metadata: authors: 0: author: AlAzzawi,Shireen
1: author: Dang,Hai-Anh H.
2: author: Hlasny,Vladimir
3: author: Abanokova,Ksenia
4: author: Behrman,Jere R.
count: Middle East and North Africa,World
docna: 0: docna: Female Headship and Poverty in the Arab
            Region: Analysis of Trends and Dynamics Based on a New Typology
docty: Policy Research Working Paper
abstracts: cdata!: Various challenges are thought to render
            female-headed households (FHHs) vulnerable to poverty in the
            Arab region. Yet, previous studies have had mixed results
            and the absence of household panel survey data hinders
            analysis of poverty dynamics. This paper addresses these
            challenges by proposing a novel typology of FHHs and
            analyzes synthetic panels constructed from 20 rounds of
            repeated cross-sectional surveys spanning the past two
            decades from the Arab Republic of Egypt, Iraq, Jordan,
            Mauritania, the West Bank and Gaza, and Tunisia. The paper
            finds that the definition of FHHs matters for measuring
            poverty levels and dynamics. Most types of FHHs are less
            poor than non&#x2013;FHHs on average, but FHHs with a
            major share of female adults are generally poorer. FHHs are
            more likely to escape poverty than households on average,
            but FHHs without children are the most likely to do so.
            While more children are generally associated with more
            poverty for FHHs, there is heterogeneity across countries in
            addition to heterogeneity across measures of FHHs. The
            findings provide useful inputs for social protection and
            employment programs aiming at reducing gender inequalities
            and poverty in the Arab region.
display_title: Female Headship and Poverty in the
            Arab Region: Analysis of Trends and Dynamics Based on a New Typology
listing_relative_url: /research/2024/01/34239758/female-headship-poverty-arab-region-analysis-trends-dynamics-based-new-typology
topicv3: Poverty m1326687 695,Gender and Human Development m1326908 919,Poverty Measurement and Analysis m1326941 707,Inequality and Shared Prosperity m1327655 700,Household Surveys m1504071 2761
publishtoextweb_dt: 2024-01-16T00:00:00Z
dois: 10.1596/1813-9450-10672
no_of_pages: 97
author_keys: 0: author_key: NA
1: author_key: 747967
2: author_key: 1253459
3: author_key: 1288641
4: author_key: 86114
model_extractions: Policy Research Working Paper 10672 Female Headship and Poverty in the Arab Region Analysis of Trends and Dynamics Based on a New Typology _Shireen AlAzzawi Hai-Anh Dang Vladimir Hlasny Kseniya Abanokova Jere Behrman_ Development Economics Development Data Group January 2024
Policy Research Working Paper 10672

# **Abstract**

Various challenges are thought to render female-headed households (FHHs) vulnerable to poverty in the Arab region. Yet, previous studies have had mixed results and the absence of household panel survey data hinders analysis of poverty dynamics. This paper addresses these challenges by proposing a novel typology of FHHs and analyzes synthetic panels constructed from 20 rounds of repeated cross-sectional surveys spanning the past two decades from the Arab Republic of Egypt, Iraq, Jordan, Mauritania, the West Bank and Gaza, and Tunisia. The paper finds that the definition of FHHs matters for measuring poverty levels and dynamics. Most types of FHHs are less poor than non– FHHs on average, but FHHs with a major share of female adults are generally poorer. FHHs are more likely to escape poverty than households on average, but FHHs without children are the most likely to do so. While more children are generally associated with more poverty for FHHs, there is heterogeneity across countries in addition to heterogeneity across measures of FHHs. The findings provide useful inputs for social protection and employment programs aiming at reducing gender inequalities and poverty in the Arab region.

This paper is a product of the Development Data Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at hdang@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Female Headship and Poverty in the Arab Region: Analysis of Trends and Dynamics Based on a New Typology**

Shireen AlAzzawi, Hai-Anh Dang, Vladimir Hlasny, Kseniya Abanokova, and Jere Behrman<sup>*</sup>

**Keywords** : poverty, feminization, female-headedness typology, synthetic panels, Arab region, household surveys

**JEL Codes** : I3, J16, N35, O1

> * AlAzzawi (salazzawi@scu.edu) is lecturer, Santa Clara University, Santa Clara CA, USA; Dang (hdang@worldbank.org; corresponding author) is senior economist, Living Standards Measurement Unit, Development Data Group, World Bank, USA and is also affiliated with IZA, Indiana University, and London School of Economics and Political Science; Hlasny (vhlasny@gmail.com) is economic affairs officer, UN ESCWA, Beirut, Lebanon; Abanokova (kabanokova@worldbank.org) economist, Living Standards Measurement Unit, Development Data Group, World Bank, USA; Behrman (jbehrman@econ.upenn.edu) is WR Kenan Jr Professor of Economics & Sociology, University of Pennsylvania, USA. We would like to thank Kathleen Beegle, Nazmul Chaudhury, Ebad Ebadi, Daniel Halim, Emily Hannum, Dean Jolliffe, Michael Kevane, Mahdi Majbouri, and participants at the American Economic Association meeting (New Orleans) and the Central Banks of the Middle East and North Africa's Annual Conference on Development Economics (Rabat) for helpful comments on an earlier draft. We would also like to thank the Chief Economist’s Office for the Middle East and North Africa (MNACE) for guidance and financial support and the UK Foreign Commonwealth and Development Office (FCDO) for additional funding assistance through the Data and Evidence for Tackling Extreme Poverty (DEEP) Research Program.
# **1. Introduction**

Are female-headed households (FHHs) in the Arab region more likely to be poor, and increasingly so? Social and cultural barriers often hinder women’s economic participation in the region and several recent studies find that women are at an increasing disadvantage compared to men in labor markets (Amara and Jemmali, 2018; AlAzzawi and Hlasny, 2022). The COVID-19 pandemic further deepened gender inequality in many countries (Dang and Nguyen, 2021; Alon _et al._ , 2022). Yet, few studies have investigated the topic of poverty feminization in the region. These are important policy questions since many countries in the region specifically target FHHs based on the premise that they are more vulnerable to poverty and probably increasingly vulnerable to poverty, particularly during the pandemic.<sup>1</sup> Furthermore, the Arab region is home to countries of different income levels with diverse social and cultural circumstances, resulting in different context-specific factors contributing to poverty feminization.

That poverty is more prevalent among women than men is widely assumed, and various explanations are offered for it. These include lower school enrollment rates and less work experience (Grant and Behrman, 2010), limited access to income-generating assets such as land (Deere and Leon, 2003), credit and other financial services (Demirguc-Kunt _et al._ , 2013), physical and social capital, and technology (World Bank, 2011; Klasen _et al._ , 2015), and market discrimination (Buvinic and Gupta, 1997).

There is, however, far less agreement on the existence of “feminization of poverty” affecting FHHs (Chant, 2010; Duflo, 2012; Klasen _et al._ , 2015; Bradshaw _et al._ , 2017). Buvinic and Gupta (1997) observe that of 65 studies covering Africa, Asia, Latin America and the Caribbean, 38

> 1 These include the Arab Republic of Egypt’s largest poverty-targeting cash transfer program, Takaful, and other subsidy programs in Jordan, Lebanon, and Tunisia (NAF, 2020; Nasri, 2020; ESCWA, 2021; World Bank, 2022).

2
studies find that FHHs were overrepresented among the poor, 15 others found that poverty was associated with certain FHH types, and the remaining eight studies show no such relationship. While Quisumbing _et al._ (2001) and Medeiros and Costa (2008) find FHHs to be consistently poorer in only 10 developing countries in Africa, Asia and Latin America, Chant (2003) fails to obtain a similar finding in studies for the three continents <mark>. More recently,</mark> Milazzo and van de Walle (2017) even find that despite a growing population share of FHHs in Africa, FHHs saw faster poverty reduction than male-headed households (MHHs). Furthermore, one particular challenge in understanding the current literature on poverty feminization is variations in how FHHs are defined (see Appendix A, Table A.1; we return to this discussion in the next section).

Several authors investigated the gender dimension of poverty in the Arab region before the onset of the Arab Spring uprisings in 2011 (Nassar, 1997; Datt _et al._ , 2001; El-Laithy, 2001). More recent post Arab-Spring studies examined poverty dynamics for the whole population and different population groups (e.g., Dang and Ianchovichina, 2018). Yet, these studies do not investigate the gender prism; just a few studies explicitly examine poverty feminization related to FHHs but only on a single-country basis (AlAzzawi, 2018; Amara and Jemmali, 2018; AbdelLatif _et al._ , 2019). Furthermore, these few studies stopped short of examining poverty dynamics for FHHs due to the lack of panel data.<sup>2</sup> These knowledge gaps prevent efficient and cost-effective policy interventions, since policies that address chronic poverty could be quite different from those that tackle transient poverty.<sup>3</sup>

> 2 Mixed results exist regarding static poverty across countries. For example, comparison between MHHs and FHHs by self-reported headship revealed that for the Arab Republic of Egypt, FHHs are less likely to be poor (AlAzzawi, 2018; AbdelLatif _et al._ , 2019) while the opposite result holds for Tunisia (Amara and Jemmali, 2018).

> 3 For example, while social safety-net programs better address transient poverty (e.g., as they help prevent the nonpoor but vulnerable households from falling into poverty), longer-term investments in human capital and infrastructure can tackle chronic poverty. See, e.g., Barret (2005) and Ravallion (2016) for further discussion on different policy interventions regarding chronic poverty versus transitory poverty.

3
Our study makes several new contributions to the literature. First, we propose and evaluate a novel typology of FHHs consisting of four main types and several sub-types, which are based on self-reported responses, demographic characteristics, and socio-economic characteristics. This approach allows us to employ more nuanced headship definitions that reach beyond the traditional identification solely based on the household head’s gender to better include other aspects of household female composition. Our proposed typology also calls for more attention to the important role of children in defining FHHs, since FHHs with children could show remarkably different, static and dynamic, poverty outcomes from those of FHHs without any children or those of non-FHHs. Second, we study the trends in the FHH poverty–gender nexus and poverty dynamics, for six countries across the Arab region—namely the Arab Republic of Egypt, Iraq, Jordan, Mauritania, the West Bank and Gaza (Palestine), and Tunisia—for which little knowledge exists regarding poverty by FHH status.

Third, despite the absence of actual panel data, we construct synthetic panels that allow us to examine FHH poverty dynamics for these countries. By conducting analyses on both poverty incidence and dynamics, we contribute to a better understanding of the dynamic economic wellbeing of FHHs over time. In fact, to our knowledge, we offer the first multi-country study that investigates to what extent FHH poverty exists across a number of countries in the Arab region, and whether FHHs, according to a variety of household types, are more likely to enter or escape poverty over time, using recent survey data. We also make a new data contribution by carefully assembling and harmonizing relevant, up-to-date surveys from multiple sources in a region that is well recognized for limited data access.

We find that the shares of FHHs widely vary, ranging from 10 percent to more than 40 percent depending on the countries and definitions. Compared with non-FHHs, most types of FHHs 4
(including self-reported, potential, and most-educated-female-adult FHHs) are 1 percent to 4 percent less likely to be poor while majority-female-adult FHHs are 3 percent to 5 percent more likely to be poor.

We also find considerable mobility in and out of poverty over the past decade, with the average poor FHH having between 21 and 54 percent chance of escaping poverty, depending on the country. Yet, country heterogeneity exists, with Iraq, Jordan, and Mauritania having upward mobility rates of between 41 and 54 percent, and Egypt, the West Bank and Gaza and Tunisia having upward mobility rates between 21 and 31 percent. More children are generally associated with more poverty and lower chances of escaping poverty for FHHs. The upward mobility rates out of poverty for FHHs without children, FHHs with children, and non-FHHs across all countries are respectively 42 percent, 37 percent, and 36 percent. The corresponding figures for downward movement into poverty for these FHH types are respectively 14 percent, 17 percent, and 19 percent. Our results on mobility are robust to different definitions of FHHs, alternative estimation models, and sample sizes.

The rest of the paper is organized as follows. Section 2 discusses the various definitions of female headship in the existing literature before proposing our new typology of female-headed households (Section 2.1) and introduces the synthetic panel method that allows us to assess FHH poverty feminization dynamically without actual panel data (Section 2.2). Section 3 reviews the available data (Section 3.1), welfare aggregates and standardization measures (Section 3.2), and presents descriptive statistics (Section 3.3). Section 4 reports the main results for cross-sectional poverty (Section 4.1) and poverty dynamics (Section 4.2), and Section 5 concludes with key findings and policy implications. Appendixes A and B present additional estimation results and 5
descriptive statistics, Appendix C discusses the synthetic-panel method, and Appendix D provides further analyses with equivalence scales.

# **2. Analytical Framework**

# **2.1. Typology of female-headed households**

Households vary in their compositions and socioeconomic characteristics. In the countries in our sample, the majority of households are comprised of a married couple with one or two income earners, with or without children. Single-head households vary broadly: from widowed retirees who may have already worked for many years and are now living with older children who might be supporting them, to a middle-aged mother who got divorced or lost her husband and is struggling to meet ends by joining the labor market for the first time. Among this group, the presence of another adult male, whether an earner or not, is yet another confounding factor, as well as the presence of children.

The heterogeneous nature of FHHs and the need to separately study different FHH types have been discussed extensively in the literature on poverty feminization (e.g. Kabeer, 1997; Quisumbing, _et al._ , 2001; Klasen _et al._ , 2015; Beegle _et al._ , 2016; Munoz Boudet _et al._ , 2018). The variety of household-headship designations in existing studies has led to mixed results regarding poverty feminization and dynamic patterns. Our reading of some selected studies in the past two decades suggests that while FHHs are not observed to be poorer than non-FHHs in many cases, FHHs can be poorer or have lower consumption depending on the specific type and country context (Appendix A, Table A.1). Advancing an FHH typology can thus be critical for clearing the apparent inconsistencies and for re-classifying households with what may be considered “ _de facto_ female heads” (based on demographic or socioeconomic characteristics), as opposed to “ _de_ 6
_jure_ female heads” (based on official status or self-reported information). This also has important implications for poverty reduction efforts targeted at vulnerable population groups.

Figure 1 presents our proposed typology of FHHs, which consists of several layers. For the first layer, existing studies can be broadly grouped under two categories: “ _de jure_ FHH” and “ _de facto_ FHH” (second row). For the second layer, we consider three approaches under these two groups: the self-reported approach (under “ _de jure_ FHH”), and the demographic approach and the socioeconomic approach (under “ _de facto_ FHH”) (third row). For the third layer, we consider four main types of FHHs under these three approaches: i) Type 1: self-reported FHHs, ii) Type 2: FHHs defined using the majority share of females among adults in the household (i.e., majority-femaleadult FHHs), iii) Type 3: potential FHHs, and iv) Type 4: FHHs defined as those where the mosteducated adult member is female and no working-age employed male is present (i.e., mosteducated-female-adult FHHs) (fourth row). Furthermore, under these four main types, we also consider five alternative sub-types, which include _de jure_ and married FHHs (under self-reported FHHs), FHHs defined using the majority share of employed females in the household (under majority-female-adult FHHs), and asset and core FHHs (under potential FHHs) (fifth row).<sup>4</sup> Finally, all these types of FHHs should be considered separately with or without any children (last row), since the presence of children plays a crucial role in FHHs’ poverty as discussed below.

