From: Ian Wright (ian_paul_wright@HOTMAIL.COM)
Date: Thu Jun 12 2003 - 16:27:14 EDT
Hello Philip, Thanks for your reply. I thought you were arguing against the possibility of applying statistical mechanics to understanding certain stationary distributions, such as income distributions. But on a closer reading I see you were questioning the relevance of deterministic theories. My point was only that these distributions can be regarded as stationary for our purposes, because empirically they seem to be constant for long periods of time. In this case the distributions can be understood as maximum entropy distributions, i.e. the system has reached the most probable dynamic state given the constraints on the system, such as fixed money, fixed population and local money conservation. In the case of income distribution an individual has a finite lifespan and so I agree it is clear that their income will not time-average to the distribution mean. But I would like a satisfactory explanation of why the approach adopted in "statistical mechanics of money" generates a distribution in close agreement with reality (ignoring, for the moment, the lower and upper tails). I would need to look into it, but I would guess their model is ergodic. The answer may lie in a more flexible interpretation of the model. The particles in the model can be interpreted as referring to roles, rather than distinct individuals. Distinct individuals enter and leave the system by assuming a role in the economy. The roles do not change, and are "infinitely" lived, compared to the individuals that assume those roles. The income of any particular role will time-average to the distribution mean, even if in the interpretation an individual's income cannot. Does this make sense to you? It seems to me that the same argument can be applied to firms, capital etc. -Ian. _________________________________________________________________ Help STOP SPAM with the new MSN 8 and get 2 months FREE* http://join.msn.com/?page=features/junkmail
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