[lbo-talk]

Jerry Monaco :

Does anyone have a critique of this, besides just general hostility?
The link to the original paper is at the bottom.


 World's economies show similarities in economic inequality
http://www.physorg.com/news95074548.html

Economists who yearn for the redistribution of wealth in an ideal
society are up against history. According to a recent study, the
uneven distribution of wealth in a society appears to be a universal
law that holds true for economies in many different societies, from
ancient Egypt to modern Japan and the U.S. This distribution may
reflect a simple natural law analogous to a 100-year-old theory
describing the distribution of energy in a gas.

Scientists Arnab Chatterjee and Bikas Chakrabarti from the Saha
Institute of Nuclear Physics, along with Sitabhra Sinha of the
Institute of Mathematical Sciences, both in India, have analyzed a
variety models explaining different sets of data, and found striking
similarities. The results show that the poorer majority of the
population follows one distribution, while a small proportion of the
wealthiest people veers off in a tail following a power-law
distribution, in essence reflecting how "the rich get richer."

The studies included large sets of data from sources such as income
tax returns and net values of assets in societies including Japan, the
U.S., the UK, India, and nineteenth century Europe. The data, taken
from a large number of recent publications by several groups,
represented a variety of different economies and stages of
development. Generally, the lower 90% of the population (in terms of
income) followed a log-normal distribution, characterized by an
initial rapid rise in population followed by a rapid fall as income
increased.

[World's economies show similarities in economic inequality]


However, the top 2-10% of the population deviated from this bulk
distribution, as scientists discovered more very rich people than
would be expected using the log-normal model. Instead, this top tier
followed a power law with a certain exponent called the Pareto
exponent, named after Vilfredo Pareto, who first observed this power
law in the 1890s.

"While the distribution of the richest 10% does indeed follow a
different behavior (power law) than the rest (Gibbs or log-normal),
one need not assume different dynamics at work in the two cases,"
Chatterjee explained to PhysOrg.com. "In fact, both types of
distributions can arise from the same model. In the case of the random
savings model, the agents having the highest savings fractions will
have a higher probability of ending up in the richest 10% of the
population, while in the random thrift model, the agents with higher
thrift value generally tend to be the richest.

"As an agent gets richer, a feedback effect occurs by which the rich
are more likely to gain from a transaction than the poorer
agents-thereby resulting in an accumulation of assets for the richer
players that is manifested as a power law tail."

When comparing these income and wealth distributions to a physical
model called the Gibbs distribution, the scientists found that the
economic model of the poorer 90% seemed to fit very well with this
natural law. Proposed in the late 1800s, the Gibbs distribution is a
thermodynamic model that describes the distribution of energy in an
ideal gas in equilibrium.

The economic model and the gas model share basic characteristics. As
Chatterjee et al. explain, the asset- (e.g. money-) trading process
can be viewed as a molecule scattering process-in both cases, assets
or molecules are conserved (on the time scale of the model). Also,
even though an individual does not see asset exchanges as random, the
scientists show that, from a global level, exchanging assets or
scattering molecules are indeed random processes.

"As described in our paper, the Gibbs form seems to be a better fit
for the data than the log-normal form (which is preferred by many
economists)," Chatterjee explained. "Note, for a particular [savings
factor], the resultant [distribution] only fits the lower 90% of the
population. To fit the entire range, including the power law tail, one
needs a suitably distributed saving propensity. In the thrift model,
one obtains realistic values of the Pareto exponent (i.e., as seen in
society) by assuming a distribution of the thrift parameter. Hence,
both these models can explain both the features of the observed income
distribution."

Aside from these general models, the scientists also discovered some
interesting details within their results. When comparing wealth (i.e.
one's net worth) with income, they found that wealth is much more
unequally distributed than income (wealth models always have lower
Pareto exponents, for any society). Also, while most of the data for
the models is based on individuals, data from companies also seemed to
follow the same models.

Even though the model shows a widespread inequality among citizens in
a society, however, the scientists' findings might also provide
guidance for experts trying to distribute wealth more evenly.

"With uniform savings and large saving propensity, our model would
yield a narrow peaked income distribution, which corresponds to a
socialist economy," Chatterjee said. "Note that, here, the super-rich
are absent, and the bulk of the population is described by a narrow
most-probable income distribution, or everybody ending up with the
average money in the market-a socialist's ideal dream."

Since the richer agents demonstrate certain characteristics in savings
and thrift, the scientists explain that certain characteristics might
make citizens in a society "more" financially equal.

"A way to exercise this would be to modify the saving patterns of the
individuals, making all of them have a similar and large saving
propensity, to be precise. In isolated sectors where such
manipulations with savings propensities were possible, our predicted
effects had indeed been seen earlier by social statisticians (such as
J. Angle) and analysts (such as G. Willis and J. Mimkes).

"In the thrift model," Chatterjee continued, "introducing different
distributions of thrift among the agents can result in more or less
equitable distributions. Also, introducing certain forms of taxation
in random asset exchange models have resulted in more equitable
distributions. These could help experts make policies for a more
equitable distribution of wealth in society."

Citation: Chatterjee, Arnab, Sinha, Sitabhra, and Chakrabarti, Bikas
K. "Economic Inequality: Is it Natural?" Currently at
http://arxiv.org/abs/physics/0703201 ; To be published in Current
Science.

Copyright 2007 PhysOrg.com.
All rights reserved. This material may not be published, broadcast,
rewritten or redistributed in whole or part without the express
written permission of PhysOrg.com.

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