The typology is motivated by both our review of the literature and our empirical analysis for each type of FHHs in the Arab region. Figure 1 briefly refers to some illustrative studies that employ these approaches and we elaborate below on this new typology.

# **_“De jure” FHHs: Self-reported approach_**

> 4 While we propose these three approaches and types for classification purposes, they are not mutually exclusive and existing studies have combined one or more in defining female headship.

7
A natural departure point to analyzing FHHs is to adopt the self‐reported identification of the head by the survey respondent (our first type, self-reported FHHs), which falls under the _de jure_ FHHs group. Marital status is a key characteristic in this respect. A large share of FHHs are formed as the result of a major marital shock such as divorce or widowhood. If, prior to the shock, the husband was the primary income-earner, the newly-formed FHH may be more likely to fall into poverty (Brown and van de Walle, 2021). FHHs formed through widowhood, especially at a young age with children present, can exhibit both more poverty and higher persistence of poverty (Appleton, 1996; Dreze and Srinivasan, 1997; Horrell and Krishnan, 2007; van de Walle, 2013; Munoz Boudet _et al._ , 2018; Brown and van de Walle, 2021) than FHHs formed largely “by choice”, through divorce or migration of the male spouse (Quisumbing, _et al._ , 2001; Klasen _et al._ , 2015; Beegle _et al._ , 2016; Bradshaw _et al._ , 2017).

Females who never marry or who seek divorce might have chosen this status because they have strong prospects for supporting their newly-formed households on their own, such as higher personal incomes or enabling family-support systems. Ignoring such considerations could mask differences between self-reported FHHs that are financially secure and those that are economically vulnerable (Kabeer, 1997; van de Walle, 2013; Milazzo and van de Walle, 2017). Consequently, it may also be useful to consider alternative types of households based on their marital status— never married, married, divorced or separated, and widowed.

In our samples, most self-reported MHHs are married, and this group is the largest in the sample. By contrast, from 69 to 77 percent of self-reported FHHs in all six countries are widowed, except for Mauritania and the West Bank and Gaza, where 35 and 53 percent, respectively, of selfreported FHHs are widowed households when considering all years together (Appendix B, Tables B.1-B.7). The second-largest group of self-reported FHHs have married heads, but this share 8
typically remains about 20 percent or below in all countries and years, except for Mauritania where it rose rapidly to almost 40 percent after 2008.<sup>5</sup>

# **“** **_De facto” FHHs: Demographic and socioeconomic approaches_**

The term “head” is a loaded term carrying strong connotations about household decisionmaking power that has traditionally been given to the oldest-male member (regardless of his breadwinner status). This is certainly an issue in the Arab region, where the traditional patriarchal system may preclude designating the female as “head” in the presence of a disabled adult male or a son (regardless of age), even if the woman is the main income-earner.

A _de facto_ FHH can thus be defined as one where the male head is temporarily or regularly absent, or (if co-resident) is not the main breadwinner (Buvinic and Youssef, 1978; Buvinic _et al._ , 1983; Klasen _et al._ , 2015). _De facto_ headship accounts for the demographic composition of the household, as well as the socioeconomic circumstances determining the respective members’ relative contributions to household resources (Rosenhouse, 1989; Handa, 1994, 1996; Rogers, 1995; Varley, 1996; Buvinic and Gupta, 1997; Fuwa, 2000; Posel, 2001; Budlender, 2008; Grown and Valodia, 2010; Chant, 2010; Rogan, 2013; Klasen, 2015).

A _de facto_ FHH may be more vulnerable to poverty for several reasons. In many societies, the absence of male connections to local economic and social institutions can be debilitating. _De facto_

> 5 One complication in classifying married self-reported FHHs arises where one spouse works overseas and sends home remittances, which is common in the region. If the overseas spouse is the husband, the stay-behind spouse might or might not designate herself as the household head in his absence. This can underestimate poverty among “true” FHHs, where the female head does not rely on others for support, since some of the self-declared female heads or main income-earners are in fact temporary designees while the main income-contributing spouses are overseas. In the surveys for all years, remittances are major sources of income for self-reported FHHs, consisting for example of 68% of the consumption per capita in Egypt, and 37% of the consumption per capita in Jordan (Appendix B, Tables B.1 and B.4, all years columns). However, the surveys lump together domestic and overseas remittances and do not allow any further breakdown or provide information on the amount of overseas remittances. The surveys do not identify the relations between the remitters and the households, which complicates matters as such remittances might be alimony or in-kind support.

9
FHHs residing with the female heads’ fathers or older sons may still be better off than FHHs who do not have support of working-age males; for example, agricultural production may become especially harder due to fewer working-age household members working on the farm (Rogan, 2013; Brown and van de Walle, 2021). These FHHs may also have less access to productive assets such as livestock or extension services. Moreover, women in Arab labor markets have far fewer job opportunities compared to men. Their labor-force participation rates are currently among the lowest in the world; their unemployment rates are also four times the world average (UNDP, 2022). When they do work, they tend to face wage and occupational discrimination (Elhamidi and Said, 2008) or are overrepresented in the informal sector with low pay and no social insurance. Residing in a majority-female household, or in one where the majority of earners are female, affects the propensity of being poor (Rogan, 2013; Munoz Boudet _et al._ , 2018).

Ideally, an objective criterion would be used to assign headship to the family member whose income or decision-making contributes most to maintaining the family. For instance, Gammage (1998) found that using the _maintenance_ criteria to define FHHs in El Salvador and Costa Rica results in a markedly higher percentage of such female-maintained households (FMHs) compared to the _de jure_ FHH group, and higher poverty incidence. Unfortunately, household surveys in the Arab region do not provide information about individual incomes or total earnings, only aggregates for the household.

In the absence of such information, based on our review of the literature (Table A.1 in Appendix A), we propose several alternative definitions of _de facto_ FHHs using demographic and socioeconomic criteria to provide a more multifaceted understanding of FHHs. Regarding household composition, we consider households where the _proportion of females among (workingage) adults exceeds 0.5_ (second type, majority-female-adult FHHs). We define _potential FHHs_ as 10
those households where there are no working-age males present (third type, potential FHHs). The final type of FHHs combines the demographic and socioeconomic criteria and consists of _households with no employed males, whose most-educated adult member is female_ (fourth type, most-educated-female-adult FHHs).

Notably, these main types of FHHs can also include subcategories. For example, under the second-type majority-female-adult FHHs, we can consider those where the _proportion of employed females exceeds that of employed males (majority-employed-female-adult FHHs)._ Similarly, under the third-type potential FHH, we can consider a subcategory called _core FHH_ that encompasses only the potential FHHs with employed females, and another subcategory called _asset FHH_ encompassing only households with females who have ownership rights over the dwellings they reside in.

# **_Key confounding factors: Presence of children_**

To account for additional household circumstances interacting with household poverty status, we should distinguish FHHs _with and without children_ . Access to childcare affects women’s labor force participation (LFP) in many countries around the world, rich and poor alike (Akgunduz and Plantega, 2018; Clark _et al._ , 2019). In European countries, childless women (with or without a partner) and single mothers have higher personal earnings than women whose family trajectories combined parenthood and partnership (Muller _et al._ , 2020). In Egypt, childcare similarly presents a considerable barrier to women’s employment (Caria _et al._ , 2022). Yet, only a handful of previous studies have examined how poverty differs with and without children, but mostly for self-reported FHHs (Medeiros and Costa, 2008; Liu _et al._ , 2017; AlAzzawi, 2018). Exceptions include Munoz Boudet _et al._ (2018) and Munoz Boudet _et al._ (2021), who look at household gender composition 11
with and without children. Importantly, the common finding in these few studies is that FHHs with children are generally poorer than FHHs without children.

Furthermore, a related economics literature on equivalence scales suggests that scale adjustments (for different numbers of adults and children) could have substantial effects on poverty and profiles of the poor for various countries at different income levels (Lanjouw and Ravallion, 1995; Newhouse _et al._ , 2017; Abanokova _et al._ , 2022). This is especially relevant for FHHs; for example, FHHs tend to have lower numbers of household members, but higher dependency ratios (World Bank, 2011; Klasen _et al._ , 2015). In our sample (Appendix B, Table B.7), across all years and countries, the average size of FHHs is 5.7, while that of MHHs is 7.4. The average age of female heads is much higher than that of male heads (56 for FHHs vs. 48 for MHHs). Female heads are also mostly widowed (70.7%, compared to 1.3% for male heads).

For widowed FHHs, their offspring are typically already-grown, independent adults who might be contributing to household expenses from their own earnings. The current welfare of these female heads is likely a function of their accumulated earnings, or more likely those of their deceased or living spouses and adult children, and thus are not strictly comparable to (male or female) heads with young children who rely on current labor market earnings to support themselves and their families. This distinction is especially pertinent to dynamic analysis. If the full sample of female or male heads were treated as a single group, this would unduly bias the results in favor of the elderly, widowed female heads without children, and against the much younger working male heads with children. Consequently, it is important to examine poverty incidence and dynamics among FHHs with or without children.

In summary, our new typology consists of four main types of FHHs and their associated five sub-types (variants). We investigate poverty trends and dynamics of these four types of FHHs for 12
households with and without children, further differentiating between those with different numbers of children.

# **2.2. Empirical framework**

We provide both static and dynamic analyses of FHH (headcount) poverty in the Arab region. For static analysis, we examine the differences in poverty between different types of FHHs and non-FHHs. Specifically, we estimate the following linear probability model i hF i hF i i i i h′ i i (1) iih iih iih iih iih ii ii iih where ppi is a binary variable representing the poverty status (i.e., equals 1 if poor and 0 = γγ FF + θθ FF ∗CChi + ββ ZZ + μμ + ττ + εε hll otherwise) for household pp _i_ , _i= 1,..., n_ in survey round _j_ , _j_ = 1 or 2, country _c, c_ = 1,..., 6, for FHH type _h_ (F i ). i i i iih iih<sup>is the number of young children age 0-14 in the household (who</sup> are generally not old enough to enter the labor force). FF CChi i is a vector of control variables, iih including household employment and demographic characteristics and residence area (i.e., urban/ ZZ rural residence). and are respectively the country and survey round (year) fixed effects that ii ii control for unobserved macro factors that can affect the whole country or outcomes in specific μμ ττ years, and i is the error term. iih In Equation (1), εε h and h are the coefficients of interest. Compared to non-FHHs, h presents the association between poverty and different types of FHHs without any children, γγ θθ γγ h h presents this association for FHHs with exactly one child, and so on. For easier interpretation, we γγ + θθ ���������������� can also fix the number of children at the mean ( i ı ) and consider the association iih between poverty and different types of FHHs with the average number of children as CChııi ii h + ���������������� h i ı . γγ iih θθ CChııi ii 13
It is useful to estimate and compare two different versions of Equation (1), one without the control variables i and one with these control variables. If the estimates for h considerably iih change (or weakens) if the control variables are added, this indicates that the specified FHH type’s ZZ γγ exposure to poverty is sensitive to these control variables. Put differently, this presents a test whether the specified FHH type can capture a relationship with poverty that is not explained by the control variables (i.e., how good the definition of the specified FHH type is). The findings based on our review of the literature suggest that FHHs’ exposure to poverty ( h and to some extent h) are likely sensitive to household composition and employment characteristics. γγ For the dynamic analysis, let θθ i represent type- _h_ FHHs’ household consumption (or income) iih per capita, and i h be the poverty line in period yy _j_ for country _c._ We are interested in knowing the unconditional measures of upward poverty mobility such as zz ) (2) ii1iih 1ii ii2iill 2ii which represents the percentage of type-PP(yy < zz _h_ FHHs that are poor in the first survey round (year) but aai yy > zz nonpoor in the second survey round, or the conditional upward mobility measures such as ) (3) ii2iih 2ii ii1iih 1ii which represents the percentage of poor households in the first round that escape poverty in the PP(yy > zz | yy < zz

second round.

If true panel data were available, we could straightforwardly estimate the quantities in (2) and (3); but in the absence of such data, we can use synthetic panels to study mobility. We employ recent advances with synthetic panel data methods (Dang and Lanjouw, 2023) to construct synthetic panel data and provide more insights into the dynamics of poverty for FHHs over time.<sup>6</sup>

> 6 Recent validations and applications of the synthetic-panel methods by various researchers for different country contexts in Africa, Latin America, the Middle East, and Europe have been encouraging regarding accurate projections

14
Different from traditional pseudo-panel methods that require multiple rounds of cross-sectional surveys to study poverty mobility at the cohort level, the method that we apply works with as few as two survey rounds and provides poverty estimates at the more disaggregated household level. This method essentially exploits the time-invariant variables across the cross-sectional surveys to link different cohorts, in combination with additional cohort-based assumptions about the error terms, to construct the synthetic panels. Further discussion of this method and detailed estimates are provided in Appendix C.

# **3. Data and Descriptive Statistics**

# **3.1. Data**

We analyze 20 survey rounds from six countries: Egypt, Iraq, Jordan, Mauritania, the West Bank and Gaza, and Tunisia. For Egypt, we use the Household Income, Expenditure and Consumption Surveys (HIECs) for 2012-2013, 2015, 2017-2018, and 2019-2020; for Iraq, the Household Socio-Economic Survey (IHSESs) for 2007 and 2012; for Jordan the Household Expenditure and Income Surveys (HIESs) for 2010-2011 and 2013-2014; for Mauritania, the Permanent Survey of Living Conditions of Households (EPCVs) for 2004, 2008, 2014, and 2019; for the West Bank and Gaza, the Expenditure and Consumption Survey (PECSs) for 2007, 2009, 2011, and 2016-2017; and for Tunisia, the National Survey on Household Budget, Consumption and Standard of Living (NSHBCs) for 2005, 2010, 2015, and 2021. These surveys provide rich information on household expenditures and various household and individual characteristics for the different household types.

of economic status (Ferreira _et al._ , 2012; Beegle _et al._ , 2016; UNDP, 2016; OECD, 2018; Salvuci and Tarp, 2021; Ghomi, 2022).

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Several of these surveys were harmonized by the Economic Research Forum (Egypt’s 20122013, 2015, 2017-2018 HIECSs; Iraq’s 2007 and 2012 IHSESs; Jordan’s 2010-2011, and 20132014 HIESs; the West Bank and Gaza’s 2009 and 2011 PECSs; and Tunisia’s 2005 and 2010 NSHBCs. The most recent surveys for Egypt (2019-2020), the West Bank and Gaza (2016-2017), Tunisia (2015 and 2021), and the Mauritanian EPCVs were obtained from national statistical agencies CAPMAS, PCBS, INS and ONS, respectively. We implemented careful harmonization of these surveys with the previous survey years and translated the variables from Arabic or French to English.

We present the poverty lines for the six countries in Tables A.2-A.7 (Appendix A), compiling them from official sources and World Bank publications. We used region-specific poverty lines within each country to account for spatial differences in consumption (expenditure) patterns and price levels.<sup>7</sup> Since our focus is on poverty analysis, we used consumption values and national poverty lines in local currency units and in survey-year prices to sidestep conversion issues (e.g., with the PPP or market exchange rates) and adjustment for inflation.

