Received: by alpheratz.cpm.aca.mmu.ac.uk id LAA01605 (8.6.9/5.3[ref email@example.com] for cpm.aca.mmu.ac.uk from firstname.lastname@example.org); Mon, 26 Mar 2001 11:52:13 +0100 Message-Id: <200103261052.LAA01605@alpheratz.cpm.aca.mmu.ac.uk> Errors-To: email@example.com Precedence: bulk Reply-To: firstname.lastname@example.org Sender: email@example.com To: CAMREC list members <firstname.lastname@example.org> From: the Campaign for Real Economics <email@example.com> Date: Mon, 26 Mar 2001 11:51:20 +0100 Subject: Re: CAMREC: Power-laws, teleology and econophysicsboundary="=====================_3037698==_.ALT"
The issues involved with intentionality and econophysics seem much more like
modelling and applications than philosophical issues.
Econophysics seems to stem largely from the Mandlebrot-Bak results on stable
Paretian distributions (Mandlebrot) and self organised criticality (Bak). I
believe -- and would welcome correction if I am wrong -- that the observation
of power law distributions are evidence for the existence of a stable Paretian
distribution. If that is right, one important question is how close the
observed distributions are to power laws. In playing around with simulation
models, I find that most double log distributions can be imagined to be fairly
linear as long as the tails of the distribution are fat relative to the
gaussian distribution with the same mean and variance. Interestingly, the
power law distributions are frequently exhibited graphically in the literature
but I have not yet seen any systematic formal attempt to represent the goodness
of the power law distribution fit.
More robustly, I find that in my social simulation models, relevant scale-rank
distributions are unambiguously leptokurtic. That is, the peaks of the
distributions are about 3 orders of magnitude higher for simulated price
change, volume change, market shares, etc. than for the gaussian distribution
with the same mean and variance. Leptokurtosis is a property of stable
Paretian distributions but it is also a property of any fat-tailed
distribution. It is the fat tails -- the presence of occasional extreme events
-- that causes the peaks to be so much higher than the gaussian equivalent.
Simulation experiments of the sort undertaken by Bak and inspired by his
research programme have demonstrated systematically (and without any reported
counterexamples known to me) that extreme events (hence, fat tailed
distributions) occur without tuning when the simulated system is dissipative
with a high degree of interaction among metastable system components.
In physical systems, the lack of intentionality (more generally, cognition
including intentionality) among components makes the hypothesis of stable
distributions including occasional extreme events more plausible than in social
systems where individuals will seek to exploit or avoid extreme events. In
social systems, a common intention is frequently to change the structure of a
system in order to avoid extreme events. Changing the structure of the system
and the interactions among agents seems likely to change the distribution of
events. We see this in the evolution of markets -- and not just financial
markets -- where technologies evolve to change those interactions and sometimes
specifically to reduce the incidence or impact of extreme events.
It does seem to me to be an interesting question whether the effect of
intentionality is to make observed distributions unstable. It might even be
that intentionality generates time varying parameters but the distribution of
the time series of parameter values is itself non-gaussian and Paretian, hence
power law distributed.
These ruminations have clear modelling implications and can be related to
observation. Is some other (more philosophical) justification needed?
the Campaign for Real Economics wrote:
> Power-laws and teleology:
> I've been interested in Econophysics for some time, seems a natural way to
> view human activity. I've been surprised by the lack of interest expressed
> by economists, though.
> It seems that blending economics and physics may have deeper philosophic
> differences than I thought. Economics must explicitly acknowledge that
> competitive agents act with 'intent.' Physics has no formal notion of
> 'agent intent.' The existence of intent adds teleology and metaphysics
> prior to the epistemological level. I doubt that physics even uses the
> notion of 'agents', there are only 'objects.' On a billiard table, one only
> needs initial conditions to predict system behavior. The billiard balls
> have no 'intent.' Teleology has been exorcised from physics.
> This leads me to ask what it is that we demonstrate when systems of
> 'intending agents' and' un-intentional objects' both exhibit power-law
> distributions. Power-law distributions are regularly seen in biological
> populations, human societies and quantum physics. What does it mean for a
> stockmarket to display power-laws despite the high degree of freedom agents
> possess, where every agent seems to have complete freedom to pursue any
> strategy (including withdrawal)? Can we construct a mechanistic simulation
> model that successfully demonstrates agent behavior in both intentional and
> unintentional styles?
> It looks like this is the same problem facing molecular biologists. They
> can describe every reaction in terms of pure (unintentional) physical
> chemistry, but this begs the question of where intentionality emerges? At
> what point can one hook intentionality to an organizational unit?
> We don't have any trouble assigning intention to humans. Most would say
> dogs and cats have intentions. Some would say the heart intents to pump
> blood and lungs intend to obtain oxygen from the air. A few might say white
> blood cells intend to destroy foreign proteins. Personally, I'd have a hard
> time ascribing intention at a lower level than a cell, but others go much
> Where is the epistemological justification for an econophysicist to hook
> intention to simulated agent?
-- Professor Scott Moss Director Centre for Policy Modelling Manchester Metropolitan University Aytoun Building Manchester M1 3GH UNITED KINGDOM
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