index. Note that the rapid increase observed in the Gini and coefficient of variation is consistent on the scale of entropy measures. In particular, the more rapid increase in the second and third entropy measures over time further corroborates the impact of changes at the higher end of the distribution, to the extent that the magnitude of changes in income inequality on the entropy scale is proportional to α , and the largest increase is recorded for (α = 2 ).<sup>11</sup> In a context where wages and salary are the main sources of income, and where unemployment continues to be limited, the increased income inequality may also be partly driven by the widening income gaps between poor and non poor, reflecting the rising return to higher education. Between 1997 and 2000, the income share of the upper 20% of the distribution increased from 41.7% to about 45%, partly at the expenses of the poorest 20 percent of the population, whose already low income share declined further to 6.5% during the same period (see Table A. 2 in Annex). Similarly, despite the decline from its peak of almost 21 percent in 1996, unemployment rates continued to be high and by 2000, were estimated to about 14.5 percent (IMF [2003]). Compared to other countries in Eastern Europe and Central Asia, the contribution of salaries and wages to overall income inequality was already high in Latvia, where it accounted for over 60 percent of aggregate income inequality in the late 1990s (World Bank [2000b]).<sup>12</sup> The widening wage and income differentials between poor and non poor are likely to further increase the contribution of wage to income inequality.

The potential wage effect is also corroborated by a much faster increase in income inequality in the Riga region, where most income is in the form of wages and salaries. At 37, the Gini coefficient in the Riga region is close to the national estimate and substantially higher than the estimates recorded in most other regions (see Table A. 3 in Annex). The changing pattern of income inequality across geographic regions in the late 1990s contrasts with the early phase of the transition where no significant difference in income inequality was recorded across regions. Indeed, in the last Poverty Assessment, the Gini coefficient was about 33 across all five main geographical regions (World Bank [2000a]).

In addition to the prospects of a rising income gap between the poor and non-poor over time, and wage dispersion, there may be other possible causes of rapid increase in income inequality in Latvia. The first set may be associated with the growth prospects and constraints imposed by the transition to market economy. In particular, these include rising returns to education, increased risk-rewards in the post-socialism period (primarily characterized by fostering of risk-taking behaviors), and more importantly the limited prospects to the poor for hedging against risks and uncertainty, partly inherent to their limited share of assets endowments. Returns to higher education increased significantly during most of the transition 12 Latvia ranked third; Hungary and Estonia were the only two countries in the sample with higher contribution of salaries and wages to overall income inequality. Other key components of income inequality in Latvia include selfemployment and state transfers, which account for over 22% and 5% of total income inequality, respectively.

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