# **3.2. Living-standards indicator**

Expenditure is widely regarded as a better indicator of permanent income when households, particularly in poorer countries, exercise consumption smoothing and use savings to augment unstable incomes due to seasonal or informal employment or unexpected shocks (Deaton, 1997; Deaton and Zaidi, 2002; Mancini and Vecchi, 2022). We use household consumption expenditures

> 7 We were able to do this for all countries in our sample except for Jordan. According to DOS reports, Jordan’s Department of Statistics (DOS) did not publish region-specific poverty lines and used a single poverty line for all of Jordan in 2010 and 2013. Jordan’s DOS does not publish region-specific Consumer Price Indices so we were unable to take spatial price differences into consideration.

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per capita as the welfare measure underlying poverty analysis.<sup>8</sup> This includes all monetary expenditures on consumer goods and non-monetary consumption, such as imputed rents, use-value of durables, own production and in-kind transfers (i.e., gifts) received by households. Food consumption includes food that the household has purchased, grown and received from other sources. Non-food consumption is the sum of expenditure on all non-food items, including expenditure on fuel, clothing, schooling, health and miscellaneous items, and in-kind transfers.

It can be useful to ensure comparability of household expenditures across different contexts to account for potential differences in households’ age and size compositions, as well as economies of scale in consumption. Studies have examined individual-level, rather than household-level, consumption to better disaggregate expenditures by gender (Dunbar _et al._ , 2013; De Vreyer and Lambert, 2021). Unfortunately, the available surveys provide data on household consumption aggregates rather than individual-level consumption; therefore this approach cannot be applied to the available data.

Another approach is to calculate the Adult Equivalent Expenditure (AEE) (or income) for each household, which gives smaller weight to children than adults and takes economies of scale into consideration. For example, Deaton and Paxson (1998) suggest using a parametric form of an equivalence scale, where a child is assumed to require a fraction of what an adult needs, and where the elasticity of needs with respect to adjusted household size is a constant αα . This gives rise to the following formula δδ

> 8 This is also the most common approach employed in recent studies of poverty in countries in the Middle East (Marotta _et al._ , 2011; CAPMAS, 2013).

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where i∗ is the AEE for household _i_ in survey _j_ , which is an adjusted version of household expenditure conditional on the number of adults yy i and children i (we suppress the country and FHH type indexes for less cluttered notation). The smaller aa is, the smaller the relative weight of kk children; the higher is , the smaller the degree of economies of scale assumed.αα<sup>9</sup> We construct several different AEE levels for each household based on this method, using different values for δδ the weight of children ( ) and degree of economies of scale ( ) and show the results in Figure D.1, Appendix D. The relationship between household size and poverty dynamics reveals varying αα δδ scenarios for FHHs, with FHHs generally having a higher likelihood of escaping poverty than nonFHHs when assessing consumption on a per capita basis.<sup>10</sup>

# **3.3. Descriptive statistics**

Table 1 presents some key sample statistics on the prevalence of FHHs defined according to our proposed typology (Section 2.1) across the six Arab countries and different (survey) years. The four main types of FHHs are shown in bold while the alternative sub-types are shown in regular font. The shares of self-reported FHHs remain relatively stable over time in most countries, except for Mauritania. In recent years, this share hovers from around 10 percent (Iraq, the West Bank and Gaza) to 13 percent (Jordan) and 18 percent (Egypt, Tunisia).<sup>11</sup> Mauritania has the largest share of self-reported FHHs, which has almost doubled from 18.9 percent in 2004 to 36.6 percent in 2019. The shares of majority-female-adult FHHs are significantly higher in all countries,

> 9 When = 1 and = 1, we have per capita expenditure, which assumes no economies of scale and an equal weight for children and adults in the household. 10 These results are consistent with Abanokova δδ αα _et al.’_ s (2022) finding regarding the sensitivity of income dynamics to scale parameters, showing persistent upward mobility when income is evaluated on a per capita basis for the Russian Federation.

> 11 These shares are lower than the corresponding figure of 26 percent for African households observed in Milanzo and van de Walle (2017).

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ranging from 21 percent (Egypt) to 44 percent (Mauritania) in the most recent years. Potential FHHs are as prevalent as those identified by self-reporting in all the countries except Iraq, where they are half as prevalent. Finally, most-educated-female-adult FHHs have relatively low prevalence rates, ranging from around 6 percent in Iraq to 25 percent in Mauritania. There is a weak-to-medium correlation among the four FHH types (i.e., ranging from 0.27 to 0.51; Appendix A, Table A.8), suggesting that each of the proposed FHH types captures different information about female headship.

Compared with the main four types, the alternative subtypes all provide lower-to-almostnegligible prevalence of FHHs. For example, under the self-reported FHH type, while _de jure_ FHHs account for between 8 percent and 17 percent of households for all countries and years, the corresponding figures for married FHHs are between 1 percent and 4 percent for all the countries, except for Mauritania in 2008 and later years. Under the majority-female-adults FHH type, the sub-type majority-employed-female-adult FHHs, however, yield a much smaller group of FHHs (ranging from around one-half to two-thirds as small). This is expected given the very low female LFP rates in the region, especially in such countries as Iraq and Jordan where they are among the lowest globally.

Figure 2 illustrates the trends in poverty headcount ratios by country for the four main types of FHHs against those of the whole population for each country. This figure shows that different FHH types display clear differences regarding poverty levels and trends. Specifically, while potential FHHs (purple line) show faster poverty decreases in Iraq, Jordan, the West Bank and Gaza, and Tunisia, most-educated-female-adult FHHs (pink line) show slightly opposite trends from those of the whole population for Iraq. This contrasts with self-reported FHHs (green lines) 19
and potential FHHs, which predominantly have less poverty than the whole population for almost all the country-year observations.<sup>12</sup> For each country, Figure 3 and Figure 4 present the poverty differences between FHHs and non-FHHs for the four main FHH types respectively by year and by the number of children (age 0-14). Figure 3 indicates that the self-reported and potential FHH types typically have lower poverty ratios than non-FHH households across most years and countries. However, majorityfemale-adult FHHs tend to be poorer than the respective non-FHHs in most years and countries, except in Egypt 2017–2020. Most-educated-female-adult households have systematically more poverty prevalence than the corresponding non-FHHs in Iraq, Jordan, the West Bank and Gaza and Tunisia, but less poverty prevalence in Egypt and Mauritania.<sup>13</sup> Figure 4 shows that the presence of children is positively associated with poverty prevalence among FHHs for most of the countries, except for Egypt and Mauritania.

# **4. Estimation Results**

# **4.1. Cross-sectional poverty**

Table 2 provides the estimation results for the associations between four main FHH types and poverty ( h in Equation (1)), without and with the household employment, demographic γγ

> 12 Pooling data for all years and countries, we further show the FHH–non-FHH poverty differences for all FHH types and by the number of children in households in Figures A.2 and A.3 (Appendix A). These figures indicate that the self-reported and potential FHH types tend to have less poverty than non-FHH households across most years and countries, but the relationship between the number of children and poverty varies across countries.

13 Table A.9 (Appendix A) provides cross-sectional poverty rates for different household types over time in six countries. Panels B and C additionally report these poverty rates for rural and urban subgroups, and Panels D and E report the poverty rates for households with children under 14 and without children under 14. Poverty rates are typically higher in rural area than in urban areas, except for the West Bank and Gaza, and higher for households with younger children. Given the consistently high poverty rates among FHHs defined by the share of women among adults, we also assess the poverty rates among self-reported MHHs according to the number of female adults present in Figure A.1 (Appendix A). Poverty almost always increases with the number of females in all six countries, validating the central finding from Figure 3.

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characteristics and residence-area variables shown respectively in the first four columns and the second four columns (Appendix A, Table A.10 offers the full results). Several interesting results stand out. First, the estimated h is negative and strongly statistically significant for three FHH types: self-reported, potential, and most-educated-female-adult FHHs, suggesting that these three FHH γγ� types are associated with less poverty prevalence. Majority-female-adult FHHs, in contrast, are associated with more poverty. This is generally consistent with our earlier discussion for Figure 3, indicating that these types of FHHs can serve as useful definitions. Second, the absolute magnitude of h increases for self-reported and most-educated-femaleadult FHHs but decreases for majority-female-adult and potential FHHs when the control variables γγ� are added. The t-tests for these changes are statistically significant. This suggests that, consistent with our earlier discussions of the literature (Sections 2.1 and 2.2), FHHs’ exposure to poverty is also affected by the control variables, including household employment, demographic characteristics, and residence area variables. Indeed, prior research for various countries suggests that FHHs are not systematically poorer or more vulnerable (Fuwa, 2000; Klasen _et al._ , 2015; Munoz Boudet _et al._ , 2018; Brown and Van de Walle, 2021). Liu _et al._ (2017) find that in eight of 14 Latin American countries, FHHs more likely live in poorer conditions, but these gaps either disappear or reverse when controlling for other household and demographic characteristics.

Table 2 shows that self-reported FHHs are about 1 percent (without control variables) to 4 percent (with control variables) less likely to be poor than non-FHHs if there are no children in the household. The corresponding changes are about 3 percent (without control variables) to 2 percent (with control variables) for potential FHHs, and 1 percent (with control variables) for mosteducated-female-adult FHHs. However, majority-female-adult FHHs are 5 percent (without 21
control variables) to 3 percent (with control variables) more likely to be poor than non-FHHs if there are no children. Finally, the estimated interaction term between FHH types and the number of children ( ) is ll positive for three of the four FHH types (self-reported, potential, and most-educated-female-adult θθ<sup>�</sup> FHHs), but negative for majority-female-adult FHHs. While the absolute magnitudes of h are small, around 1 percent (i.e., one more child is associated with a 1-percent change in the probability θθ<sup>�</sup> of the household being poor), it is strongly statistically significant. Furthermore, when we fix the number of children at the mean of the estimation sample (i.e., 1.81 children), self-reported FHHs become 1 percent more likely to be poor (without control variables) and 3 percent less likely to be poor (with control variables). The corresponding probabilities, without and with control variables, become 2.5-2.8 percent more likely to be poor for most-educated-female-adult FHHs and 4-0.7 percent more likely to be poor for majority-female-adult FHHs. However, potential FHHs are 0.2 percent (without control variables) less likely to be poor and are 0.3 percent (with control variables) more likely to be poor. In addition, having more children (or larger household sizes) is associated with greater poverty risks (Appendix A, Table A.10). This result concurs with the finding by Munoz Boudet _et al._ (2018) and Munoz Boudet _et al._ (2021) that adult couple households with children are the largest and overrepresented group among poor households. This provides supportive evidence for our proposed typology that considers children when defining FHH types.

The five remaining FHH subtypes offer qualitatively similar results, showing that most FHH types are associated with less poverty, except for majority-employed-female-adult FHHs where the opposite result holds (Appendix A, Table A.11). This table also shows the interaction terms between FHH types and the number of children, which are mostly statistically significant. The results using the alternative logit model are qualitatively similar, albeit somewhat weaker for the 22
most-educated-female-adult FHHs (Appendix A, Tables A.12 and A.13).<sup>14</sup> We further consider the overlaps of three main FHH types (self-reported, potential, and most-educated-female-adult FHHs) and all four main FHH types and show the estimation results in Appendix A, Table A.14, which remain qualitatively similar.

# **4.2. FHH poverty dynamics based on synthetic panels**

We turn next to discussing the results on poverty dynamics based on synthetic panels. For each country, Figure 5 reports the conditional upward mobility rates in the second survey year for the four main FHH types, considered separately with and without any children (Equation (3)). Figure 5 shows considerable (conditional) upward mobility at the national average level (dashed line) for some countries. In particular, the upward mobility rate is 45 percent in Iraq during 2007-2012 (i.e., 45 percent of the initial poor in the first year escape poverty in the second year), 54 percent in Jordan during 2010-2013, and 41 percent in Mauritania during 2014-2019. Still, a significant degree of immobility exists in Egypt, the West Bank and Gaza, and Tunisia, where most of the population remained poor in both years and only about one-third (or less) of the poor escaped poverty in the most recent year: 29 percent for Egypt during 2017–2020, 31 percent in the West Bank and Gaza during 2011–2017, and 21 percent in Tunisia during 2015–2021.<sup>15</sup> Unsurprisingly, non-FHHs have upward mobility rates that are almost the same as the national averages, given their large shares in the population (Table 1). But interestingly, FHHs without

> 14 The estimated marginal effects for the interaction terms with children are qualitatively similar (using the Stata command “ginteff” (Radean, 2023)).

> 15 The survey period lengths generally differ for the six countries so the estimated mobility rates are not exactly comparable across countries or to those in other studies. For a rough reference, Dang and Ianchovichina (2018) obtain a regional upward mobility rate around 52 percent in the early 2000s and 2010s. However, if we assume a similar rate of change for mobility across the years for all countries, we can obtain the average mobility per year for each country (Appendix A, Table A.15).

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children are most likely to experience upward mobility. Out of 24 FHH types across six countries, the probabilities of FHHs without any children escaping poverty are higher than the national averages in 22 cases. The exceptions are self-reported and potential FHHs in Jordan during 20102013, which have similar upward mobility rates as the national average. However, FHHs with children have upward mobility rates that are clearly higher than the national averages in five cases (self-reported, majority-female-adult, and most-educated-female-adult FHHs in Egypt during 2017-2020, and self-reported FHHs in Iraq during 2007-2012 and in Mauritania during 2014-2019) and clearly lower than the national averages in six cases (self-reported, majority-female-adult, and most-educated-female-adult FHHs in Jordan 2010-2013 and Tunisia 2015-2021). FHHs with children have similar upward mobility as the national averages for the remaining cases. Overall, across all countries and four main FHH types, the upward mobility rates for FHHs without children, FHHs with children, and non-FHHs are respectively 42 percent, 37 percent, and 36 percent.

Figure 6 plots the conditional downward mobility (i.e., falling into poverty in the second year when being initial non-poor in the first year). The results are consistent with those shown in Figure 5, with FHHs without children experiencing the least downward mobility, followed by FHHs with children and non-FHHs. Overall, the downward mobility rates for FHHs without children, FHHs with children, and non-FHHs are respectively 14 percent, 17 percent, and 19 percent.

As an alternative to Figure 5, we plot the results of locally weighted regressions of upward mobility on the number of children (Appendix A, Figure A.3). This figure also shows that the number of children is negatively associated with upward mobility for most countries and FHH types. The results for other sub-types of FHHs are qualitatively similar, with FHHs without children having the most upward mobility (Appendix A, Figure A.4). The results for preceding 24
years are, however, somewhat mixed. FHHs without children had the strongest upward mobility for Egypt and Tunisia, but had similar upward mobility as FHHs with children for Mauritania and the West Bank and Gaza (Appendix A, Figures A.5-A.8). Finally, we plot the results for upward and downward mobility for FHH types, with and without children considered together, in Figures A.9 and A.10 (Appendix A). These figures show that FHHs have higher upward mobility and lower downward mobility than MHHs across all FHH types and countries, except for Jordan.<sup>16</sup>

# **5. Conclusions and Policy Implications**

The dramatic events of the Arab Spring and the following decade of structural reforms and sectoral developments _inter alia_ have brought to the fore the importance of better understanding gender inequalities. We offer new analysis on the feminization of poverty as related to FHHs, using 20 survey rounds spanning the past two decades for six countries across the Arab region— namely Egypt, Iraq, Jordan, Mauritania, the West Bank and Gaza, and Tunisia—an understudied set of countries. We propose and evaluate a new typology of FHHs consisting of four main types (and several sub-types) of FHHs with a new focus on the presence of children, which offers policyrelevant insights regarding the trends and dynamics of poverty feminization. We assemble and harmonize the available cross-sectional data and construct synthetic panels to address the lack of actual panels.

