**Note** : The official methodology is run based on total expenditures.

Next, we contrast the poverty trends associated with the three different measures. We investigate whether these trends are very different, and which of the two alternative measures yields results that are closest to the official measure.

Table 11 shows the trends associated with the three different methodologies for the period 2015 to 2017/18 for all regions. The trend at the national level provides a goods summary of the messages of this table. At national level, our estimate of the official poverty rate increase over the period is 6 percentage points (while the estimate by CAPMAS suggests an increase slightly below 5 percentage points). This increase is halfway between the larger increase captured by the purely absolute measure (10 percentage points) and that captured by the purely relative measure (1 percentage point). In fact, the increase captured by the purely absolute measure corresponds to the effect of the change in real total expenditures computed when decomposing the trend in the official measure, which is shown in the last column. The comparisons in each region yield a very consistent picture with that observed at national level. We also note that the relative measure changed little over the period, which suggests that intraregion inequalities do not radically change over this interval.

_Table 11: Comparison of trends for the three methodologies from 2015 to 2017/18_

||Offici|al||Absol|ute||Relati|ve||Δ<br>total<br>expenditure<br>effect|
|---|---|---|---|---|---|---|---|---|---|---|
||2017<br>/18|2015|Δ<br>2017/18<br>-2015|2017<br>/18|2015|Δ<br>2017/18<br>-2015|2017<br>/18|2015|Δ<br>2017/18<br>-2015|Δ 2017/18-<br>2015|
|National|31%|25%|6%|34%|25%|10%|25%|25%|1%|10%|
|Metropolitan|25%|11%|14%|25%|13%|12%|29%|28%|2%|14%|
|<br>Lower Urban|13%|10%|4%|19%|10%|9%|25%|24%|2%|7%|
|Poverty<br>rate<br>Lower Rural|26%|17%|8%|31%|17%|14%|23%|24%|-1%|15%|
|<br>Upper Urban|28%|24%|4%|32%|23%|9%|26%|25%|2%|8%|
|Upper Rural|52%|55%|-3%|53%|52%|0%|24%|24%|0%|0%|
|Borders|42%|15%|27%|60%|18%|42%|30%|22%|8%|37%|

**Source** : Authors’ calculations based on HIECS 2015 and 2017/18. **Note** : The official methodology is run based on total expenditures.

# **Section 5: Concluding remarks**

Several countries rely on non-standard poverty measurement methodologies, which may complicate the interpretation of poverty changes across time or space. This paper focuses on one element, which is the use of non-standard poverty lines, particularly lines that are neither absolute nor relative. There is limited evidence on how these departures may impact the interpretation of poverty empirically, beyond obvious conceptual differences. This paper aims to fill this gap by looking at the case of Egypt. The analysis presented in this paper has provided several insights from comparing Egypt’s hybrid poverty lines with more standard lines.

The analysis first shows that consumption poverty increased in Egypt over the period 2015 to 2017/18, mostly due to the reduction in real consumption. The hybrid nature of the poverty lines inherent in the official poverty measurement methodology leads to a smaller increase in the poverty rate, compared to an approach where the poverty lines are updated in real terms. Yet, the profile of the poor has not been 17