We develop a GMM procedure for estimating income distributions from grouped data with unknown group bounds. The approach enables us to obtain standard errors for the estimated parameters and functions of the parameters, such as inequality and poverty measures, and to test the validity of an...

In this paper, income distributions for developing countries in Asia are modeled using beta-2 distributions, which are estimated by a method of moments procedure applied to grouped data. Estimated parameters of these distributions are used to calculate measures of inequality, poverty, and...

A major problem encountered in studies of income inequality at regional and global levels is the estimation of income distributions from data that are in a summary form. In this paper we estimate national and regional income distributions within a general framework that relaxes the assumption of...

Recently, there has been a resurgence of studies on the distribution of income and inequality at regional and global levels, largely driven by the concerns of economists, international development organisations and the general public about the overall effects of globalisation on growth and...

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...

In this paper, income distributions for developing countries in Asia are modeled using beta-2 distributions, which are estimated by a method of moments procedure applied to grouped data. Estimated parameters of these distributions are used to calculate measures of inequality, poverty, and...