# **V.2.  Decomposition of inequality by groups**

A notable drawback of inequality decompositions based on components such as those presented in the previous subsection, is their reliance on income data, with the attendant problems of accurate reporting discussed in Section II of this paper.

However, with the population divided into groups affected by transition, total inequality can also be represented as the sum of inequality from _within_ each of the groups and part of the inequality coming from differences in means _between_ these groups. Decompositions of inequality by groups allow one to move to indicators of inequality in consumption, which is superior to income in terms of data quality.

This subsection decomposes consumption inequality in seven representative transition countries into the contribution of inequality ‘between’ groups and inequality ‘within’ groups using the Theil entropy measure of inequality (F. Bourguignon (1979) and A. Shorrocks (1980)). The sum of the within- and between-group contributions equals 1.

Table 7 A-C<sup>11</sup> show to what extent inequality can be explained by inequality between groups, such as (i) rural residents versus city dwellers, (ii) high school graduates versus those with less education, and (iii) working families versus jobless households. The choice of these partitions is designed to capture some key dimension of transition such as the emergence of new social classes and changing distribution within those classes. While none of them corresponds as neatly to a set of drivers of inequality as the distribution of income by source, they complement the story emerging from the decomposition of income in an important way. First, they identify winning and losing groups more clearly than is possible with decomposition by income source. Second, differences by educational attainment help assess the magnitude and dynamics of inequality effects related to technological change. Third, they add location effects, which account for a significant share of inequality in virtually every country, since transition resulted in changes in the concentration of economic activity and migration.

# **_Urban-Rural (Location) (Table 7 A)_**

_Changes in structure_ . There were significant changes in the distribution of population across locations: in Hungary, the share of rural areas dropped from 38 percent to 35 percent of population during the period under review; in Latvia the share of Riga increased from 33 to 38 percent, and in Tajikistan the share of rural areas dropped from 78 to 73 percent in just 5 years. People have been migrating to higher income areas. As a result this driver reduced inequality. Had the initial distribution of population by location stayed the same, inequality in Latvia, for example, would have been 15 percent higher and that in Tajikistan 12 percent higher by 2003.

> 11 The Table relies on per capita equivalence scale, as Tables 3-4, where data availability dictated the choice. For Table 5 however, results are also available on per equivalent adult basis (with constant degree of returns to scale, θ 0.5 or 0.75), results are broadly in line with reported (with exception of Moldova), and are available from authors on request.

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