2010
DOI: 10.1088/1367-2630/12/7/075032
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Universal patterns of inequality

Abstract: Probability distributions of money, income, and energy consumption per capita are studied for ensembles of economic agents. The principle of entropy maximization for partitioning of a limited resource gives exponential distributions for the investigated variables. A non-equilibrium difference of money temperatures between different systems generates net fluxes of money and population. To describe income distribution, a stochastic process with additive and multiplicative components is introduced. The resultant … Show more

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Cited by 113 publications
(149 citation statements)
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References 28 publications
(70 reference statements)
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“…However, there is also a class of phenomena that follow a much different probability curve that has a very high probability at one end of the range of occurrences and very low at the other end. These power curve probabilities are often suggested for varying physical, natural, economic and social phenomena [75][76][77][78][79][80][81]. Examples of phenomena following a power distribution are earthquakes [75], the number of species in general [79], the use of words [77] and the distribution of wealth [82].…”
Section: Distance Decay and Power Curvesmentioning
confidence: 99%
“…However, there is also a class of phenomena that follow a much different probability curve that has a very high probability at one end of the range of occurrences and very low at the other end. These power curve probabilities are often suggested for varying physical, natural, economic and social phenomena [75][76][77][78][79][80][81]. Examples of phenomena following a power distribution are earthquakes [75], the number of species in general [79], the use of words [77] and the distribution of wealth [82].…”
Section: Distance Decay and Power Curvesmentioning
confidence: 99%
“…Subsequent studies revealed that the distributions of income and wealth possess a number of fairly robust features: the bulk of both the income and wealth distributions seem to reasonably fit both the log-normal and the Gamma distributions (see, e.g., [6]). Economists prefer the lognormal distribution [10,11], while statisticians [12] and physicists [13][14][15][16][17] emphasize on the Gamma distribution for the probability density or Gibbs/ exponential distribution for the corresponding cumulative distribution. However, the high end of the distribution (known as the 'tail') fits well to a power law as observed by Pareto, the exponent known as the Pareto exponent, usually ranging between 1 and 3 (see e.g.…”
Section: Introductionmentioning
confidence: 99%
“…13 This is in exact correspondence to the conservation of number of molecules and total energy in the kinetic theory of gases. Following Banerjee and Yakovenko ([2010]), we can characterise a 12 The comparison that is particularly pertinent here is with Boltzmann's original 1872 model Boltzmann ([1970]). …”
Section: Econophysics Models For Income Distributionmentioning
confidence: 99%
“…The definition of entropy as S = lnΩ reflects this correspondence. A large N approximation together with a little analytical work Banerjee and Yakovenko ([2010]) [p.4] then leads us to the distribution:…”
Section: Econophysics Models For Income Distributionmentioning
confidence: 99%