that using imputed rent for subsidized tenants reduces the percentage of population living below the poverty line in all the predominantly urban regions of Egypt. In the Metropolitan region, the adjusted poverty rate is 12.1 (1.2 percentage points lower than the original rate), whereas the Lower Urban and Upper Urban regions experience only minor changes ( **Table 6** ). Naturally, the decreases in the incidence of poverty are starker if we only look at the Old‐law tenants group. Comparing columns [3] and [4] in **Table 6** the poverty rate is 6 percentage points lower in the Metropolitan area among Old‐law renters once the adjustment is incorporated into the poverty estimation methodology. Put another way, there appears to be an overestimation of poverty among this group. In the Lower Urban region poverty rate was overestimated by 7.7 percentage points and in Upper Urban by 6.7 percentage points.

**Table 6. Poverty rates (% population living below the poverty line)**

|**Region**|**Poverty among**<br>**OLD‐law tenants**|**Poverty among OLD‐**<br>**law tenants(adjusted)**|**Poverty**<br>**rate**|**Poverty rate**<br>**_(adjusted)_**|
|---|---|---|---|---|
|Metropolitan|16.5|10.5|13.3|12.1|
|Lower Urban|17.4|9.7|10.6|9.9|
|Lower Rural|15.6|12.0|16.1|16.3|
|Upper Urban|22.6|15.9|24.8|23.9|
|Upper Rural|46.5|46.7|46.7|46.9|
|_National_|19.3|13.3|24.4|24.1|

Source: Own calculations using HIECS, 2012/13 Notes: National rate includes Border regions.

Another aspect of welfare that will be affected by the adjustments described will be the level of inequality in Egypt. Previous studies have discussed the issue of inequality in Egypt. In short, given its level of development, Egypt’s inequality indexes are typically lower than expected. The HIECS 2012/13 showed a Gini coefficient of 29.7. This level is the second lowest in a selection of countries in the MENA region ( **Figure 3** ). Tests have been carried out to ex‐post correct for potential issues of unit non‐response, or by modeling the effects of the missing top incomes by using Pareto distributions ( **Hlasny and Verme, 2013** ). There is no suggestive evidence of significant differences once these corrections were implemented. In contrast, one study ( **van der Weide et al. 2016** ) used data on housing prices to simulate the top tail of the income distribution and obtain a corrected inequality measure for the country’s urban areas.<sup>14</sup> Using data from 2008/09, the authors find that the Gini is substantially underestimated. The Gini index for Urban Egypt is found to be 47 instead of 36.4 when no correction is made. These studies, as many others that use the total consumption expenditure as obtained from the Household Survey HIECS have overlooked the potential effects of the regulatory framework of Egypt. The differences in valuation of rents and non‐ comparability across households may have important implications on the distribution of welfare as used and the estimated impact of the studies’ corrections.

> 14 Other studies have used administrative or tax data to correct for the top incomes that are typically missing in household surveys (see Diaz‐Basan 2014 or Morelli et al 2015 for instance). In Egypt, tax records are unavailable.

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