Various inequality and social welfare measures often depend heavily on the choice of a distribution of income. Picking a distribution that best fits the data involves throwing away information and does not allow for the fact that a wrong choice can be made. Instead, Bayesian model averaging utilizes a weighted average of the results from a number of income distributions, with each weight given by the probability that a distribution is 'correct'. In this study, prior densities are placed on mean income, the mode of income and the Gini coefficient for Australian income units with one parent (1997-8). Then, using grouped sample data on incomes, posterior densities for the mean and mode of income and the Gini coefficient are derived for a variety of income distributions. The model-averaged results from these income distributions are obtained. Copyright Blackwell Publishers Ltd and the Board of Trustees of the Bulletin of Economic Research, 2005.
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