Abstract
In human societies, we observe a wide range of types of stratification, i.e., in terms of financial class, political power, level of education, sanctity, and military force. In financial, political, and social sciences, stratification is one of the most important issues and tools as the Lorenz Curve and the Gini Coefficient have been developed to describe some of its aspects. Stratification is greatly dependent on the access of people to wealth. By “wealth”, we mean the quantified prosperity which increases the life expectancy of people. Prosperity is also connected to the water-food-energy nexus which is necessary for human survival. Analyzing proxies of the water-food-energy nexus, we suggest that the best proxy for prosperity is energy, which is closely related to Gross Domestic Product (GDP) per capita and life expectancy. In order to describe the dynamics of social stratification, we formulate an entropic view of wealth in human societies. An entropic approach to income distribution, approximated as available energy in prehistoric societies, till present-day economies, shows that stratification can be viewed as a stochastic process subject to the principle of maximum entropy and occurring when limits to the wealth of society are set, either by the political and economic system and/or by the limits of available technology.
Highlights
Social stratification in the history of human societies occurs persistently and organically, as if it obeys a natural law
For this evaluation we formulate and use the tools of total entropy of income distribution Φ[ x ] which, as we show, is related to Gross Domestic Product (GDP) per capita and an entropic index of inequality, ∆Φ, which is correlated with the Gini index, but shows more robust performance
This work puts forward an entropic evaluation of social development and economic stratification, instead of the usual economic analysis based on indicators as the GDP per capita, the Gini index and the Lorenz Curve
Summary
Social stratification in the history of human societies occurs persistently and organically, as if it obeys a natural law. Social structures are constantly changing, and this property of entropy is essential in order to understand and predict these changes For this evaluation we formulate and use the tools of total entropy of income distribution Φ[ x ] which, as we show, is related to Gross Domestic Product (GDP) per capita (the best-known growth index) and an entropic index of inequality, ∆Φ, which is correlated with the Gini index, but shows more robust performance. Both of them are validated by real-world income data.
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