# **Appendix: Robustness Checks**

We include three robustness checks on our main estimates of African inequality. First, we restrict the sample to those countries that are present in both 1993 and 2008. Second, we use the raw data set of decile groups without the imputation of a parametric Lorenz curve. Third, we check for the robustness to using the older set of PPP exchange rates for 2005. Table A1 summarizes the robustness checks on the inequality results which were already discussed in the main text. Below, we will discuss the results with the 2005 PPPs in more detail.

|||<br>**Table A1**|**: Africa**|<br>**n inequal**|**ity**||||
|---|---|---|---|---|---|---|---|---|
||**1993**|**change**<br>**(%, pp)**|**1998**|**change**<br>**(%, pp)**|**2003**|**change**<br>**(%, pp)**|**2008**|**1993‐2008**<br>**change (%, pp)**|
|**i. Regional inequality (from Tab**|**le 3)**||||||||
|**Gini index (%)**|51.68|0.92|52.16|3.78|54.13|3.69|56.12|8.59|
|**GE(0) (Theil‐L)**|0.47|0.16|0.47|8.21|0.51|10.74|0.57|20.02|
|**GE(0) within contribution (%)**|73.41|‐2.11|71.29|‐7.03|64.26|‐4.57|59.69|‐13.72|
|**ii. Regional inequality‐ Deciles**|||||||||
|**Gini index (%)**|51.08|1.04|51.62|3.91|53.63|3.66|55.59|8.83|
|**GE(0) (Theil‐L)**|0.46|0.17|0.46|8.60|0.50|10.98|0.55|20.73|
|**GE(0) within contribution (%)**|72.65|‐2.17|70.48|‐7.10|63.38|‐4.59|58.79|‐13.86|
|**iii. Regional inequality‐ 2005 PP**<br>|**P‐adjus**|**ted USD**|||||||
|**Gini index (%)**|52.25|0.15|52.33|6.66|55.82|1.79|56.82|8.74|
|**GE(0) (Theil‐L)**|0.48|‐1.45|0.48|14.77|0.55|5.05|0.57|18.81|
|**GE(0) within contribution (%)**|71.58|‐0.92|70.66|‐10.61|60.05|‐1.25|58.80|‐12.78|
|<br>**iv. Regional inequality‐ Balance**|**d sampl**|**e**|||||||
|**Gini index (%)**|53.46|1.00|53.99|9.43|59.08|‐4.04|56.69|6.05|
|**GE(0) (Theil‐L)**|0.51|‐0.92|0.51|22.02|0.62|‐9.02|0.56|10.00|
|**GE(0) within contribution (%)**<br>_Notes: For the decompositions by co_<br>_are measured in percent (not annual_<br>_per country‐year, based in part on a_|72.30<br>_untry, cha_<br>_ised). Obs_<br>_parametri_|‐1.90<br>_nges betwee_<br>_ervations ar_<br>_c Lorenz cur_|70.40<br>_n benchm_<br>_e weighte_<br>_ve._|‐9.91<br>_ark years ar_<br>_d using pop_|60.49<br>_e in perce_<br>_ulation. U_|1.68<br>_ntage points_<br>_sing dataset_|62.17<br>_. For all o_<br>_of 100 pe_|‐10.14<br>_ther rows, changes_<br>_rcentile groups_|

New PPP exchange rates become available periodically, reflecting new collections of international price data. Recently, the World Bank adopted the 2011 PPP exchange rates for its measurement of global poverty. Ferreira et al. (2015) provide a detailed explanation of how the World Bank adopted these new PPP exchange rates, and in particular how the international poverty line was updated. The changes for the global extreme poverty headcount have been small. For example, in 2011, the global poverty rate falls from 14.5% to 14.1% when moving from the 2005 PPPs (with a poverty line of $1.25) to the 2011 PPPs (with a poverty line of $1.90).

According to Table A1, the revision of the PPP exchange rates only had a small effect on the level of regional inequality. But it could potentially lead to a re-ranking of countries, even though these effects cancel out in the aggregate. With the GE(0) inequality measure, African inequality consists of three components (see the formula in footnote 32): (1) a country’s population size; (2) its level of inequality; and (3) its position in the African distribution captured by the country mean. Because of a substantial change in relative price levels (Ferreira et al., 2015), the change to 2011 PPPs 25