Squire,1998; Ravallion and Chen,1997).<sup>5</sup> To sum up: a 1 percent growth in mean consumption brings about a 3 percent reduction in the headcount poverty rate which is equal to about 0.5 percent of the total population or (multiplying by 38.2 million) 185,000 people. Given the relatively high degree of elasticity and the optimistic predictions for growth in 2004, the prospects for poverty reduction in Poland are good. Assuming inequality to increase at the average rate experienced over the last five years, poverty should fall by 6.4 percent, lowering it by 1.5 percentage points to 15.1 percent in 2004 (see table 1).

# **But Inequality Matters, Too**

However, inequality also rose steadily through the second half of the 1990s (see Figure 4). In 2002 the Gini coefficient for consumption inequality was 0.28, which was moderately high compared to other CEE countries (see, for example, World Bank, 2000 and 2002). Given the formerly centrally planned economic systems in CEE countries and their subsequent economic development, it is not surprising that growth is associated with rising inequality. In general, however, CEE countries constitute an outlier in the overall picture – any simple universal link between growth and inequality has been flatly rejected by recent studies (see, for example, Ravallion and Chen, 1997).

**Figure 4:  Inequality, 1994-2002**

<!-- Start of picture text --> 0.29 Gini coeff, LHS 0.14<br>0.28 Mean log deviation, 0.13<br>0.27 RHS 0.12<br>0.26<br>0.11<br>0.25<br>0.10<br>0.24<br>0.09<br>0.23<br>0.22 0.08<br>0.21 0.07<br>0.20 0.06<br>Source: Household budget survey<br>1994 1995 1996 1997 1998 1999 2000 2001 2002<br><!-- End of picture text --> Table 2 decomposes the overall inequality – measured by the Theil mean log deviation index - into two components: (i) differences between groups and (ii) within group inequalities. The focus is on variations within (and between) (i) regional groups (96 groups = 16 voivodships crossed with 6 town sizes), (ii) educational groups (3 groups: higher, secondary, other) and (iii) age categories. If, for example, mean consumption was the same for all regions (i.e., the region variation was 0), then the numbers in the respective row in the table would be 0 and all inequality could be entirely attributed to inequalities within each region. Analogously, if everyone within a given region had equal consumption (i.e., within-region variation was zero) but regions differed in mean consumption, the “between” inequality component would be 100 percent. The table shows that inequality caused by variation within groups is the main component of total inequality for all groups analyzed. However, differences between different educational groups are significant and growing component of overall inequality and are differences between different regions. On the other hand, differences across different age groups were and remain minimal.

Thus, regional inequalities clearly increased during 1994-2002, not only in absolute terms<sup>6</sup> but also in relative terms. Or, equivalently, regional inequalities rose even more than total inequalities and the role of regional inequalities in overall inequality increased. The increase in the primary education was an even more substantial signifer rising inequality.

> 5 Just to give few examples, the growth elasticity of poverty for Romania was estimated at 3 in 1996 and 1997 but has declined since than to below 2 (World Bank, 2003). An average elasticity of 3.7 was also estimated for Croatia (World Bank ,2002). However, the limited information available suggests much lower responsiveness  in other countries. Estimates of around 2 were derived for Russia (World Bank, 2002) and less than 1 for Armenia, Azerbaijan and the Kyrgyz Republic (World Bank, 2003).

> 6 See Chapter 3 of Poland Living Standard Assessment, World Bank (2004) for a discussion of regional poverty and prices

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