in 1993, because the availability of household surveys in Africa is more limited before this date.<sup>7</sup> Given the lags in data preparation, we were also unable to add another more recent benchmark year beyond 2008.<sup>8</sup> We have established two rules for allocating surveys to benchmark years (similar to Lakner and Milanovic 2015): (1) surveys need to be within two years of a benchmark year, and (2) surveys in consecutive benchmark years should be at least three and no more than seven years apart from each other. However, we had to make a few exceptions to ensure that the household surveys included in our database achieve a sufficient coverage of the African population.<sup>9</sup> PovcalNet provides the average incomes of the 10 decile groups within a country, but it does not provide more detailed information on the distribution in its main output.<sup>10</sup> We have constructed two versions of the database. First, we only use the raw data available in PovcalNet and construct a data set consisting of country decile groups. Second, we fit a parametric Lorenz curve to the decile groups and build a data set of percentile groups (for each country-year).<sup>11</sup> The second data set has the advantage of providing more detail on the country-level distributions, but this comes at the cost of requiring an additional parametric assumption. Our main set of results uses the data set of percentile groups but we present robustness checks using the more aggregated data. For the three surveys where we use survey data directly, we can of course construct percentile (or decile) groups directly. In the analysis, each quantile group is population-weighted, so every person is assigned the average per capita consumption expenditure of her quantile group in the country-year distribution.

Throughout, welfare is measured using per capita consumption expenditure, measured at the household level and expressed in 2011 PPP-adjusted USD.<sup>12</sup> This new set of PPP exchange rates was recently adopted by the World Bank in its global poverty measurement (Ferreira et al., 2015).<sup>13</sup> 7 Using a somewhat broader data set, Lakner and Milanovic (2015) covered only 29% of the population in Sub-Saharan Africa in 1988.

> 8 Chotikapanich et al. (2015) present annual estimates of the Gini and poverty headcounts for a number of African countries up to 2010. Similarly, Pinkovskiy and Sala-i-Martin (2014) calculate estimates for regional poverty and inequality up to 2011. However, their methods rely on using GDP per capita for the country mean (which is available for recent years), and extrapolating and interpolating distributional information (for which there is a longer time lag). 9 Violating the first rule, we use the 2005-2006 survey in South Africa for benchmark year 2003. This survey was largely conducted in 2006, so should be allocated to benchmark year 2008. We use four surveys (from Guinea-Bissau, Kenya, Nigeria and Tanzania) which are eight years apart from the survey in the previous benchmark year. We annualize growth rates when we estimate changes between benchmark years to account for growth spells of varying lengths.

> 10 To be precise, PovcalNet provides the overall mean and the consumption share of each decile group from which it is straightforward to construct the average income of the decile group.

11 We fit a lognormal Lorenz curve to the ten decile groups and use it to generate a distribution of 10,000 points. We use the ‘ungroup’ Stata routine (Abdelkrim and Duclos, 2007) which implements the Shorrocks and Wan (2008) method. As described in more detail in Lakner et al. (2014), this is very similar to the approach used by PovcalNet in the measurement of global poverty. Our approach differs from other papers in this field which assume parametric within-country distribution functions (e.g. Chotikapanich et al. 2012). According to Minoiu and Reddy (2012), it is preferable to fit a parametric Lorenz curve instead of a kernel density.

> 12 PovcalNet reports per capita household consumption which ignores any economies of scale in household consumption. It could be argued that poor people have little scope for economies of scale (Chen and Ravallion, 2010). 13 At the time of extracting the data used in this paper, PovcalNet used the 2005 PPP exchange rates. Our conversion into 2011 PPP-adjusted USD is consistent with PovcalNet and is given by Lakner and Milanovic (2015) and Jolliffe and Prydz (2015) as

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