The values of consumption aggregates for households who did not participate in the survey were simulated using the _Pareto distribution_ assumption. Let _xm_ be equal to the highest consumption per capita in the data (i.e., the consumption per capita for missing households is equal to or greater than the highest consumption per capita in the existing HIES data). Also assume that k (shape parameter) is equal to 2. We test hypothesis 2 by calculating consumption inequality after accounting for upper truncation in the distribution as described above. Similarly Hypothesis 3 can be tested by calculating consumption inequality after accounting for lower truncation in the distribution. For hypothesis 3, consumption per capita for missing households, which are now assumed to be the poorest, was assumed to be equal to or less than the lowest consumption per capita in the existing HIES data.

The likelihood that exclusion of households in the lower wealth echelon had led to lower inequality is very low. Table 9 presents the Gini coefficients and Figure 3 presents percent changes in them under hypotheses 2 and 3. The Gini coefficient does not exhibit appreciable increase with the assumption that the missing households were in the bottom wealth distribution. On other hand, the assumption of upper truncation (i.e., the missing households belong to the wealthiest upper echelon) appears to contribute to apparent low inequality. For example, accounting for exclusion of rich households in the data will lead to over 120 percent increase in Gini coefficient in 2002 (from 0.184 to 0.412). The impact of upper truncation is even higher in non-Baku urban areas, where the Gini coefficient would increase by close 150 percent (0. 172 to 0.432) in 2002 (Figure 4). The Gini coefficients would also increase appreciably in 2003 and 2004 after accounting for the missing households. Note that the effect of lower truncation is extremely low compared to the assumption of upper truncation.

Therefore, the most likely factor for the observed low inequality in the Azerbaijan HIES data appears to be the under-representation of households in the higher income brackets. This is likely so due to inadequate participation of the richer households in the surveys. However, the inequality figures after accounting for top truncation are still too low to be credible for Azerbaijan, particularly for 2003 and 2004. This suggests the most credible source of lower inequality may be the combination of both lack of participation of rich households and the transfers. This possibility is tested under hypothesis 5 below.

**Table** **<u>9.</u>** Lack of participation of rich households <u>partly explains low inequality in Azerbaijan</u>

|**Gini Coefficients**|**200**<br>|**2**<br>|**200**<br>|**3**<br>|**20**<br>|**04 **<br>|
|---|---|---|---|---|---|---|
||**Top**<br>**Truncation **|**Bottom**<br>**Truncation **|**Top**<br>**Truncation **|**Bottom**<br>**Truncation **|**Top**<br>**Truncation **|**Bottom**<br>**Truncation **|
|Azerbaijan|41.2|18.4|28|20.4|32.4|18.4|
|Baku|43.2|23.2|34.8|23.9|37.7|20.9|
|Non-Baku urban|43.3|26.5|26.9|20.3|33.3|17.9|
|Rural|38.2|22.9|22.8|18.1|26.6|16.5|

Source: Azerbaijan HIES data.

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