We find that different FHH types display clear differences regarding poverty levels and trends. In particular, self-reported FHHs, potential FHHs, and most-educated-female-adult FHHs are less likely to be poor than non-FHHs for the six countries, while the opposite holds for majority-female-

> 16 While Milazzo and Van de Walle (2017) find self-reported FHHs to be generally poorer, they also find these households to contribute more to the overall decline in poverty in Africa.

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adult FHHs. Yet, more children are associated with more poverty for the former three types of FHHs and less poverty for the last type of FHHs.

We also find considerable (conditional) upward mobility, ranging between 21 and 54 percent of the initially poor in a country. But country heterogeneity exists, with Iraq, Jordan, and Mauritania having relatively more upward mobility, while Egypt, the West Bank and Gaza, and Tunisia have relatively less upward mobility. While most types of FHHs more likely experience upward mobility out of poverty (or less likely fall into poverty), FHHs without children have the strongest upward mobility (or the least downward mobility), followed by FHHs with children, and non-FHHs.

Our proposed typology aligns with recent calls to go beyond identifying headship based on the gender of the head alone. For example, Beegle and van de Walle (2019) argue that since many women live in MHHs, especially in Sub-Saharan Africa, if resources are unequally shared among household members, simply comparing FHHs and MHHs based on heads’ gender can provide biased results. Summarizing opinions from experts on gender issues and survey design on the topic, Buvinic and van de Walle (2019) similarly call for other definitions based on other household characteristics including demographic and gender composition. Other concerns were also raised about practical survey challenges with headship (e.g., when the male head temporarily lives away from the household).

These discussions do not just serve academic purposes but have practical policy implications. Governments in the region strive to identify various vulnerable FHHs for effective socialprotection interventions aimed at targeting vulnerable groups and reducing gender inequalities. For example, Egypt’s largest poverty-targeting cash-transfer program, Takaful, uses proxy means testing to target households and the criteria include a much lower threshold for FHHs. In 2017, the 26
poverty threshold used to determine eligibility was raised considerably for MHHs while it was kept constant for FHHs (ESCWA, 2021), resulting in the share of beneficiaries who were FHHs almost doubling from 48% to 92%. In Jordan, the National Aid Fund targets several categories of “vulnerable” FHHs such as widows with children, those without “support”, and divorced female heads, not just poor FHHs, while its poverty-reduction program directly targets poor FHHs (NAF, 2020; ESCWA, 2021; World Bank, 2022). In Lebanon, and Tunisia, FHHs, especially widows, are also prioritized (Nasri, 2020; ESCWA, 2021).

Against this background, our findings offer highly relevant policy inputs and run against the conventional wisdom that FHHs are typically poorer than non-FHHs, which appears to be the implicit assumption underlying many targeting programs in the region and elsewhere. In contrast, we find majority-female-adult households or households with more children more vulnerable to (remaining in) poverty. While these results suggest that female headship definition using gender composition can offer an alternative approach—and potentially help identify a more vulnerable group—for poverty targeting, they also highlight the need for a more nuanced understanding of how female headship can be defined, especially in the presence of children. Furthermore, we also need to better understand the extent to which the different types of FHHs’ exposure to poverty can change, depending on various other factors such as whether we examine households’ static or dynamic poverty status, whether other household demographic and employment characteristics are considered, and last but not least, the country-specific contexts.

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# **Table 1. Share of Female-Headed Households in Six Arab Countries (percentages)**

|||**Egypt, **|**Arab Rep.**|||**Iraq**|**Jo**|**rdan**||**Mau **|**ritania**|||**West Ban**|**k and Gaza**|||**T**|**unisia**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||2012|2015|2017|2020|2007|2012|2010|2013|2004|2008|2014|2019|2007|2009|2011|2017|2005|2010|2015|2021|
|**Te 1 Self-reorted FHH**|**17.80**|**17.86**|**18.43**|**17.59**|**11.30**|**9.63**|**13.88**|**13.24**|**18.92**|**31.30**|**30.19**|**36.58**|**9.12**|**10.00**|**11.07**|**10.05**|**17.01**|**14.85**|**16.24**|**18.52**|
|**yp . p**|_1,346_|_2,104_|_2,265_|_1,967_|_1,906_|_2,531_|_402_|_669_|_1,860_|_4,273_|_3,033_|_3,654_|_108_|_388_|_505_|_397_|_2,128_|_1,704_|_4,088_|_3,153_|
|Offiil FHH|13.98|14.96|15.92|14.03|10.43|8.22|11.29|11.05|16.89|18.90|17.23|16.98|8.26|8.79|9.93|8.04|13.73|11.95|14.12|16.62|
|ca|_1,058_|_1,741_|_1,956_|_1,599_|_1,721_|_2,152_|_335_|_592_|_1,674_|_2,688_|_1,839_|_1,834_|_97_|_341_|_447_|_308_|_1,671_|_1,347_|_3,462_|_2,788_|
|N id|0.48|0.37|0.48|0.59|0.46|0.20|0.89|0.89|0.44|0.45|0.50|0.60|0.59|1.07|1.09|0|1.01|0.56|1.29|1.51|
|ever marre|_35_|_43_|_57_|_67_|_78_|_101_|_17_|_43_|_44_|_67_|_48_|_72_|_7_|_45_|_56_|_0_|_113_|_65_|_282_|_261_|
|Did/ td|0.95|1.33|1.55|1.80|0.78|0.62|0.51|0.66|6.15|6.98|6.22|6.64|0.99|0.65|1.14|0.82|1.28|1.18|1.53|1.90|
|vorce separae|_74_|_153_|_194_|_210_|_120_|_175_|_19_|_33_|_602_|_974_|_660_|_690_|_11_|_25_|_43_|_29_|_156_|_131_|_360_|_291_|
|Wid l|12.56|13.26|13.89|11.64|9.19|7.40|9.90|9.50|10.29|11.47|10.52|9.74|6.68|7.07|7.70|7.22|11.44|10.21|11.29|13.21|
|ow ony|_949_|_1,545_|_1,705_|_1,322_|_1,523_|_1,876_|_299_|_516_|_1,028_|_1,647_|_1,131_|_1,072_|_79_|_271_|_348_|_279_|_1,402_|_1,151_|_2,820_|_2,236_|
|Mid FHH|3.80|2.89|2.52|3.53|0.87|1.41|2.58|2.19|1.92|12.20|12.96|18.45|0.87|1.22|1.14|2.01|3.28|2.90|2.12|1.91|
|arre|_287_|_363_|_309_|_365_|_185_|_379_|_67_|_77_|_176_|_1,558_|_1,194_|_1,714_|_11_|_47_|_58_|_89_|_457_|_357_|_624_|_365_|
|**T 2 Sh f fl dlt>05**|**22.96**|**22.29**|**22.46**|**20.87**|**24.02**|**28.92**|**25.80**|**22.80**|**31.50**|**40.40**|**39.98**|**43.96**|**21.52**|**19.53**|**20.97**|**24.28**|**29.20**|**28.98**|**26.17**|**27.21**|
|**ype . are o emae aus.**|1,712|2,659|2,797|2,352|4,547|6,525|728|1,105|_3,075_|_5,606_|_3,897_|_4,393_|265|751|919|955|3,710|3,363|_6,907_|_4,740_|
|Share of employed females> share of|**5.42**|**6.22**|**6.12**|**6.02**|**4.81**|**3.81**|**6.02**|**7.56**|**11.40**|**12.90**|**14.30**|**14.68**|**7.65**|**6.72**|**6.54**|**4.59**|**10.94**|**9.01**|**10.17**|**11.04**|
|employed males|_406_|_733_|_757_|_660_|_916_|_1,070_|_178_|_291_|_1,056_|_1,888_|_1,422_|_1,454_|_88_|_269_|_300_|_176_|_1,313_|_987_|_2,382_|_1,854_|
|**T 3 Pttil FHH**|**16.68**|**16.49**|**19.37**|**18.86**|**5.73**|**3.59**|**13.25**|**12.78**|**17.01**|**27.09**|**25.02**|**27.88**|**11.09**|**10.35**|**10.55**|**9.88**|**18.30**|**17.54**|**18.13**|**26.75**|
|**ype . oena**|_1,244_|_1,935_|_2,344_|_2,087_|_1,007_|_1,621_|_359_|_576_|_1,643_|_3,694_|_2,345_|_2,824_|_127_|_398_|_482_|_397_|_2,280_|_1,974_|_4,609_|_4,618_|
||3.06|3.17|3.49|3.75|1.65|0.86|2.52|3.52|7.07|8.07|9.68|9.12|3.04|2.34|2.84|1.82|5.07|4.11|4.27|5.67|
|Core FHH|_229_|_364_|_419_|_407_|_283_|_388_|_77_|_129_|_635_|_1,160_|_939_|_912_|_34_|_97_|_130_|_74_|_620_|_457_|_1,022_|_947_|
||11.77|11.70|14.05|13.10|4.00|2.61|12.02|10.90|14.85|24.30|22.63|24.67|9.24|8.76|8.52|N.A.|15.56|15.55|15.22|N.A.|
|Asset FHH|_881_|_1,459_|_1,765_|_1,489_|_783_|_1,258_|_321_|_510_|_1,417_|_3,287_|_2,095_|_2,523_|_106_|_338_|_402_|_N.A._|_1,967_|_1,769_|_4,037_|_N.A._|
|**Type 4. Most educated adult member**|**12.92**|**13.88**|**14.30**|**13.98**|**8.54**|**5.87**|**18.49**|**18.48**|**8.76**|**16.47**|**13.83**|**24.67**|**16.87**|**15.25**|**14.82**|**11.52**|**15.42**|**17.75**|**17.84**|**20.11**|
|**is female & no employed males**|_951_|_1,610_|_1,749_|_1,554_|_1,485_|_1,990_|_499_|_932_|_969_|_2,384_|_1,378_|_2,490_|_201_|_595_|_643_|_419_|_1,936_|_2,024_|_4,479_|_3,520_|

Note: The main definitions of female-headed households are in bold, and the variant definitions are in regular font. The numbers in bold refer to the percent of the cross-sectional sample for each period. The numbers in _italics_ refer to the sample size of each group. Type 1 _self-reported FHHs_ are obtained from self-reporting information in the survey questionnaires. Type 2 _majority-female-adult FHHs_ are defined as households where the proportion of females among (working age) adults exceeds 0.5. Type 3 _potential FHHs_ are those households where there are no working-age males present. Type 4 _most-educated-female-adult FHHs_ consist of households with no employed males, whose most educated adult member is female. Under Type 1 FHHs, the different sub-types are defined as in the survey questionnaires. Under Type 3 FHHs, sub-type 3 _core FHH_ encompasses only the potential FHHs with employed females, and sub-type 3 _asset FHH_ encompasses only households with females who have ownership rights over the dwellings they reside in.

33
# **Table 2. Probabilities of Being Poor**

|||**Specific**|**ation 1**|||**Specificatio**|**n 2**||
|---|---|---|---|---|---|---|---|---|
|||**FHH Type 2**||**FHH Type 4**||||**FHH Type 4**|
||**FHH Type 1**<br>**Self-reported**|<br>**Majority-female-**<br>**adult**|**FHH Type 3**<br>**Potential**|<br>**Most-educated-**<br>**female-adult**|**FHH Type 1**<br>**Self-reported**|**FHH Type 2**<br>**Majority-female-adult**|**FHH Type 3**<br>**Potential**|<br> <br>**Most-educated-**<br>**female-adult**|
|Self-reported FHH|-0.007***<br>(0.00)||||-0.044***<br>(0.00)||||
|Self-reported FHH # Number of children|0.008***<br>(0.00)||||0.006***<br>(0.00)||||
|Share of female adults>0.5||0.052***<br>(0.00)||||0.032***<br>(0.00)|||
|Share of female adults>0.5# Number of||<br>-0.007***||||<br>-0.014***|||
|children||(0.00)||||(0.00)|||
||||-0.027***|||-0.017***|||
|Potential FHH|||(0.00)|||(0.00)|||
||||0.014***|||0.011***|||
|Potential FHH# Number of children|||(0.00)|||(0.00)|||
|Educated females||||0.002<br>(0.00)||||-0.006**<br>(0.00)|
|Educated females# Number of children||||<br>0.013***<br>(0.00)||||<br>0.013***<br>(0.00)|
|Household head`s|||||||||
|characteristics|N|N|N|N|Y|Y|Y|Y|
|Household characteristics|N|N|N|N|Y|Y|Y|Y|
|Country FE|Y|Y|Y|Y|Y|Y|Y|Y|
|<br>Survey year FE|Y|Y|Y|Y|Y|Y|Y|Y|
|N|214931|214931|214931|214931|211069|211069|211069|211069|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Robust standard errors are in parentheses. The full regression results using the linear probability model are provided in Appendix A, Table A.10.

34
<!-- Start of picture text --> Female-headed household Typology<br>“De jure” FHH “De facto” FHH<br>Self-reported approach Demographic approach Socio-economic approach<br>Mei Type 3: Potential FHH | Type4: Mosteducated member<br>Type 1: Self-reported Type 2: Major share of (no working-age male) wanetip i the household is female,<br>an females in HH Fuwa (2000) , ~ where no working-age<br>DeGraff and Bilsborrow(1993) Milazzo and van de Walle (2017)... employed male ispresent<br>Quisumbing et al. (2001) a ? \<br>Core FAH<br>mart seus (or Married FHH employedNumber/ femalesShai scot FHH (femae' is engoged<br>reason for spouse's Liu et al. (2017) (earners) Deere et ol generating<br>absence) Brown and Van de Bibi and Chatti (2012) activities)<br>Buvinic and Gupta Walle (2021) M Goto eral Fuwa {2000)<br>wtasenat (2025) (ois) Rogan (2013)<br><!-- End of picture text -->
# **Figure 2. Cross-sectional Headcount Poverty Rate (percentage), by Household Type, Regional Poverty Lines**

<!-- Start of picture text --> Egypt Iraq<br>2012 2015 2017 2020 2007 2012<br>Jordan Mauritania<br>2010 2013 2004 2008 2014 2019<br>Palestine Tunisia<br>2007 2009 2011 2017 2005 2010 2015 2021<br>Whole population Self-reported FHH Share of females>0.5<br>Potential FHH Educated females<br>35 30<br>30<br>25<br>25<br>20 20<br>15<br>Poverty rate (%) 15 Poverty rate (%)<br>30 60<br>25<br>50<br>20<br>40<br>15<br>10 30<br>Poverty rate (%)5 20 Poverty rate (%)<br>100 30<br>80 25<br>60 20<br>40 15<br>10<br>Poverty rate (%)20 Poverty rate (%)<br><!-- End of picture text --> Note: Population sampling weights are applied.

