The share of the poor that work outside agriculture, that are children, and have no formal education are all noticeably lower in the fixed samples **.** For example, the share of the poor working outside agriculture drops 3.3 percentage points, from 35.4 to 32.1, when limiting to observations where urban/rural and education are non-missing. The share of the poor under the age of 15 drops by 3.3 percentage points in the first fixed sample, because the sample differentially excludes poor children that did not report educational attainment. The proportion of poor adults with no schooling decreases 12 percentage points from 43.7 percent to 31.5 percent in the second fixed sample, which excludes all children and non-working adults. This sensitivity indicates that the pattern of missing variables is not independent across variables. Conducting the analysis on a fixed subsample for which all data are present would therefore distort the findings.<sup>34</sup>

# **5. Conclusions**

Using harmonized household data from 89 countries, this paper provides an overarching demographic profile of the global extreme poor and moderate poor in 2013, shedding light on where they live and who they are, and the extent to which they work in the agricultural sector. Not only is this the most updated and most comprehensive profile of the poor in terms of global coverage, but the analysis breaks new ground by examining the characteristics of the moderate poor, and presenting conditional correlations between demographic variables and household welfare. Five main conclusions emerge.

First, both the extreme and moderate poor are rural and young, and mostly live in larger households with more children. More than four in five of the extreme poor live in rural areas, which is slightly more than previously thought. Moreover, 44 percent of the extreme poor are children under 15, and households with three or more children comprise nearly 60 percent of the extreme poor. The prevalence of child poverty raises the prospect of long-term consequences on the physical and intellectual development of poor children, which could in turn impede their future earning capacity. The gender gap in poverty is not apparent in traditional poverty measures, because poverty is measured based on household per capita welfare, whereas gender disparities are most apparent in individual-level indicators such as education, decision making power and labor market outcomes. Male headed households, however, are disproportionately likely to be poor, at least in the lower middle-income countries that contain the majority of the extreme poor. In general, these findings emphasize the potential benefits of programs that directly or indirectly support children, large households, and rural households, as well as indirect measures to reduce the future incidence of child poverty.

Shifting out of low productivity agricultural work, while important, is not sufficient to escape poverty. Consistent with the clustering of the poor in rural areas, poor workers are much more likely than non-poor workers to make their living from agricultural work. Yet a substantial proportion of the extreme and moderate poor who live in rural areas – 24 and 40 percent, respectively – work outside the agricultural sector. Within the scope of this study, it is unclear why

> 34 Multiple imputation methods, which can address problems created by non-random patterns of missing survey data, can be explored in the future (Rubin, 2004).

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