For the additional data we obtain directly from household surveys, we replicate the approach followed by PovcalNet: First, we use the local CPI (from PovcalNet and World Development Indicators (WDI)) to deflate consumption to 2011 domestic prices, and (2) apply the 2011 PPP conversion factors for private consumption (also from WDI) to convert into 2011 PPP-adjusted USD. In the Appendix, we perform a robustness check of our main results using the 2005 PPP exchange rates.<sup>14</sup> It is appropriate to use consumption expenditure as the welfare indicator, as it can be measured more easily than income in low-income countries (Deaton and Zaidi, 2002), such as Sub-Saharan Africa. However, it is important to recognize that relative to income surveys, consumption surveys tend to show lower levels and slower increases in inequality. For example, this can be explained by a declining marginal propensity to consume, and difficulties in capturing expenditures on the types of items consumed at the top end of the distribution.<sup>15</sup> Therefore, if incomes at the top increase faster than in the rest of the distribution, consumption surveys would register this increase in inequality only to a limited extent.

# **III. Summary Statistics**

Table 1 shows the main summary statistics of our database of national household surveys. Our database includes around 25 surveys per benchmark year out of a total of 48 African countries. Most surveys lie within one year of their respective benchmark year. Given our interest in estimating the African distribution of consumption expenditure, it is important that the surveys included in our database cover as much of the region as possible. On average, we cover 80% of regional GDP, and at 72% a somewhat lower share of the regional population.<sup>16</sup> Given that richer countries are more likely to have a survey that can be included in our database, it is not surprising that the GDP coverage exceeds the population coverage. This can also be seen very clearly when we break down the GDP and population coverage by country income status.<sup>17</sup> For example, in 2008 our database covers 97% of the population of the upper middle and high income countries in Africa, compared with 61% for low income countries.

> , where ������� is the CPI in 2011, ���11 is the PPP conversion factor in 2011, and the 2005 terms are defined accordingly.

> 14 For South Sudan we add a 2009 survey directly from household surveys. While the conversion into 2011 PPPs is straightforward, expressing the welfare aggregate in 2005 PPPs is more difficult because national accounts aggregates do not exist separately for Sudan and South Sudan before 2008. Therefore, for the period between 2005 and 2008 we use Sudan’s inflation rate, as well as its 2005 PPP exchange rate.

> 15 This problem is not unique to developing countries. Recently Aguiar and Bils (2015) use the relative expenditure by high- and low-income households on luxuries to show that US consumption inequality is underestimated in the Consumer Expenditure Survey.

> 16 The coverage of Sub-Saharan Africa is very similar in Lakner and Milanovic (2015) who use a somewhat broader set of surveys. On average, they cover 80% of regional GDP and 74% of regional population between 1993 and 2008. 17 Income status as defined by the World Bank Analytical Classification in 2014 (last updated on 1 July 2014). This 2014 classification is based on estimates of gross national income (GNI) per capita for 2013.

5