Next, we analyze poverty rates by demographic category and by displacement status (Table 10). In Ethiopia, the monetary measure shows evidence of large differences in poverty rates between refugees and the host community. For example, while 63% of refugee households with a female household head are monetary poor, only 7% of the female-headed households in the host community are identified as poor by the $1.90 a day measure. This gap between the refugee community and the host community is also large among households headed by men. When turning to the multidimensional measure, a similar pattern emerges, with 55% of refugees in female-headed households being poor in Ethiopia, while only 14% are poor using the multidimensional measure in the host community. These results are consistent in Nigeria among male household heads. Among female household heads, we find no differences between IDPs and non-IDPs using the monetary poverty measure; however, there is a sizable gap between these two groups when using the MPI.

To explore the role of possible disruptions to family structures as part of the displacement, Table 10 also presents descriptive analysis by _de jure_ and _de facto_ head. We find that regardless of the type of female head, IDP households are significantly more likely to be classified as poor according to both the monetary and the multidimensional measures. Another striking finding is that _de facto_ headed households are more likely to be monetary and multidimensionally poor in Ethiopia, while the opposite is the case in Nigeria.

The legal environment, as well as the disproportionate role in caring and housework responsibilities, may act as a disadvantage for households with a relatively larger number of women contributing to the household income. The third set of poverty rates shown in Table 10 explores this hypothesis. In Ethiopia, for example, households where women are contributing more to the household income and those with no earners are the most vulnerable groups in both the refugee and the host community. This pattern is consistent using both measures of poverty. On the other hand, households where most earners are male and where the primary income source is remittances are less likely to be poor, especially among refugees.

Overall, monetary poverty and multidimensional poverty identify different households as poor. In spite of these salient differences, people living in refugee/IDP households are consistently poorer according to both the monetary and the multidimensional poverty measures. When we compare the rankings of the population subgroups according to each measure, we find that households with a single female earner or no earners are consistently identified as poorer according to each of the measures.

_Table 10. Poverty by demographic characteristics for Ethiopia and Nigeria_

|Panel A.Ethiopia|%<br>Refugee|of monetary poo<br>Host<br>Community|r<br>All|% of m<br>Refugee|ultidimension<br>Host<br>Community|a|l poor<br>All|
|---|---|---|---|---|---|---|---|
|Female hhh|63%|7%|58%|55%|14%||53%|
|Male hhh|49%|20%|38%|18%|10%||17%|
|De jure female hh|47%|17%|39%|34%|11%||32%|
|De facto female hh|68%|19%|66%|61%|17%||60%|

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