36
**Figure 3. FHH–non-FHH Differences in Headcount Poverty Rate (percentage points)**

Panel A: Self-reported FHH Panel B: Share of females>0.5 <!-- Start of picture text --> 2012201520172020 ****** *** *** *** *** *** 2012201520172020<br>20072012 *** * ** 20072012<br>20102013 * ** *** 20102013<br>2004200820142019 *** *** *** ** ********* 2004200820142019<br>2007 2007<br>200920172011 *** ** ** *** 200920112017<br>2005201020152021 ******** *** * * * ** ****** 2005201020152021<br>-5 0 5 10<br>-15 -10 -5 0 5<br>Panel C: Potential FHH Panel D: Educated females<br>2012201520172020 *** *** *** ** * ****** *** ** * 2012201520172020<br>20072012 * * ** 20072012<br>20102013 ** * * * * ** *** 20102013<br>2004200820142019 **** ** * ********* ** * 2004200820142019<br>2007200920172011 *** ****** *** ** *** *** 2007200920112017<br>2005201020152021 ** * ** * * * *** *** 2005201020152021<br>-40 -30 -20 -10 0 -20 -10 0 10<br>Egypt Egypt<br>Iraq Iraq<br>Jordan Jordan<br>Mauritania Mauritania<br>Palestine Palestine<br>Tunisia Tunisia<br>Egypt Egypt<br>Iraq Iraq<br>Jordan Jordan<br>Mauritania Mauritania<br>Palestine Palestine<br>Tunisia Tunisia<br><!-- End of picture text -->

**Note:** Headcount poverty rates are estimated using per capita household expenditures. Stars indicate significantly higher headcount poverty ratio between FHHs and non-FHHs in each category. ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Negative difference means FHHs are less likely to be poor.

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# **Figure 4. Differences in Headcount Poverty Rate for FHHs vs. non-FHHs by Number of Children under 14 (percentage points)**

<!-- Start of picture text --> Panel A: Self-reported FHH Panel B: Share of females>0.5<br>Egypt Egypt<br>Iraq Iraq<br>Jordan Jordan<br>Mauritania Mauritania<br>Palestine Palestine<br>Tunisia Tunisia<br>-10 0 10 20 30 40 -10 0 10 20 30<br>Panel C: Potential FHH Panel D: Educated females<br>Egypt Egypt<br>Iraq Iraq<br>Jordan Jordan<br>Mauritania Mauritania<br>Palestine Palestine<br>Tunisia Tunisia<br>-20 0 20 40 -20 0 20 40<br>0 1 2 3 4 or more<br><!-- End of picture text -->

**Note:** Authors’ calculation based on pooled cross section. Headcount poverty rates are estimated using per capita household expenditures. The number of children are shown for 0, 1, 2, 3, and 4 or more children. The headcount poverty rates are shown on the x-axis, with positive numbers indicating more poverty for FHHs. The error bars are the 95% CIs.

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# **Figure 5. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH wo/children FHH w/children Non-FHH<br>40 60<br>55<br>35<br>50<br>30<br>45<br>Percentage (%) Percentage (%)<br>25 40<br>60 50<br>55 45<br>50<br>40<br>Percentage (%) 45 Percentage (%)<br>35<br>30<br>45<br>40 25<br>35<br>20<br>30<br>Percentage (%) Percentage (%)<br>25 15<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

39
# **Figure 6. Probabilities of Female-Headed Households Falling in Poverty in Second Year Conditional on Being Non-poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH wo/children FHH w/children Non-FHH<br>14<br>16<br>14 12<br>12 10<br>10 8<br>Percentage (%) 8 6 Percentage (%)<br>14 16<br>12 14<br>10 12<br>8 10<br>Percentage (%) 6 8 Percentage (%)<br>55 10<br>50 9<br>45 8<br>40 7<br>35 6<br>Percentage (%) 30 5 Percentage (%)<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that enters poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

40
# **Appendix A: Additional Tables and Figures**

# **Table A.1. Overview of the key studies**

||**Studies**|**Country**|**FHH**<br>**definition**|**Reference**<br>**group**|**Conclusions**|
|---|---|---|---|---|---|
||||Self-<br>reported<br>FHH|Self-<br>reported<br>MHH<br>|FHHs have lower income, land ownership, and average level of education than<br>MHHs and are less likely to be employed (with fewer hours if employed). Children<br>of FHHs are significantly less likely to be enrolled in school than children of MHHs.|
|1|DeGraff and<br>Bilsborrow (1993)|Ecuador|Self-<br>reported<br>widowed<br>FHH|Self-<br>reported<br>MHH, other<br>self-reported<br>FHH|Widowed or divorced FHHs have higher income and amount of land owned than<br>MHHs but lower children's school enrollment and are less likely to be in school<br>than are children of MHHs and children of other FHHs.|
||||Self-<br>reported<br>married<br>FHH|Self-<br>reported<br>MHH, other<br>self-reported<br>FHH|Married FHHs have lower income and amount of land owned than MHHs and<br>enrollment rate similar to MHH, but children of married FHHs are significantly less<br>likely to be enrolled in school than are children of MHHs but more likely than<br>widowed FHHs.|
|2|Buvinic and Gupta<br>(1997)|65 studies<br>on<br>developing<br>countries|Self-<br>reported<br>FHH, de<br>facto, de<br>jure FHH|Self-<br>reported<br>MHH|Thirty-eight studies - FHHs are poorer than MHHs when poverty is measured by<br>(total/per capita/per equivalent) household income and consumption expenditures,<br>access to services, and ownership of land and assets. Fifteen studies - certain types<br>of FHHs are more vulnerable to poverty than others. Eight studies – poverty in<br>FHHs is not higher than in MHH.|
||||Self-<br>reported<br>FHH|Self-<br>reported<br>MHH|FHHs are similar to MHHs when poverty is measured by per capita expenditure.<br>The difference between FHHs versus non-FHHs does not change if using different<br>poverty indicators.|
||||Self-<br>reported de<br>jure, de<br>facto FHH|Non-FHH|Widows/divorced/separated FHHs have significantly higher headcount poverty in<br>indigenous areas when poverty is measured by per capita expenditure. FHHs have<br>lower education than non-FHHs|
|3|Fuwa (2000)|Panama|Self-<br>reported<br>married<br>FHH, FHH<br>with<br>unmarried<br>partners|Non-FHH|FHHs with unmarried partners have higher headcount poverty ratios in urban and<br>indigenous areas when poverty is measured by per capita expenditure. The result is<br>robust to applying an equivalence scale using alternative poverty measures and<br>poverty lines.|
||||<br>Potential<br>FHH|Non-FHH|FHHs are not poorer than non-FHHs when poverty is measured by per capita<br>expenditure.|
||||“Working”<br>FHHs|Non-FHH|FHHs are similar to non-FHHs when poverty is measured by per capita expenditure.<br>FHHs have higher education endowments than non-FHHs, except in indigenous<br>areas.|

41
||||core FHH|Non-FHH|FHHs are less poor than non-FHHs when poverty is measured by per capita<br>expenditure.|
|---|---|---|---|---|---|
|4|Quisumbing_et al._<br>(2001)|10<br>developing<br>countries|Self-<br>reported<br>FHH,<br>females|Self-<br>reported<br>MHH, males|FHHs and individual females contribute disproportionately to overall poverty in 25-<br>50% of the dataset when headcount poverty is measured by (total/per capita/per<br>equivalent) household income and consumption expenditures and are insensitive to<br>the poverty line. FHHs and individual females are similar to MHHs or males when<br>using stochastic dominance criteria, but they are constantly worse off in Ghana and<br>Bangladesh.|
|5|Horrell and Krishnan<br>(2007)|Zimbabwe|Self-<br>reported<br>widowed<br>FHH|Self-<br>reported|The income per capita/ adult equivalent is lower in widowed FHHs than in the<br>MHHs.|
||||Self-<br>reported de-<br>facto FHH|MHH|The income per capita/ adult equivalent is higher in the de facto FHHs than in the<br>MHHs.|
|6|Medeiros and Costa<br>(2007)|8 Latin<br>American<br>ti|FHH,<br>females|MHH, males|Poverty is higher among FHHs, but there is no clear evidence of a recent and<br>widespread feminization of poverty in Latin America. Differences in poverty<br>among FHHs and MHHs increased in Argentina and Mexico, showing specific<br>types of feminization of poverty. The results are robust to different values of<br>poverty lines, the use of equivalence scales, and the distribution of household<br>income.|
|||counres|Self-<br>reported<br>FHH w/o<br>children|Couple HH<br>w/o children|The insignificant increase in poverty indices when comparing FHHs without<br>children to couple-headed HH without children in Bolivia. The rise in poverty<br>indices is significant at 5% when comparing FHHs with children to MHHs with<br>children in Costa Rica.|
|7|Deere_et al._(2012)|Latin<br>American<br>countries|HHs where<br>women have<br>ownership<br>rights|Self-<br>reported<br>FHHs who<br>have<br>ownership<br>rights|The gender of the household head is a poor substitute for a gendered analysis of<br>asset ownership within and among households since an analysis based on headship<br>tends to underestimate women’s ownership of assets.|
|8|Van de Walle (2013)|Mali|Self-<br>reported<br>widowed<br>FHH<br>Self-<br>reported<br>widowed<br>MHH|Self-<br>reported<br>married<br>FHH<br>Self-<br>reported<br>married<br>MHH|Widowed FHHs have significantly lower consumption per capita than married<br>FHHs, while MHHs do not have any significant differences in per capita<br>consumption between widowed MHHs and married MHHs.|
||||Self-<br>reported<br>widowed<br>FHH rural|Self-<br>reported<br>widowed<br>FHH urban|Widowed FHH living in rural areas have lower per capita consumption than all<br>other households living in rural areas. The gap between widowed FHHs and other<br>HHs is lower for HHs residing in urban areas.|

42
|||Self-<br>reported<br>widowed<br>FHH rural|Self-<br>reported<br>non-<br>widowed<br>FHH rural|Per capita consumption of widowed FHHs is around 12% lower than that of all rural<br>households. The results are robust to using an equivalence scale in measuring<br>consumption.|
|---|---|---|---|---|
|||Self-<br>reported<br>widowed<br>FHH urban|Self-<br>reported<br>non-<br>widowed<br>FHH urban|Per capita consumption of widowed FHHs is around 6% lower than that of all other<br>urban households. The results are robust to using an equivalence scale in measuring<br>consumption.|
|9<br>Rogan (2013)|South<br>Afi|Self-<br>reported de<br>jure FHH,<br>de facto<br>FHH, co-<br>resident<br>FHH|Self-<br>reported<br>MHH|Poverty rates are higher in FHHs than in MHHs, irrespective of how headship is<br>defined.|
||rca|Self-<br>reported de<br>jure FHH,<br>de facto<br>FHH|co-resident<br>FHH|Co-resident FHHs are less poor than other types of FHHs.|
|||core FHH|non-FHH|FHH has the lowest risk of poverty|
|||Self-<br>reported<br>FHH|Self-<br>reported<br>MHH|No significant differences between FHHs and MHHs were found regarding<br>consumption, the probability of shock exposure, or vulnerability to poverty in<br>Thailand or Viet Nam.|
|||Self-<br>reported de-<br>jure FHH|Self-<br>reported<br>MHH|De jure FHHs have lower consumption than MHHs in Viet Nam. There are no<br>significant differences between de-jure FHHs and MHHs regarding the probability<br>of shock exposure or vulnerability to poverty in Thailand or Viet Nam.|
|10<br>Klasen_et al._(2015)|Thailand,<br>Viet Nam|Self-<br>reported de-<br>facto FHH|Self-<br>reported<br>MHH|De facto FHHs have higher consumption than MHHs in Thailand. There are no<br>significant differences between de-facto FHHs and MHHs regarding the probability<br>of shock exposure or vulnerability to poverty in Thailand or Viet Nam.|
|||Self-<br>reported<br>single,<br>widowed<br>FHH|Self-<br>reported<br>MHH|FHHs with an absent spouse have higher consumption levels than MHHs in<br>Thailand. Single FHH has a lower consumption level than Viet Nam. There are no<br>significant differences between FHHs and MHHs regarding the probability of any<br>shock exposure in Thailand or Viet Nam. Single FHHs are less vulnerable to<br>poverty in Thailand but more vulnerable to poverty in Viet Nam.|
|11<br>Liu_et al._(2017)|14 Latin<br>American<br>countries|Self-<br>reported<br>married w/o<br>spouse,<br>single,<br>separated,|Self-<br>reported<br>married<br>FHH with<br>spouse|In eight of the 14 countries, FHHs are more likely to live in poor conditions.<br>However, MHHs are in more impoverished conditions than FHHs when married<br>status, urban or rural setting, ownership, and the presence of children are controlled<br>in the regression. Generally, married FHHs with the spouse present are better off<br>than any other category. The worst living conditions are associated with single,<br>separated, divorced, or widowed FHHs.|

43
||||widowed<br>FHH|||
|---|---|---|---|---|---|
|||20<br>countries in|Self-<br>reported<br>FHH|Self-<br>reported<br>MHH|While the share of FHHs in the population is growing during 1990-2012, poverty<br>has been falling faster among FHHs. FHHs contributed more to the overall decline<br>in poverty despite their smaller overall population share.|
|12|Milazzo and van de<br>Walle (2017)|<br>Sub-<br>Saharan<br>Africa|Self-<br>reported<br>FHH w/o a<br>resident<br>adult male|Self-<br>reported<br>MHH|The poverty trends of the various types of FHHs followed different paths across<br>countries and periods, with no one type consistently outperforming the others.|
|13|Alazzawi (2018)|Egypt,|Self-<br>reported<br>urban FHH<br>with<br>children|Self-<br>reported<br>urban MHH<br>with<br>children|FHHs have a higher predicted poverty rate than MHHs in urban areas. The factors<br>contributing to the poverty differential between FHH and MHH households are<br>education, employment status, occupation, sector, and region of residence.|
|||Arab Rep.|Self-<br>reported<br>rural FHH<br>with<br>children|Self-<br>reported<br>rural MHH<br>with<br>children|FHHs have a higher predicted poverty rate than MHHs in rural areas. Education,<br>employment status, occupation, number of rooms per capita, and region of<br>residence are factors that contribute to the poverty differential between FHHs and<br>MHHs|
|14|Munoz Boudet_et al._<br>(2018)|71<br>developing|couple/singl<br>e females<br>w/o children|other HH|Adult couple households with children, children, and other adults (extended<br>family) are the most frequent among poor households. Poor and non‐poor women<br>concentrate in the adult couple household with children. One adult female<br>household with children is more prevalent among the poor in Latin America, the<br>Caribbean, and Sub‐Saharan Africa.|
|||countries|Male/female<br>earner with<br>and w/o<br>children||Poor women live in households with children and with children and earner<br>dependents, where the earner is a single male or a head couple. Single female-<br>earner households comprise the largest percentage of poor households in Latin<br>America, the Caribbean, and Sub‐Saharan Africa.|
||B d V d|43 Afi|Self-<br>reported<br>FHH|Self-|FHHs have lower poverty rates than MHHs when using per capita welfare<br>measures. FHHs are significantly worse than MHH when poverty is measured<br>using consumption adjusted for economies of scale.|
|15|rown an an e<br>Walle (2021)|rcan<br>countries|Self-<br>reported<br>married<br>FHH|reported<br>MHH|MHHs are poorer than married FHHs|

44
# **<u>Table A.2. Poverty Line, Arab Republic of Egypt by Region, in LCU, Per Capita Annual Consumption in Survey Year Prices</u>**

|||**Food**<br>|**poverty line**<br>|||**Po**<br>|**verty line**<br>||
|---|---|---|---|---|---|---|---|---|
|**Region**|**2012/2013**|**2015**|**2017/2018**|**2019/2020**|**2012/2013**|**2015**|**2017/2018**|**2019/2020**|
|**Urban governorates**|2748|4318|6065.3|7071|4320|6141|9280.1|11285|
|**Urban lower Egypt**|2484|3835|5667.6|6304|3840|5631|8536.9|9755|
|**Rural lower Egypt**|2568|3854|5901.7|6570|3852|5675|8673|10108|
|**Urban upper Egypt**|2568|3968|5752.1|6553|3972|5823|8728.5|10225|
|**Rural upper Egypt**|2496|3760|5896.5|6484|3756|5694|8865.6|10068|
|**Urban frontier**|2736|3990|5924.3|6696|3996|6247|8568.7|10409|
|**Rural frontier**|2688|3979|6304.7|7074|3984|5788|8979.3|10788|
|**Total**|2568|3921|5889.6|6604|3924|6141|8827|10279|

Source: Compiled from various CAPMAS Poverty assessment updates.

