Averaging Lorenz curves

A large number of functional forms has been suggested in the literature for estimating Lorenz curves that describe the relationship between income and population shares. The traditional way of overcoming functional-form uncertainty when estimating a Lorenz curve is to choose the function that best fits the data in some sense. In this paper we describe an alternative approach for accommodating functional-form uncertainty, namely, how to use Bayesian model averaging to average the alternative functional forms. In this averaging process, the different Lorenz curves are weighted by their posterior probabilities of being correct. Unlike a strategy of picking the best-fitting function, Bayesian model averaging gives posterior standard deviations that reflect the functional-form uncertainty. Building on our earlier work (Chotikapanich and Griffiths, 2002), we construct likelihood functions using the Dirichlet distribution and estimate a number of Lorenz functions for Australian income units. Prior information is formulated in terms of the Gini coefficient and the income shares of the poorest 10% and poorest 90% of the population. Posterior density functions for these quantities are derived for each Lorenz function and are averaged over all the Lorenz functions. Copyright Springer 2005Gini coefficient, Bayesian inference, Dirichlet distribution,

The Atkinson Inequality Measure and its Sampling Properties: Bayesian and Classical Approaches

This paper examines several Bayesian methods of obtaining posterior probability density functions of the Atkinson inequality measure and its associated social welfare function, in the context of grouped income distribution data. The methods are compared with asymptotic standard errors. The role of the number of income classes is investigated using a simulated distribution. If only a small number of groups is available in published data, there is a clear gain from generating the posterior probability density function when using an explicit income distribution assumption. Even with a small number of groups, the Bayesian approach gives results that are close to the sample values obtained using the corresponding individual observations. Copyright Blackwell Publishing Ltd/University of Adelaide and Flinders University of South Australia 2004.

Distribution of Income and Taxes in Slovenia and Croatia

The purpose of this article is to estimate the redistributive effects of personal income tax (PIT) in Slovenia and Croatia. The decomposition of the Gini coefficient developed by Aronson, Johnson & Lambert reveals only a limited difference between potential and actual redistribution, with this loss being a consequence of the different tax treatment of taxpayers with equal pre-tax income. The results also suggest that Croatia experiences greater income inequality among taxpayers than Slovenia. Another decomposition of inequality measure indicates that some types of income — especially wages — contribute a constant and high proportion to the overall inequality seen in both countries during the period examined.

The measurement of inequality in Fiji's household income distribution

Measures of inequality determine the effectiveness of social and economic policies aimed at reducing inequality and to design effective intervention policies. The purpose of this paper is to focus on poverty reduction and welfare improving impacts of reducing income inequality in the case of Fiji. Using Fiji’s Household Income and Expenditure Survey 2002-2003, a comprehensive analysis is used to measure the level of inequality by household income, quintile income distribution, decomposition of inequality by ethnicity and regional groups, and the household income inequality by source of income