<mark>We match households that are similar in a set of individual‐ and household‐level covariates, including per capita family income, proportion of females in the household, education of the principal applicant, marital status of the principal applicant, the presence of elderly or disabled people in the household, and whether the household receives income from employment or remittances.</mark><sup>26</sup> <mark>We find a good match for approximately 34,000 households in the database.</mark><sup>27</sup> <mark>We proceed with the analysis by estimating equation</mark> (1) using the matched sample, adding a dummy for female principal applicant.

<mark>Table 7 shows the results of two models for each poverty outcome; the difference between the models is that the number of adult men is included as an additional control in columns (2), (4), and (6) but is not included as a regressor in columns (1), (3), and (5). Columns (1) and (3) of Table 7 show that before UNHCR assistance, female principal applicants who are like male applicants in terms of education, household composition, marital status, and income sources are more likely to be poor than male principal applicant households, even after controlling for family type, household size, and a number of other characteristics that affect vulnerability to poverty. However, once the number of adult males in the household is controlled for, the association of greater poverty with female principal applicants disappears—columns (2) and (4). After UNHCR assistance is received—columns (5) and (6)—households with female principal applicants are no longer more likely to be poor and the number of adult males in a household has no</mark> significant impact on the likelihood of poverty either.

<mark>Other research suggests that the ability to work informally or use networks to access economic opportunities, including negotiating housing rent or prices of other important expenditures, are possible reasons why having more adult men can help keep households out of poverty (World Bank, 2016; ODI UNICEF and UNHCR, 2017). However, while on average male principal applicant households have more</mark> than one adult male, female principal applicant households have less than one adult male.

<mark>Our results suggest that assistance is well targeted in terms of providing resources needed to lift female principal applicant households above the poverty line as after assistance the association between female principal applicants and a greater likelihood of poverty disappears. The impact of having more adult males in the household on the likelihood of poverty is also offset by the assistance. Thus, controlling for difference in observable characteristics between male and female principal applicant households, female principal applicant households are no more likely to be poor than their male counterparts after UNHCR assistance.</mark>

> 26 Although the use of more covariates guarantees a successful matching, it reduces the probability of finding observations on the common support. This is known as the dimensionality paradox (Guo and Fraser 2015). Given the large set of households that the dataset surveyed, we had more room for flexibility on this aspect. Out of 53,320 observations, 9,058 were of the common support.

> 27 The density function of the matched male principal applicant households resembles the density function of female principal applicant households, as confirmed by the balancing test, which shows a reduction of 100 percent in the differences between the matched households across all covariates. (See Appendix 2)

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