Re: [xmca] Re: déjatel¹ nost¹

This was a great post among many, Martin. Thank you.

And that NYT op-ed piece you included was quite worth reading. It
makes me wonder, among numerous other things, such as Rosa
Luxembourg's famous prediction of "socialism, or barbarism," that if
computer modeling can be usefully applied to economic systems, could
it be applied to activity systems, and if CHAT could contribute to
using computer modeling in the social sciences.

- Steve

On Oct 1, 2008, at 12:46 PM, Martin Packer wrote:

> 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
>
> TimesPeople
> [image: The New York Times] <http://www.nytimes.com/> [image:
> Printer
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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 15:49 PDT 2008