Wealth distribution in modern societies: Collected data and a master equation approach

Gere, István; Kelemen, Szabolcs; Tóth, Géza; Bı́ró, Tamás; Néda, Zoltán

doi:10.1016/j.physa.2021.126194

Cited by 7 publications

(17 citation statements)

References 20 publications

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“…To focus on the most recent related publication, Néda et al [132] used income data from Japan (2015), USA (2013), Russia (2015), Australia (2011), Finland (2017), Hungary (2015) and a county in Romania (2005), fitting a simple and elegant model to them, and identified a beta prime distribution, which has a Pareto tail with tail index ξ = 1/3. The same research team, in a follow-up publication [133], examined the wealth data for the USA and Russia and again reported a Pareto tail.…”

Section: Hyperbolic Background Measure and The Pareto Distributionmentioning

confidence: 97%

Entropy and Wealth

Koutsoyiannis

Sargentis

2021

Entropy

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While entropy was introduced in the second half of the 19th century in the international vocabulary as a scientific term, in the 20th century it became common in colloquial use. Popular imagination has loaded “entropy” with almost every negative quality in the universe, in life and in society, with a dominant meaning of disorder and disorganization. Exploring the history of the term and many different approaches to it, we show that entropy has a universal stochastic definition, which is not disorder. Hence, we contend that entropy should be used as a mathematical (stochastic) concept as rigorously as possible, free of metaphoric meanings. The accompanying principle of maximum entropy, which lies behind the Second Law, gives explanatory and inferential power to the concept, and promotes entropy as the mother of creativity and evolution. As the social sciences are often contaminated by subjectivity and ideological influences, we try to explore whether maximum entropy, applied to the distribution of a wealth-related variable, namely annual income, can give an objective description. Using publicly available income data, we show that income distribution is consistent with the principle of maximum entropy. The increase in entropy is associated to increases in society’s wealth, yet a standardized form of entropy can be used to quantify inequality. Historically, technology has played a major role in the development of and increase in the entropy of income. Such findings are contrary to the theory of ecological economics and other theories that use the term entropy in a Malthusian perspective.

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Section: Hyperbolic Background Measure and The Pareto Distributionmentioning

confidence: 97%

Entropy and Wealth

Koutsoyiannis

Sargentis

2021

Entropy

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“…Importance of such exhaustive data was recognized in our previous works on income distribution. The exhaustive data for income derived from a anonymized social-security database in ten consecutive years in the Cluj county (Romania) [14,32], allowed us to model realistically the dynamics of the income and to describe successfully its distribution.…”

Section: The Exhaustive Wealth Datamentioning

confidence: 99%

“…The low and middle classes of income and wealth can be described better with an exponential distribution. In case of wealth a third region should be considered as well, the region of negative wealth (debts), which is also characterized by an exponential trend, different from the one which applies for the low and middle classes [14].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, we proposed a simple master-equation approach based on a Local Growth and Global Reset (LGGR) [30] process to describe in a similar manner the distribution of both income and wealth [14,28]. The novelty of this approach is also its ability to describe all income and wealth regions in a unified manner, proposing a compact form of the distribution function for all income/wealth categories and capturing the regions of the negative wealth as well.…”

Section: Introductionmentioning

confidence: 99%

“…Besides presenting and discussing the relevant wealth distributions derived from the data, our additional aim is also to validate once again the modeling power of the LGGR model [14] in understanding social inequalities. By possessing exhaustive wealth data for three different economic periods in Romania we are also able to show how social inequalities varied in these turbulent times and how the growth and reset rates should be adjust in the LGGR model to account for the measured wealthdistributions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Wealth Distribution in Villages. Transition From Socialism to Capitalism in View of Exhaustive Wealth Data and a Master Equation Approach

et al. 2022

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Socio-economic inequalities derived from an exhaustive wealth distribution is studied in a closed geographical region from Transylvania (Romania). Exhaustive wealth data is computed from the agricultural records of the Sancraiu commune for three different economic periods. The data is spanning two different periods from the communist economy and gives a glance to the present situation after 31 years of free market economy in Romania. The local growth and reset model based on an analytically solvable master equation is used to describe the observed data. The model with realistically chosen growth and reset rates is successful in describing both the experimentally observed distributions and the inequality indexes (Lorenz curve, Gini coefficient, and Pareto point) derived from this data. The observed changes in the inequality measures are discussed in the context of the relevant socio-economic conditions.

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