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Statistical Physics Perspective on Economic Inequality

This article is a supplement to my main contribution to the Routledge Handbook of Complexity Economics (2023). On the basis of three recent papers, it presents an unconventional perspective on economic inequality from a statistical physics point of view. One section demonstrates empirical evidence for the exponential distribution of income in 67 countries around the world. The exponential distribution was not familiar to mainstream economists until it was introduced by physicists by analogy with the Boltzmann-Gibbs distribution of energy and subsequently confirmed in empirical data for many countries. Another section reviews the two-class structure of income distribution in the USA. While the exponential law describes the majority of population (the lower class), the top tail of income distribution (the upper class) is characterized by the Pareto power law, and there is no clearly defined middle class in between. As a result, the whole distribution can be very well fitted by using only three parameters. Historical evolution of these parameters and inequality trends are analyzed from 1983 to 2018. Finally, global inequality in energy consumption and CO2 emissions per capita is studied using the empirical data from 1980 to 2017. Global inequality, as measured by the Gini coefficient G, has been decreasing until around 2010, but then saturated at the level G=0.5. The saturation at this level was theoretically predicted on the basis of the maximal entropy principle, well before the slowdown of the global inequality decrease became visible in the data. This effect is attributed to accelerated mixing of the world economy due to globalization, which brings it to the state of maximal entropy and thus results in global economic stagnation. This observation has profound consequences for social and geopolitical stability and the efforts to deal with the climate change.

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