45
# **<u>Table A.3. Poverty Lines, Jordan, in LCU, Per Capita Annual Consumption in Survey Year Prices</u>**

||**Food poverty line**|**Poverty li**|**ne**|
|---|---|---|---|
||2010<br>2013|2010|2013|
|**Jordan**|336<br>383|814|929|

Source: Jordan Department of Statistics: DOS https://jorinfo.dos.gov.jo/Databank/pxweb/en/Poverty/Poverty__Poverty-Indicators/ 46
# **<u>Table A.4. Poverty Lines, Iraq, in LCU, Per Capita Annual Consumption in Survey Year Prices</u>**

||2007|2012|
|---|---|---|
|**Kurdistan**|1212|1709|
|**Baghdad**|987|1391|
|**Rest of Iraq**|865|1220|
|**Total**|1073|1266|

Source: World Bank “Poverty Estimates and Trends in Iraq” <u>https://microdata.worldbank.org/index.php/catalog/2334/download/34771</u> 47
# **<u>Table A.5. Poverty Lines, the West Bank and Gaza, in LCU, Per Capita Annual Consumption in Survey Year Prices</u>**

||**Food**|**poverty line**||**Po**|**verty line**||
|---|---|---|---|---|---|---|
||2009|2011|2017|2009|2011|2017|
|**Gaza**|567|570|567|712|714|710|
|**West Bank**|609|632|710|765|792|889|
|**Total**|603|620|668|757|776|836|

Source: Compiled from various PCBS poverty reports. Spatial deflator provided by PCBS was used to calculate regional poverty lines for Gaza and the West Bank relative to the national poverty line available from PCBS publications.

48
|**Table A.6. Poverty Lines, Tunisi**|**a, in LCU, Per C**<br>**Food**<br>|**apita Annua**<br>**poverty line**<br>|**l Consumptio**<br>|**n in Survey Y**<br>|**ear Prices**<br>**P**<br>|**overty line**<br>|||
|---|---|---|---|---|---|---|---|---|
||2005|2010|2015|2021|2005|2010|2015|2021|
|**Cities (metropolitan)**|615|757|1085|1346.526|902|1038|1878|2682.997|
|**Small & medium towns (urban)**|596|733|1050.154|--|818|941|1702.871|--|
|**Noncommunal (rural)**|466|571|951.668|1529.233|581|669|1500.530|2223.527|

Source: World Bank (2016). “Tunisia Poverty Assessment 2015”. Table A1.3.

49
# **<u>Table A.7. Poverty Lines, Mauritania, in LCU, Per Capita Annual Consumption in Survey Year Prices</u>**

||**Extreme poverty line**|||**Pove**|**rty line**||
|---|---|---|---|---|---|---|
||**2004**|**2008**|**2004**|**2008**|**2014**|**2019**|
|**Total**|70400|96000|94650|129000|169445|191000|

Source: IMF (2011) Table 1.1.

50
# **<u>Table A.8. Correlation between Main Types of Female-Headed Households</u>**

||**FHH Type 1**<br>**Self-reported**|**FHH Type 2**<br>**Majority-female-adult**|**FHH Type 3**<br>**Potential**|**FHH Type 4**<br>**Most-educated-female-adult**|
|---|---|---|---|---|
|**FHH Type 1**|1.000|0.265***<br>(0.000)|0.415***<br>(0.000)|0.298***<br>(0.000)|
|**FHH Type 2**||1.000|0.319***<br>(0.000)|0.304***<br>(0.000)|
|**FHH Type 3**|||1.000|0.510***<br>(0.000)|
|**FHH Type 4**||||1.000|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels.

51
**-** **<u>Table A.9. Headcount Poverty Rate of Female and Non female Headed Households by Headship Definition (percent)</u>**

||Egypt,|Arab Rep.|||||Mauritani|a (2004-2019)|West Ban|k and Gaza|||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(2012|-2020)|Iraq (2|007-2012)|Jordan (2|010-2013)|||(2007|-2017)|Tunisia (|2005-2021)|
||FHH|<br>non-FHH|<br>FHH|<br>non-FHH|<br>FHH|<br>non-FHH|FHH|non-FHH|FHH|<br>non-FHH|<br>FHH|<br>non-FHH|
|**_Panel A: All_**|||||||||||||
|Self-Reported FHH|23.32|32.01<sup>*</sup>|20.22|24.79<sup>*</sup>|14.46|14.94|29.52|38.03<sup>*</sup>|50.63|59.70<sup>*</sup>|16.04|17.34<sup>*</sup>|
|Reported de jure FHH|21.51|31.92<sup>*</sup>|19.24|24.80<sup>*</sup>|16.08|14.80|29.66|36.80<sup>*</sup>|48.17|59.73<sup>*</sup>|13.46|17.57<sup>*</sup>|
|Reported married FHH|29.15|31.01|25.96|24.36|7.76|15.03<sup>*</sup>|28.35|36.73<sup>*</sup>|62.71|59.10|26.55<sup>*</sup>|16.96|
|<br>Potential FHH|17.41|32.41<sup>*</sup>|22.28|24.43|8.42|15.35<sup>*</sup>|31.43|36.80<sup>*</sup>|35.30|60.18<sup>*</sup>|13.46|17.69<sup>*</sup>|
|Core FHH|19.53|31.25<sup>*</sup>|15.41|24.43<sup>*</sup>|4.16|15.11<sup>*</sup>|30.47|36.17<sup>*</sup>|34.38|59.47<sup>*</sup>|13.41|17.32<sup>*</sup>|
|Asset FHH|16.33|32.05<sup>*</sup>|21.76|24.42|8.38|15.30<sup>*</sup>|32.88|36.37<sup>*</sup>|39.06|59.69<sup>*</sup>|15.78|17.28<sup>*</sup>|
|Share of female adults>0.5|29.62|31.32<sup>*</sup>|25.94<sup>*</sup>|23.64|17.15<sup>*</sup>|14.19|37.36<sup>*</sup>|34.61|62.04<sup>*</sup>|58.33|19.10<sup>*</sup>|16.42|
|Share of employed<br>females>employed males|22.3|31.44<sup>*</sup>|22.11|24.48<sup>*</sup>|7.48|15.37<sup>*</sup>|33.11|36.18<sup>*</sup>|54.89|59.38<sup>*</sup>|16.68|17.24|
|Most educated member is female<br>adult & no employed males|20.43|32.11<sup>*</sup>|29.12<sup>*</sup>|24.17|21.87|13.61|27.55|37.22<sup>*</sup>|64.52<sup>*</sup>|58.46|18.15<sup>*</sup>|17.01|
|<br>**_Panel B: Rural_**|||||||||||||
|Self-Reported FHH|28.16|37.9<sup>*</sup>|36.29|35.34|13.20|17.70|32.42|44.98<sup>*</sup>|45.81|56.02<sup>*</sup>|23.95|25.50|
|Reported de jure FHH|25.89|37.69<sup>*</sup>|34.15|35.45|13.55|17.61|33.94|43.01<sup>*</sup>|42.56|56.07<sup>*</sup>|18.79|25.85<sup>*</sup>|
|Reported married FHH|32.87|36.92<sup>*</sup>|43.82<sup>*</sup>|35.28|11.18|17.39|30.16|43.30<sup>*</sup>|61.12|55.38|33.52<sup>*</sup>|24.98|
|Potential FHH|22.05|38.24<sup>*</sup>|38.52|35.33|15.50|17.41|33.14|44.18<sup>*</sup>|37.66|56.25<sup>*</sup>|22.28|25.77<sup>*</sup>|
|Core FHH|25.67|37.00<sup>*</sup>|28.11|35.42|1.93|17.50<sup>*</sup>|34.21|42.46<sup>*</sup>|37.72|55.73<sup>*</sup>|22.96|25.41|
|Asset FHH|20.52|38.07<sup>*</sup>|38.85|35.34|12.51|17.54|33.88|43.83<sup>*</sup>|40.33|55.89<sup>*</sup>|24.28|25.42|
|Share of female adults>0.5|36.19|36.9|38.08<sup>*</sup>|33.89|21.37<sup>*</sup>|16.00|42.93<sup>*</sup>|40.94|60.23<sup>*</sup>|54.05|27.51<sup>*</sup>|24.34|
|Share of employed<br>females>employed males|27.46|37.17<sup>*</sup>|34.11|35.46|13.03|17.51|39.58|42.13<sup>*</sup>|59.83|55.11|25.30|25.32|
|Most educated member is female<br>adult & no employed males|24.25|37.90<sup>*</sup>|51.45<sup>*</sup>|34.76|23.55<sup>*</sup>|16.19|33.68|43.27<sup>*</sup>|60.50|54.97|28.20<sup>*</sup>|24.82|
|<br>**_Panel C: Urban_**|||||||||||||
|Self-Reported FHH|16.96|23.08<sup>*</sup>|15.19|18.52<sup>*</sup>|14.70|14.36|26.68|30.24<sup>*</sup>|50.17|58.89<sup>*</sup>|12.29|13.27<sup>*</sup>|
|<br>Reported de jure FHH|16.96|22.97<sup>*</sup>|15.08|18.48<sup>*</sup>|16.61|14.21|25.75|29.90<sup>*</sup>|47.92|58.92<sup>*</sup>|11.59|13.33<sup>*</sup>|
|Reported married FHH|16.81|22.39<sup>*</sup><br>|15.97|18.20<br>|7.29|14.53<sup>*</sup><br>|26.42|29.62<sup>*</sup>|61.23|58.33<br>|17.25<sup>*</sup>|13.09<br>|
|Potential FHH|11.5|23.56<sup>*</sup>|14.49|18.25<sup>*</sup>|7.33|14.91<sup>*</sup>|29.05|29.28|32.54|59.48<sup>*</sup>|8.69|13.75<sup>*</sup>|
|<br>Core FHH|<br>13.47|22.58<sup>*</sup>|<br>9.54|18.21<sup>*</sup>|<br>4.43|14.60<sup>*</sup>|<br>25.24|<br>29.51<sup>*</sup>|<br>31.97|58.70<sup>*</sup>|<br>8.68|13.32<sup>*</sup>|
|Asset FHH|9.11|23.18<sup>*</sup>|12.56|18.25<sup>*</sup>|7.72|14.82<sup>*</sup>|31.32<sup>*</sup>|28.90|36.09|58.94<sup>*</sup>|9.64|13.37<sup>*</sup>|
|Share of female adults>0.5|21.27|22.61|17.92|18.28|16.24<sup>*</sup>|13.81|31.12<sup>*</sup>|27.94|60.55<sup>*</sup>|57.77|14.40<sup>*</sup>|12.68|
|Share of employed<br>females>employed males|17.58|22.65<sup>*</sup>|11.31|18.40<sup>*</sup>|6.65|14.91<sup>*</sup>|26.20|29.73<sup>*</sup>|52.13|58.69<sup>*</sup>|12.50|13.23|
|Most educated member is female<br>adult & no employed males|16.40|23.10<sup>*</sup>|18.57|18.15|21.52|13.06|20.58|30.74<sup>*</sup>|63.05<sup>*</sup>|57.76|13.38|13.11|
|<br>**_Panel D: Have children under 14_**|||||||||||||
|Self-Reported FHH|35.2|39.33<sup>*</sup>|22.15|25.99<sup>*</sup>|29.00<sup>*</sup>|18.18|31.91|40.75<sup>*</sup>|67.33|64.40|28.70<sup>*</sup>|22.48|
|<br>Reported de jure FHH|37.62|39.05|21.27|26.01<sup>*</sup>|34.42<sup>*</sup>|18.11|33.39|39.21<sup>*</sup>|65.85|64.47|25.84<sup>*</sup>|22.81|
|Reported married FHH|31.51|39.24<sup>*</sup>|26.85|25.66|13.71|18.82|29.33|39.71<sup>*</sup>|72.35|64.45|33.15<sup>*</sup>|22.64|
|<br>Potential FHH|32.83|39.34<sup>*</sup>|27.84|25.64|25.95<sup>*</sup>|18.55|33.94|39.50<sup>*</sup>|59.40|64.60|29.98<sup>*</sup>|22.55|
|Core FHH|30.60|39.13<sup>*</sup>|23.68|25.68|21.68|18.73|32.23|38.93<sup>*</sup>|48.35|64.63<sup>*</sup>|25.61|22.89|
|Asset FHH|32.24|39.24<sup>*</sup>|28.13|25.65|27.28<sup>*</sup>|18.55|35.51|39.04<sup>*</sup>|64.80|64.51|33.36<sup>*</sup>|22.60|
|Share of female adults>0.5|40.1|38.72|27.32|24.90|26.82<sup>*</sup>|16.80|39.83<sup>*</sup>|37.41|70.08<sup>*</sup>|63.15|27.90<sup>*</sup>|21.48|
|Share of emloed|||||||||||||
|py<br>|35.69|39.1<sup>*</sup>|25.57|25.68|17.43|18.79|35.55|38.89<sup>*</sup>|67.74|64.38|26.60<sup>*</sup>|22.68|
|females>employed males|||||||||||||
|<br>Most educated member is female||<sup>*</sup>|<sup>*</sup>||<sup>*</sup>|||<sup>*</sup>|<sup>*</sup>||<sup>*</sup>||
|adult & no employed males|32.09|39.48|33.62|25.37|34.47|16.46|30.61|39.74|77.00|63.23|29.63|22.22|
|<br>**_Panel E: No children under 14_**|||||||||||||
|Self-Reported FHH|10.53|10.52|6.79|6.15|3.88|4.13|12.21|13.63|30.83|31.39|8.71|9.28|
||||||52||||||||
|Reported de jure FHH|10.39|10.55|6.26<br>|6.26|4.54|3.98|12.76|13.34<br>|30.16|31.50|8.69|9.28|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Reported married FHH|12.7|10.49|13.20<sup>*</sup>|6.17|0.00|4.20|9.25|13.42<sup>*</sup>|36.90|31.19|8.97|9.18|
|Potential FHH|6.24|11.58<sup>*</sup><br>|5.05|6.36<br>|0.81|4.77<sup>*</sup><br>|11.70|13.58<sup>*</sup>|23.57|32.92<sup>*</sup><br>|7.74|9.57<sup>*</sup><br>|
|Core FHH|7.59|10.65<sup>*</sup><br>|1.33|6.39<sup>*</sup>|0.00|4.33<sup>*</sup><br>|11.32|13.31|23.75|31.66<sup>*</sup><br>|7.38|9.29<sup>*</sup>|
|Asset FHH|6.14<br>|11.29<sup>*</sup>|4.76<br>|6.36|0.68|4.72<sup>*</sup><br>|12.19<br>|13.42|25.22<br>|32.03<sup>*</sup>|8.97<br>|9.21|
|Share of female adults>0.5|12.16<sup>*</sup>|9.89|8.69<sup>*</sup>|4.83|2.74|4.86<sup>*</sup>|15.30<sup>*</sup>|11.80|33.93<sup>*</sup>|29.72|11.40<sup>*</sup>|7.91|
|Share of employed<br>females>employed males|8.79|10.7<sup>*</sup>|3.09|6.57<sup>*</sup>|0.47|4.64<sup>*</sup>|10.29|13.61<sup>*</sup>|31.32|31.29|10.27<sup>*</sup>|8.99|
|Most educated member is female<br>adult & no employed males|8.74|10.90<sup>*</sup>|9.36<sup>*</sup>|5.84|3.02|4.41|10.04|14.05<sup>*</sup>|35.36<sup>*</sup>|30.23|11.40|8.51|

Note: The data are pooled across all available years for each country. Headcount poverty rates are estimated using per capita household expenditures. Stars indicate statistically significant difference in headcount poverty between FHHs and non-FHHs in each category at the 5% or lower level. Population sampling weights are applied.

