Income Inequality Decomposition, Russia 1992-2002: Method and Application

Decomposition methods for income inequality measures, such as the Gini index and the members of the Generalised Entropy family, are widely applied. Most methods decompose income inequality into a between (explained) and a within (unexplained) part, according to two or more population subgroups or income sources. In this article, we use a regression analysis for a lognormal distribution of personal income, modelling both the mean and the variance, decomposing the variance as a measure of income inequality, and apply the method to survey data from Russia spanning the first decade of market transition (1992-2002). For the first years of the transition, only a small part of the income inequality could be explained. Thereafter, between 1996 and 1999, a larger part (up to 40%) could be explained, and ‘winner’ and ‘loser’ categories of the transition could be spotted. Moving to the upper end of the income distribution, the self-employed won from the transition. The unemployed were among the losers.