Statistical Mechanics of Money, Income, and Wealth: Lessons for Global Economic Crisis

First we review the progress in applications of statistical physics to probability distributions of money, income, and wealth in a society.  Developing an analogy between the probability distributions of energy in physics and money in economics, we argue that the distribution of money should follow the exponential Boltzmann-Gibbs law for certain classes of models with interacting economic agents.  Analyzing the empirical data, we find that income distribution in the USA has a well-defined two-class structure.  The majority of the population (about 97%) belongs to the lower class characterized by the exponential ("thermal") distribution.  The upper class (about 3% of the population) has the Pareto power-law ("superthermal") distribution, whose share of the total income expands and contracts dramatically following the bubbles and busts in financial markets [5].  When debt is included in the statistical models, it destabilizes the Boltzmann-Gibbs distribution in the absence of an intrinsic mechanism for limiting debt.  As a result, the nominal wealth growth of the upper class largely comes from the debt growth of the lower class, until the economy collapses under the burden of excessive debt.  We also briefly discuss the distribution of energy consumption per capita around the world and show that it also follows the exponential Boltzmann-Gibbs law.  The data show how globalization of the world economy affects inequality of energy consumption.