53
# **<u>Table A.10. Probabilities of Being Poor, Linear Probability Model (Main FHH Types)</u>**

|||**Specif**|**ication 1**|||**Spec**|**ification 2**||
|---|---|---|---|---|---|---|---|---|
||**FHH Type 1**<br>**Self-reported**|**FHH Type 2**<br>**Majority-female-adult**|**FHH Type 3**<br>**Potential**|**FHH Type 4**<br>**Most-educated-female-adult**|**FHH Type 1**<br>**Self-reported**|**FHH Type 2**<br>**Majority-female-adult**|**FHH Type 3**<br>**Potential**|**FHH Type 4**<br>**Most-educated-female-adult**|
||-0.007***||||-0.044***||||
|Self-reported FHH|<br>(0.00)||||<br>(0.00)||||
|Self-reported FHH # Number of children age|0.008***||||0.006***||||
|0-14|(0.00)||||(0.00)||||
|||0.052***||||0.032***|||
|Share of female adults>0.5||(0.00)||||(0.00)|||
|Share of female adults>0.5# Number of||-0.007***||||-0.014***|||
|children age 0-14||(0.00)||||(0.00)|||
|il|||-0.027***||||-0.017***||
|Potenta FHH|||(0.00)||||(0.00)||
|Potential FHH# Number of children age 0-14|||0.014***<br>||||0.011***<br>||
||||(0.00)||||(0.00)||
|Edtd fl||||0.002||||-0.006**|
|ucae emaes||||(0.00)||||(0.00)|
|Educated females# Number of children age 0-||||<br>0.013***||||<br>0.013***|
|14||||(0.00)||||(0.00)|
|_Household head`s characteristics_|||||||||
|Hd`|||||-0.001***|-0.001***|-0.001***|-0.001***|
|eas age|||||(0.00)|(0.00)|(0.00)|(0.00)|
|ih i ll i i|||||-0.066***|-0.064***|-0.064***|-0.065***|
|Hgest educaton eve s prmary|||||(0.00)|(0.00)|(0.00)|(0.00)|
|Highest education level is secondary|||||-0.123***<br>|-0.121***<br>|-0.121***<br>|-0.121***<br>|
||||||(0.00)|(0.00)|(0.00)|(0.00)|
|Hiht dti ll i tti|||||<br>-0.178***|<br>-0.176***|<br>-0.176***|<br>-0.176***|
|ges eucaon eve s erary|||||(0.00)|(0.00)|(0.00)|(0.00)|
|Head is married|||||-0.020***<br>|0.007***<br>|0.005**<br>|0.006***<br>|
||||||(0.00)|(0.00)|(0.00)|(0.00)|
|Hd i ld|||||-0.037***|-0.032***|-0.031***|-0.027***|
|ea s empoye|||||(000)|(000)|(000)|(000)|
|_Household characteristics_|||||.<br>|.<br>|.<br>|.<br>|
|Hhld i|||||0.022***|0.024***|0.023***|0.023***|
|ouseo sze|||||(0.00)|(0.00)|(0.00)|(0.00)|
|Number of children ae 0-14|0.077***|0.081***|0.076***|0.077***|0.050***|0.054***|0.049***|0.049***|
|g|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Sh f hhld b 1524|||||-0.008***|-0.008***|-0.008***|-0.009***|
|are o ouseo memers age -|||||(0.00)|(0.00)|(0.00)|(0.00)|
||||||-0.022***|-0.019***|-0.017***|-0.020***|
|Share of household members age 60 and older|||||(0.00)|(0.00)|(0.00)|(0.00)|
|Ub|||||<br>-0.084***|<br>-0.084***|<br>-0.084***|<br>-0.084***|
|ran|||||(0.00)|(0.00)|(0.00)|(0.00)|
|I|-0.149***|-0.152***|-0.149***|-0.148***|-0.181***|-0.182***|-0.179***|-0.180***|
|raq|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Jordan|-0.144***|-0.147***|-0.144***|-0.146***|-0.092***|-0.094***|-0.090***|-0.092***|
||(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
||<br>-0.155***|<br>-0.160***|<br>-0.156***|<br>-0.158***|<br>-0.207***|<br>-0.208***|<br>-0.213***|<br>-0.212***|
|Mauritania|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
||0181***|0178***|0181***|0180***|0185***|0183***|0186***|0185***|
|West Bank and Gaza|.<br>(0.01)|.<br>(0.01)|.<br>(0.01)|.<br>(0.01)|.<br>(0.01)|.<br>(0.01)|.<br>(0.01)|.<br>(0.01)|
||<br>-0.060***|<br>-0.063***|<br>-0.060***|<br>-0.061***|<br>-0.054***|<br>-0.055***|<br>-0.054***|<br>-0.054***|
|Tunisia|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|_cons|0.127***|0.112***|0.133***|0.126***|0.312***|0.261***|0.270***|0.267***|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.01)|(0.01)|(0.01)|(0.01)|
|r2_a|0.16|0.17|0.16|0.16|0.21|0.21|0.21|0.21|
|N|214931|214931|214931|214931|211069|211069|211069|211069|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Robust standard errors are in parentheses. All regressions control for survey rounds fixed effects. The reference groups for head`s education without formal education. The reference group for share of household members is share of members aged between 25 and 59 years. The reference country is the Arab Republic of Egypt.

54
# **<u>Table A.11. Probabilities of Being Poor for Other FHH Types, Linear Probability Model</u>**

||||**Specification 1**|||||**Specification 2**|||
|---|---|---|---|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|**(9)**|**(10)**|
||-0.003|||||-0.027***|||||
|De-jure FHH|<br>|||||<br>|||||
||(0.00)|||||(0.00)|||||
|De-jure FHH # Number of children age 0-14|0.013***<br>|||||0.009***<br>|||||
||(0.00)|||||(0.00)|||||
|Married FHH||-0.031***|||||-0.058***||||
|||(0.01)|||||(0.01)||||
|id b f hild||0.005**|||||0.006**||||
|Marre FHH # Numer o cren age 0-14||(0.00)|||||(0.00)||||
||||0.009**|||||0.008**|||
|Employed FHH|||(0.00)|||||(0.00)|||
|Employed FHH # Number of children age 0-14|||-0.001<br>|||||-0.004*<br>|||
||||(0.00)|||||(0.00)|||
|A FHH||||-0.019***|||||-0.018***||
|sset||||(0.00)|||||(0.00)||
|A FHH # Nb f hild 014||||0.014***|||||0.011***||
|sset umer o cren age -||||(0.00)|||||(0.00)||
||||||-0023***|||||-0010**|
|Core FHH|||||.<br>(0.00)|||||.<br>(0.00)|
|Core FHH # Number of children age 0-14|||||0.006**<br>(0.00)|||||0.007***<br>(0.00)|
|_Household head`s characteristics_|||||||||||
|`||||||-0.001***|-0.001***|-0.001***|-0.001***|-0.001***|
|Heads age||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Hihest education level is rimar||||||-0.065***|-0.065***|-0.064***|-0.064***|-0.064***|
|g py||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Hihest edcation leel is secondar||||||-0.122***|-0.122***|-0.121***|-0.121***|-0.121***|
|g u v y||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Highest education level is tertiary||||||-0.177***<br>|-0.177***<br>|-0.176***<br>|-0.177***<br>|-0.176***<br>|
|||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Head is married||||||-0.008**|0.011***|0.006***|0.006**|0.006***|
|||||||(0.00)<br>|(0.00)<br>|(0.00)<br>|(0.00)<br>|(0.00)<br>|
|||||||-0.033***|-0.038***|-0.032***|-0.031***|-0.032***|
|Head is employed||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|_Household characteristics_|||||||||||
|hld i||||||0.023***|0.023***|0.023***|0.023***|0.023***|
|Houseo sze||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Nb f hild 014|0.077***|0.078***|0.078***|0.077***|0.078***|0.050***|0.050***|0.050***|0.049***|0.050***|
|umer o cren age -|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Share of household members age 15-24||||||-0.009***<br>|-0.008***<br>|-0.009***<br>|-0.009***<br>|-0.009***<br>|
|||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Sh f hhld b 60 d ld||||||-0.021***|-0.021***|-0.021***|-0.018***|-0.021***|
|are o ouseo memers age an oer||||||(0.00)<br>|(0.00)<br>|(0.00)<br>|(0.00)<br>|(0.00)<br>|
|||||||-0.084***|-0.084***|-0.084***|-0.084***|-0.084***|
|Urban||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|I|-0.149***|-0.150***|-0.149***|-0.149***|-0.149***|-0.181***|-0.182***|-0.181***|-0.180***|-0.181***|
|raq|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
||-0.145***|-0.145***|-0.145***|-0.144***|-0.145***|-0.091***|-0.093***|-0.093***|-0.090***|-0.092***|
|Jordan|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
||<br>0.122***|<br>0.123***|<br>0.123***|<br>0.125***|<br>0.124***|<br>0.058***|<br>0.059***|<br>0.059***|<br>0.061***|<br>0.059***|
|Mauritania|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
||0.181***|0.180***|0.180***|0.180***|0.180***|0.185***|0.184***|0.184***|0.184***|0.184***|
|West Bank and Gaza|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
||-0060***|-0061***|-0061***|-0060***|-0060***|-0054***|-0054***|-0054***|-0054***|-0054***|
|Tunisia|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|.<br>(0.00)|
|_cons|0.126***|0.126***|0.125***|0.126***|0.127***|0.289***|0.284***|0.272***|0.268***|0.273***|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
|Adjuster R2|0.16|0.16|0.16|0.16|0.16|0.21|0.21|0.21|0.21|0.21|
|<br>Number of observations|214931|214931|214931|214931|214931|211069|211069|211069|211069|211069|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Robust standard errors are in parentheses. All regressions control for survey rounds fixed effects. The reference groups for head`s education without formal education. The reference group for share of household members is share of members aged between 25 and 59 years. The reference country is the Arab Republic of Egypt.

55
# **<u>Table A.12. Probabilities of Being Poor, Logit Model</u>**

|||**Specif**|**ication 1**|||**Speci**|**fication 2**||
|---|---|---|---|---|---|---|---|---|
||**FHH Type 1**<br>**Self-reported**|**FHH Type 2**<br>**Majority-female-adult**|**FHH Type 3**<br>**Potential**|**FHH Type 4**<br>**Most-educated-female-adult**|**FHH Type 1**<br>**Self-reported**|**FHH Type 2**<br>**Majority-female-adult**|**FHH Type 3**<br>**Potential**|**FHH Type 4**<br>**Most-educated-female-adult**|
|Self-reported FHH|-0.110***<br>||||-0.290***<br>||||
||(0.02)||||(0.03)||||
|Self-reported FHH # Number of children age|<br>0.057***||||<br>0.036***||||
|0-14|(0.01)||||(0.01)||||
|||0.415***||||0.323***|||
|Share of female adults>0.5||<br>(0.02)||||<br>(0.02)|||
|Share of female adults>0.5# Number of||-0.072***||||-0.116***|||
|children age 0-14||(0.01)||||(0.01)|||
|Potential FHH|||-0.339***<br>||||-0.165***<br>||
||||(0.02)||||(0.03)||
|Pil FHH# Nb f hild 014|||0.124***||||0.075***||
|otenta umer o cren age -|||(0.01)||||(0.01)||
|Educated females||||-0.037||||-0.040|
|||||(0.02)||||(0.03)|
|Educated females# Number of children age 0-||||0.086***||||0.074***|
|14||||(0.01)||||(0.01)|
|_Household head`s characteristics_|||||||||
|`|||||-0.009***|-0.009***|-0.007***|-0.008***|
|Heads age|||||(0.00)|(0.00)|(0.00)|(0.00)|
|Hihest education level is rimar|||||-0.451***|-0.443***|-0.443***|-0.448***|
|g py|||||(0.02)|(0.02)|(0.02)|(0.02)|
||||||-0.911***|-0.903***|-0.900***|-0.903***|
|Highest education level is secondary|||||(0.02)|(0.02)|(0.02)|(0.02)|
|Hiht dti ll i tti|||||-1.572***|-1.568***|-1.563***|-1.562***|
|ges eucaon eve s erary|||||(0.03)|(0.03)|(0.03)|(0.03)|
|d i id|||||-0.097***|0.083***|0.059***|0.068***|
|Hea s marre|||||(0.03)|(0.02)|(0.02)|(0.02)|
|Hd i ld|||||-0.256***|-0.213***|-0.212***|-0.178***|
|ea s empoye|||||(0.02)|(0.02)|(0.02)|(0.02)|
|_Household characteristics_|||||||||
|hld i|||||0.160***|0.167***|0.160***|0.165***|
|Houseo sze|||||(0.00)|(0.00)|(0.00)|(0.00)|
|Nb f hild 014|0.468***|0.508***|0.456***|0.470***|0.301***|0.338***|0.298***|0.293***|
|umer o cren age -|(0.00)|(0.00)|(0.00)|(0.00)|(0.01)<br>|(0.01)<br>|(0.01)<br>|(0.01)<br>|
||||||-0.092***|-0.095***|-0.095***|-0.100***|
|Share of household members age 15-24|||||(0.01)|(0.01)|(0.01)|(0.01)|
|Share of household members age 60 and older|||||-0.325***<br>|-0.316***<br>|-0.286***<br>|-0.315***<br>|
||||||(0.02)|(0.02)|(0.02)|(0.02)|
||||||<br>-0.614***|<br>-0.610***|<br>-0.611***|<br>-0.611***|
|Urban|||||(0.01)|(0.01)|(0.01)|(0.01)|
||-1.072***|-1.106***|-1.065***|-1.070***|-1.441***|-1.457***|-1.422***|-1.429***|
|Iraq|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
||-1.184***|-1.203***|-1.180***|-1.204***|-0.886***|-0.903***|-0.863***|-0.880***|
|Jordan|(0.07)|(0.07)|(0.07)|(0.07)|(0.08)|(0.08)|(0.08)|(0.08)|
|Mauritania|-1.117***|-1.152***|-1.125***|-1.137***|-1.622***|-1.628***|-1.665***|-1.664***|
||(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|
||<br>0.796***|<br>0.784***|<br>0.797***|<br>0.795***|<br>0.887***|<br>0.880***|<br>0.896***|<br>0.892***|
|West Bank and Gaza|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|
|Tii|-0.468***|-0.481***|-0.466***|-0.473***|-0.438***|-0.445***|-0.433***|-0.434***|
|unsa|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
|_cons|<br>-1.917***|<br>-2.062***|<br>-1.861***|<br>-1.932***|<br>-0.606***|<br>-0.975***|<br>-0.877***|<br>-0.915***|
||(0.04)|(0.04)|(0.04)|(0.04)|(0.06)|(0.06)|(0.06)|(0.06)|
|N|214931|214931|214931|214931|211069|211069|211069|211069|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Robust standard errors are in parentheses. All regressions control for survey rounds fixed effects. The reference groups for head`s education without formal education. The reference group for share of household members is share of members aged between 25 and 59 years. The reference country is the Arab Republic of Egypt.

