A study of the personal income distribution in Australia

Abstract

We analyze the data on personal income distribution from the Australian Bureau of Statistics. We compare fits of the data to the exponential, log-normal, and gamma distributions. The exponential function gives a good (albeit not perfect) description of 98% of the population in the lower part of the distribution. The log-normal and gamma functions do not improve the fit significantly, despite having more parameters, and mimic the exponential function. We find that the probability density at zero income is not zero, which contradicts the log-normal and gamma distributions, but is consistent with the exponential one. The high-resolution histogram of the probability density shows a very sharp and narrow peak at low incomes, which we interpret as the result of a government policy on income redistribution.

7 pages, 4 figures, Proceedings of the Econophysics Colloquium, Canberra, 14-18 November 2005

Cited by in corpus (13)

• Interplay between topology and dynamics in the World Trade Web
• The k-generalized distribution: A new descriptive model for the size distribution of incomes
• Evidence for the Gompertz Curve in the Income Distribution of Brazil 1978-2005
• Modeling of income distribution in the European Union with the Fokker-Planck equation
• Effects of network topology on wealth distributions
• Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World
• Stochastic volatility of financial markets as the fluctuating rate of trading: an empirical study
• Ideal-gas like market models with savings: quenched and annealed cases
• An statistical analysis of stratification and inequity in the income distribution
• Kinetic market models with single commodity having price fluctuations
• Applications of statistical mechanics to economics: Entropic origin of the probability distributions of money, income, and energy consumption
• Income Distribution in the European Union Versus in the United States
• Taxes in a simple wealth distribution model by inelastically scattering particles