POVERTY-SPECIFIC PURCHASING POWER PARITIES (PPPs) IN AFRICA CPD method in its unweighted form. For comparison purposes all basic heading PPPs were then aggregated to the level of household consumption using the GEKS-Fisher procedure.

Depending on the reduced-list scenario, the removal of items was contained to either the “food and non-alcoholic beverages” or the “clothing and footwear” ICP expenditure categories. These two categories were chosen because of their importance as basic necessities as well as for practical reasons. It turns out that the product dataset for the 2011 ICP Africa comparison contains quite detailed and harmonized metadata for items belonging to both categories.

Determining what items to remove in each reduced-list scenario was not without its problems. At first, it would seem that the main difficulty lies in the circularity of the task at hand: it is necessary to consistently identify the poor in each country before assessing what items they consume. Yet, while the circularity is indeed an obstacle, it can be solved using the iterative procedure employed in Section 4. Instead, the lack of item-level detail in most of the household expenditure surveys proved to be the more intractable problem is. On this front, we mined the micro data from household expenditure surveys in 28 Sub-Saharan Africa countries and concluded that their item-level detail is generally insufficient to properly distinguish item-varieties and establish a one-to-one mapping with ICP items.

Given this constraint, we chose the practical alternative of using information from the ICP product data set for Africa mentioned above to identify items that one would expect to be outside the consumption basket of the poor. To identify items priced only in supermarkets we used information from the “required outlet type” field provided for each item. In the case of garments and footwear, we stratified items within the “garments” and “shoes and other footwear” basic headings as branded or unbranded by exploiting the available item-level brand stratum information ( _high_ , _medium_ , or _low_ ). As stated earlier, we grouped and labeled all _high_ and _medium_ garments and footwear as branded for brevity even if some _low_ items also include some brand specification. Lastly, for the premium food and nonalcoholic beverages scenario we removed items with a relatively high (per-unit) price across all countries within each basic heading, and assume a linear relationship between quantity and prices for each item.

We must underline that all three approaches are not without their drawbacks, but we cannot do any better given the current set of data. Nevertheless, market consumer reports by Nielsen (2014) and information from the Food and Agriculture Organization (2015) indicate that the poor in many African countries rarely shop in supermarkets. Likewise, it is not unreasonable to assume that high brand stratum garments and clothing are outside the scope of what the poor consume, at least on average.

# _5.2 Poverty-specific PPPs by reduced-list scenario_

To measure the effect of moving from PPPs based on a full-list to PPPs based on a reduced-list, we compute the SD across (normalized) relative differences in country PPPs due to the shift.<sup>14</sup> These relative difference in PPPs are captured by the ratio between a country’s reduced-list PPP and its full-list PPP (“PPP ratio”).<sup>15</sup> The SDs of the normalized PPP ratios in each scenario are presented in Table 2, while country PPP ratios by reduced-list scenario are available in Table A5 (annex).

TABLE 2 — EFFECT OF REMOVING ITEMS ( _BY REDUCED-LIST SCENARIO_ <u>), 50 COUNTRIES</u>

|Reduced-list (poverty-specific) scenario|SD of normalized<br>PPP ratios|
|---|---|
|(1) Removing supermarket only items|0.88 %|
|(2) Removing branded garments & footwear items|0.29 %|
|(3)Removing _premium_food & nonalcoholic beverages items|0.73%|

_Source_ : Authors’ calculations

> 14 All PPP ratios presented are based on normalized country PPPs with respect to the regional geometric mean. This normalization procedure removes the base-country effect that would occur otherwise.

> 15 A PPP ratio greater (less) than 1.00 denotes an increase (decrease) in country PPP, relative to the region, due to the shift from a fulllist to a reduced-list.

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