Re: [xmca] Re: déjatel¹ nost¹

Andy Blunden wrote:

But yes, Marx unfolded it all out of the commodity relation.

I suppose so, in a manner of speaking. Certainly Marx's analysis of the
commodity tells us something key about the capitalist kind of economy. It
tells us about a central way for entities to be; it tells us about the
ontology of capitalism. Marx tells us not just that commodities exist in
this kind of social reality, he tells us about the processes in which they
are created and destroyed. His is a "critical" analysis that explores the
conditions for the possibility of commodities (and of capitalism as a
whole). (It's also critical in the sense of exposing the inherent injustice
of buying people's labor and paying them less than the value of the goods
they produce. The relations among people, and people's productive work,
exist as commodities too.)

But I think Marx never forgot the people whose conduct is mediated by
commodities. The fact that we need to eat and sleep if we are to do a
productive day's work. That we die and can't take our accumulated capital
with us. That it takes two parents to produce a new worker. Can one say that
these facts are built into the form of the commodity? I think so.
Regulations about ownership and inheritance reflect some of these facts.
Hourly wage rules reflect others. Commodities are tailored to the (so-far)
unavoidable realities of human existence. Commodities have affordances -
there are some practices we can perform with them, others we can't. But
people have affordances too, despite our plasticity - there are some things
you can do with a worker, others you can't. Figuring out which is which is
one of the key struggles in this form of life, as you know well.

So commodity (understood as a form, as a relation) is the unit of analysis.
But it was the whole system, in its complexity, dynamism, inequity and
contradictions, that Marx was trying to understand. One thing I find
fascinating about the NY Times Op Ed piece this morning (I've copied the
text below) is the suggestion that this system is in fact an emergent order,
'merely' the product of the acts of multiple agents. There is no such
'thing' to the system separate from what humans do. If we all stayed in bed
one morning and refused to work, the system would vanish. The
interobjectivity of buildings and equipment would remain, but unanimated,
nothing would get done. I don't know what capacities were built into the
agents in the simulation that is reported in this article - not
rational-choice individualism, I assume - but this is where having a
Vygotskian around would be very useful!

Martin

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------------------------------
October 1, 2008
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."
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Received on Wed Oct 1 12:48 PDT 2008