Abstract
Numerous theoretical and empirical studies have examined the economics of income distribution and redistribution. Kolm [5] and Atkinson’s [1] original papers initiated extensive theoretical discussions on techniques to measure income inequality. Lambert’s [6] milestone book completely reviewed the theoretical basis underlying income distribution and related issues including redistribution, social welfare, and poverty. With the development of theory in income distribution, economists are eager to apply the theory to empirical problems in welfare economics, labor economics, and development economics [2]. Income related data become the key component of all empirical analysis. How to analyze the income data correctly and efficiently is the challenge to every researcher in this field. Hardware seems no longer to be a problem after the information technology advance from the outdated IBM mainframes to personal computers that are much faster and smaller nowadays. However, there is no single dominant software for income distribution analysis. Popular statistical packages, like SAS, Stata, and GAUSS, were not developed specifically for economists who are interested in income inequality, redistribution and social welfare. These software packages do not provide the most effective way to analyze income data for the following reasons:
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