2008 The New York Times Company

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