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Center for Nonlinear Studies |
The talk reviews 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 found 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 a Pareto power-law ("superthermal") distribution, whose parameters change in time with the rise and fall of financial markets. Recent studies, such as the role of debt and the distribution of bank account balances, are discussed. For a review article, see arXiv:0709.3662.
Host: Alexander Balatsky, T-4