A Unified Approach to Measuring Poverty and Inequality
percentage contribution of the subnational regions to the overall squared gap measure. Columns G, H, and I depict the population distribution of the subnational regions, or the percentage of the overall population that resides in each region. Row 11 shows that the overall squared gap measure increased from 4.6 in 2003 [11,A] to 4.8 in 2006 [11,B], reflecting a 0.2 point increase [11,C]. The squared gap measure for Kakheti is 6.6 in 2003 [1,A]. The squared gap measure for the same population subgroup is 9.4 in 2006 [1,B]. Thus, the squared gap measure increased by 2.7 points in three years [1,C]. The squared gap measure in Kvemo Kartli decreased by 1.7 points, from 7.8 in 2003 [4,A] to 6.2 in 2006 [4,B]. The squared gap measure also fell between 2003 and 2006 in other regions, such as Samegrelo [8,C] and MtskhetaMtianeti [10,C]. Kakheti’s contribution to the overall squared gap measure in 2003 is 14.0 percent [1,D]. The contribution increased to 18.2 percent in 2006 [1,E], an increase of 4.2 percentage points [1,F]. Lessons for Policy Makers Comparing the contribution of subnational regions to the overall squared gap measure to the contribution to the overall squared gap measure and the share of poor in each region, we see they are not necessarily the same. Tbilisi’s contribution to overall poverty in 2006 is larger than Kakheti’s contribution when poverty is measured by headcount ratio and poverty gap measure, but Tbilisi’s contribution is lower in 2006 (3.0 [2,B]) than that of Kakheti (9.4 [1,B]) when poverty is measured using the squared gap measure. This finding may reflect that inequality across the poor, captured by the squared normalized shortfalls, is much higher in Kakheti, and that is not captured by the analysis based on headcount ratio or poverty gap measure. Quantile Incomes and Quantile Ratios In addition to analyzing poverty, understanding how a population’s poor segment compares to the rest of the population is important. Table 3.12 reports quantile per capita expenditure for five percentiles and certain quantile ratios of per capita consumption expenditure for Georgia’s subnational regions in 2003. Each of the first five columns denotes a quantile PCE. Column A denotes the quantile PCE at the 10th percentile, column
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