For example, focusing on Malawi,<sup>40</sup> wealth inequality is roughly 1.5 larger than income inequality (in terms of variance of the logs) in rural areas and roughly 3 times larger in urban areas. Further, there is certainly much more wealth inequality in urban than in rural areas, by a factor of 3 (i.e., a larger factorial rural-urban difference than that of income inequality, 1.6), suggesting a stronger ability to accumulate wealth, and hence, to create dispersion in urban areas than in rural areas.<sup>41</sup> Comparing our results with US inequality, we find that income dispersion does not transmit as much into wealth dispersion in SSA as it does in the United States. Precisely, in terms of household income, the United States has a log variance of 0.99 for the year 2010, as reported in D ́ıaz-Gim ́enez et al. (2011) using the Federal Reserve’s Survey of Consumer Finances, while the variance of logs for urban income for Malawi, Tanzania, and Uganda is, respectively, 1.60, 1.90, and 2.01. That is, urban income inequality is larger in SSA than in the United States. In contrast, in terms of wealth the United States has a log variance of 4.53, which is surprisingly similar to the inequality measures of urban Malawi, Tanzania, and Uganda, respectively, 4.52, 4.44, and 4.67. That is, using urban Malawi as a benchmark, the Unites States is able to generate the same amount of wealth dispersion as urban Malawi with about 60% of its income dispersion. This lower transmission from income to wealth inequality in urban SSA compared with the United States is also present in rural SSA. For example, rural Malawi has income inequality similar to that in the United States, with a variance of logs of 0.99, while wealth inequality in rural Malawi is 1.49: one-third of the US wealth inequality. That is, with the same income dispersion as rural Malawi, the United States is able to generate three times the wealth dispersion of rural Malawi. Similar relations are attained for Tanzania and Uganda.<sup>42</sup> To summarize, the inability of income dispersion in SSA, which is at least as large as that of the United States, to translate into wealth dispersion as large as that of the United States, points to an inherent inability to save and accumulate wealth in both urban and, more so, rural SSA. Moreover, despite this evidence on a lesser ability to save, we find that consumption inequality is 49% and 37% of income inequality (in terms of the variance in logs) in rural and urban Malawi, while this figure is larger and close to 55% in the United States (Blundell et al. (2008)).<sup>43</sup> Combining these two dimensions suggests that the greater ability to contain the

> 40In terms of wealth (i.e., net worth), we focus on Malawi because Tanzania lacks housing and other durables data and Uganda debt data.

> 41Since most of the variation in wealth in rural areas comes from land (roughly 80%), this suggests that either land cannot be accumulated (or create wealth dispersion) in rural areas or rural households do not have access to the accumulation of other types of assets.

> 42 Similar insights are obtained from alternative measures of inequality such as the Gini index, mean to median ratios, and 90th/10th percentile ratios, also reported in Table 3.

> 43These figures are 34% and 33%, respectively, for rural and urban Tanzania and 50% and 52%, respectively, for rural and urban Uganda. For the United States, we use the reported average from the mid-1980s to the early 1990s in Blundell et al. (2008).

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