56
# **<u>Table A.13. Probabilities of Being Poor for Other FHH Types, Logit Model</u>**

||||**Specification 1**|||||**Specification 2**|||
|---|---|---|---|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|**(9)**|**(10)**|
||-0098***|||||-0098**|||||
|De-jure FHH|.<br>(0.02)|||||.<br>(0.05)|||||
|De-jure FHH # Number of children ae 0-14|0.094***|||||0.059***|||||
|g|(0.01)|||||(0.01)|||||
|Mid FHH||-0.182***|||||-0.392***||||
|arre||(0.05)|||||(0.06)||||
|Married FHH # Number of children age 0-14||0.024<br>|||||0.029*<br>||||
|||(0.02)|||||(0.02)||||
|Emloed FHH|||0.036|||||-0.135***|||
|py|||(0.03)<br>|||||(0.05)<br>|||
|Eld FHH # Nb f hild 014|||-0.002|||||0.058***|||
|mpoye umer o cren age -|||(0.01)|||||(0.02)|||
|||||-0.235***|||||-0.103***||
|Asset FHH||||<br>(0.03)|||||<br>(0.03)||
|Asset FHH # Number of children ae 0-14||||0.106***|||||0.056***||
|g||||(0.01)|||||(0.01)||
|C FHH|||||-0.259***|||||0.028|
|ore|||||(0.04)|||||(0.03)|
|Core FHH # Number of children age 0-14|||||0.060***<br>|||||-0.016<br>|
|<br>_Household head`s characteristics_|||||(0.02)|||||(0.01)|
|`||||||-0.008***|-0.009***|-0.008***|-0.008***|-0.008***|
|Heads age||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Hih di ll i i||||||-0.443***|-0.449***|-0.442***|-0.442***|-0.442***|
|gest eucaton eve s prmary||||||(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|Hiht dti ll i d||||||-0.902***|-0.909***|-0.900***|-0.900***|-0.901***|
|ges eucaon eve s seconary||||||(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|||||||-1.563***|-1.570***|-1.562***|-1.562***|-1.564***|
|Highest education level is tertiary||||||(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
|Head is married||||||0.061|0.104***|0.065***|0.065***|0.066***|
|||||||(0.04)<br>|(0.02)<br>|(0.02)<br>|(0.02)<br>|(0.02)<br>|
|||||||-0.216***|-0.267***|-0.216***|-0.210***|-0.216***|
|Head is employed||||||(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|_Household characteristics_|||||||||||
|Hhld i||||||0.162***|0.161***|0.163***|0.162***|0.163***|
|ouseo sze||||||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Nb f hild 014|0.470***|0.477***|0.478***|0.465***|0.474***|0.298***|0.303***|0.300***|0.298***|0.303***|
|umer o cren age -|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
|Share of household members ae 15-24||||||-0.096***|-0.092***|-0.100***|-0.099***|-0.100***|
|g||||||(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
|Sh f hhld b 60 d ld||||||<br>-0.316***|<br>-0.326***|<br>-0.323***|<br>-0.304***|<br>-0.324***|
|are o ouseo memers age an oer||||||(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|||||||-0.613***|-0.616***|-0.611***|-0.610***|-0.612***|
|Urban||||||(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
||-1.077***|-1.081***|-1.079***|-1.071***|-1.076***|<br>-1.434***|<br>-1.446***|<br>-1.436***|<br>-1.432***|<br>-1.441***|
|Iraq|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
||-1.188***|-1.194***|-1.191***|-1.183***|-1.189***|-0.876***|-0.895***|-0.881***|-0.872***|-0.885***|
|Jordan|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.08)|(0.08)|(0.08)|(0.08)|(0.08)|
||<br>-1.115***|<br>-1.080***|<br>-1.097***|<br>-1.098***|<br>-1.091***|<br>-1.649***|<br>-1.597***|<br>-1.647***|<br>-1.649***|<br>-1.636***|
|Mauritania|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|(0.05)|
|West Bank and Gaza|<br>0.795***|<br>0.794***|<br>0.794***|<br>0.786***|<br>0.795***|<br>0.889***|<br>0.883***|<br>0.889***|<br>0.887***|<br>0.887***|
||(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|
||<br>-0.468***|<br>-0.469***|<br>-0.469***|<br>-0.465***|<br>-0.467***|<br>-0.434***|<br>-0.436***|<br>-0.434***|<br>-0.433***|<br>-0.435***|
|Tunisia|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
|_cons|-1.923***<br>|-1.935***<br>|-1.943***<br>|-1.926***<br>|-1.927***<br>|-0.849***<br>|-0.781***<br>|-0.866***<br>|-0.888***<br>|-0.871***<br>|
||(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|(0.07)|(0.06)|(0.06)|(0.06)|(0.06)|
|N|214931|214931|214931|214931|214931|211069|211069|211069|211069|211069|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Robust standard errors are in parentheses. All regressions control for survey rounds fixed effects. The reference groups for head`s education without formal education. The reference group for share of household members is share of members aged between 25 and 59 years. The reference country is the Arab Republic of Egypt.

57
# **-** **<u>Table A.14. Probabilities of Being Poor for Combination of Main Female Headed Household Types, Linear Probability Model</u>**

||**Specific**|**ation 1**|**Specif**|**ication 2**|
|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|
||-0037***||-0033***||
|Overlap of self-reported FHHs, potential FHHs, and most-educated-female-adult FHHs|.<br>(0.00)<br>||.<br>(0.00)<br>||
|Overlap of self-reported FHHs, potential FHHs, and most-educated-female-adult FHHs # Number of children age 0-14|0.005**<br>(0.00)||0.007***<br>(0.00)||
|Overlap of self-reported FHHs, potential FHHs, majority of females and most-educated-female-adult FHHs||-0.037***<br>(0.00)||-0.033***<br>(0.00)|
|Overlap of self-reported FHHs, potential FHHs, majority of females and most-educated-female-adult FHHs # Number of children age 0-14||0.005**<br>(0.00)||0.007***<br>(0.00)|
|_Household head`s characteristics_|||||
|`|||-0.001***|-0.001***|
|Heads age|||(0.00)|(0.00)|
|Highest education level is primary|||-0.064***<br>(0.00)|-0.064***<br>(0.00)|
||||-0.121***|-0.121***|
|Highest education level is secondary|||(0.00)|(0.00)|
||||-0.176***|-0.176***|
|Highest education level is tertiary|||(0.00)|(0.00)|
|Head is married|||0.001<br>|0.001<br>|
||||(0.00)<br>|(0.00)<br>|
||||-0.033***|-0.033***|
|Head is employed|||<br>(0.00)|<br>(0.00)|
|_Household characteristics_|||||
|Household size|||0.023***|0.023***|
||||(0.00)|(0.00)|
|Nb f hild 014|0.078***|0.078***|0.050***|0.050***|
|umer o cren age -|(0.00)|(0.00)|(0.00)|(0.00)|
|Sh f hhld b 1524|||-0.009***|-0.009***|
|are o ouseo memers age -|||(0.00)|(0.00)|
|Share of household members ae 60 and older|||-0.021***|-0.021***|
|g|||(0.00)|(0.00)|
||||-0.084***|-0.084***|
|Urban|||(0.00)|(0.00)|
||-0.150***|-0.150***|-0.181***|-0.181***|
|Iraq|(0.00)|(0.00)|(0.00)|(0.00)|
||-0.145***|-0.145***|-0.093***|-0.093***|
|Jordan|(0.01)|(0.01)|(0.01)|(0.01)|
||-0.150***|-0.150***|-0.209***|-0.209***|
|Mauritania|(0.01)|(0.01)|(0.01)|(0.01)|
||0.180***|0.180***|0.184***|0.184***|
|West Bank and Gaza|<br>(0.01)|<br>(0.01)|<br>(0.01)|<br>(0.01)|
||-0.061***|-0.061***|-0.054***|-0.054***|
|Tunisia|(0.00)|(0.00)|(0.00)|(0.00)|
|_cons|0.129***|0.129***|0.283***|0.283***|
||(0.00)|(0.00)|(0.01)|(0.01)|
|Adjuster R2|0.16|0.16|0.21|0.21|
|Number of observations|214931|214931|211069|211069|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Robust standard errors are in parentheses.

58
# **<u>Table A.15. Average change for mobility per year between the survey rounds</u>**

||**Upward mobility (%)**|**Downward mobility (%)**|
|---|---|---|
|Jordan (2010-2013)|17.8|3.5|
|Egypt, Arab Rep. (2017-2020)|9.7|5.3|
|Iraq (2007-2012)|9.0|2.7|
|Mauritania (2014-2019)|8.1|2.8|
|West Bank and Gaza (2011-2017)|5.1|8.1|
|Tunisia (2015-2021)|3.5|1.3|

**Note:** Countries are ranked in a decreasing order of upward mobility.

59
**Figure A.1. Headcount Poverty Rates in Self-Reported Male-Headed Households (%), by Number of Female Adults**

<!-- Start of picture text --> Egypt Iraq<br>2012<br>2007<br>2015<br>2017<br>2012<br>2020<br>0 10 20 30 40<br>0 50 100<br>Jordan Mauritania<br>2004<br>2007<br>2008<br>2014<br>2012<br>2019<br>0 10 20 30 40 0 20 40 60 80<br>Palestine Tunisia<br>2007 2005<br>2009 2010<br>2011 2015<br>2017 2021<br>0 20 40 60 80 100 0 20 40 60<br>0 1 2 3 4 >4<br><!-- End of picture text -->

**Note:** Headcount poverty rates are estimated using per capita household expenditures. The numbers of female adults are shown for 0, 1, 2, 3, 4, and more than 4 adults. The years are shown on the y-axis and the poverty rates are shown on the x-axis.

60
# **Figure A.2. FHH–non-FHH Differences in Headcount Poverty Rate in MENA, Pooled Cross Sections (percentage points)**

<!-- Start of picture text --> Egypt Iraq<br>***<br>***<br>***<br>**<br>***<br>*** *** ***<br>***<br>*** *** ***<br>Self-reported Married *** Core ***Females>0.5 Educated Self-reported Married Core Females>0.5 Educated<br>De jure Potential Asset Employed De jure Potential Asset Employed<br>Jordan Mauritania<br>***<br>***<br>***<br>*** ***<br>*** ***<br>** *** *** *** *** *** ***<br>*** ***<br>Self-reported Married Core Females>0.5 Educated Self-reported Married Core Females>0.5 Educated<br>De jure Potential Asset Employed De jure Potential Asset Employed<br>Palestine Tunisia<br>***<br>***<br>***<br>** ***<br>*** *** ***<br>*** *** **<br>*** *** *** *** ***<br>Self-reported Married Core Females>0.5 Educated Self-reported Married Core Females>0.5 Educated<br>De jure Potential Asset Employed De jure Potential Asset Employed<br>0 5<br>-5 0<br>-10 -5<br>difference (pps) difference (pps)<br>-15 -10<br>10 5<br>5<br>0<br>0<br>-5 -5<br>difference (pps) difference (pps)<br>-10 -10<br>10 10<br>0<br>5<br>-10<br>difference (pps) -20 0 difference (pps)<br>-30 -5<br><!-- End of picture text -->

**Note:** Authors’ calculation based on pooled cross sections. The four main types of FHHs are shown in darker color, the five sub-types of FHHs are shown in lighter color. The headcount poverty rate is applied to per capita household expenditures, of FHHs versus the rest of the households. Stars indicate statistically significantly higher headcount poverty ratio between FHHs and non-FHHs in each category. ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels respectively.

61
# **Figure A.3. Correlation Between Probabilities of Female-Headed Households Escaping Poverty in Second Year and Number of Children (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>0 1 2 3 4 0 1 2 3 4<br>Number of children Number of children<br>Jordan 2010-2013 Mauritania 2014-2019<br>0 1 2 3 4 0 1 2 3 4<br>Number of children Number of children<br>Palestine 2011-2017 Tunisia 2015-2021<br>0 1 2 3 4 0 1 2 3 4<br>Number of children Number of children<br>Self-reported FHH Females>0.5<br>Potential FHH Educated females<br>.38 .5<br>.36 .48<br>.34 .46<br>.32 .44<br>.3 .42<br>Percentage (%) Percentage (%)<br>.28 .4<br>.55 .48<br>.5 .46<br>.44<br>.45<br>.42<br>Percentage (%) Percentage (%)<br>.4 .4<br>.45<br>.25<br>.4<br>.2<br>.35 .15<br>Percentage (%) Percentage (%)<br>.3 .1<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round.

62
# **Figure A.4. Probability of Other FHH Types Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>De-jure Employed fem. Core De-jure Employed fem. Core<br>Married Assets Married Assets<br>Jordan 2010-2013 Mauritania 2014-2019<br>De-jure Employed fem. Core De-jure Employed fem. Core<br>Married Assets Married Assets<br>Palestine 2011-2017 Tunisia 2015-2021<br>De-jure Employed fem. De-jure Employed fem.<br>Married Core Married Core<br>FHH wo/children FHH w/children Non-FHH<br>45 70<br>40<br>60<br>35<br>50<br>30<br>Percentage (%) Percentage (%)<br>25 40<br>70 50<br>48<br>60<br>46<br>44<br>50<br>42<br>Percentage (%) 40 Percentage (%)<br>40<br>50 25<br>40 20<br>30 15<br>Percentage (%) Percentage (%)<br>20 10<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

63
**Figure A.5. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage), Arab Republic of Egypt**

<!-- Start of picture text --> Egypt 2012-2015 Egypt 2015-2017 Egypt 2017-2020<br>FHH wo/children FHH w/children Non-FHH<br>Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem.<br>40 40 40<br>30 30 30<br>Percentage (%) Percentage (%) Percentage (%)<br>20 20 20<br>10 10 10<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

64
**Figure A.6. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage), Mauritania**

<!-- Start of picture text --> Mauritania 2004-2008 Mauritania 2008-2014 Mauritania 2014-2019<br>FHH wo/children FHH w/children Non-FHH<br>Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem.<br>50 50 50<br>45 45 45<br>40 40 40<br>Percentage (%) Percentage (%) Percentage (%)<br>35 35 35<br>30 30 30<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

65
**Figure A.7. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage), West Bank and Gaza**

<!-- Start of picture text --> Palestine 2007-2009 Palestine 2009-2011 Palestine 2011-2017<br>FHH wo/children FHH w/children Non-FHH<br>Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem.<br>45 45 45<br>40 40 40<br>35 35 35<br>Percentage (%) Percentage (%) Percentage (%)<br>30 30 30<br>25 25 25<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

66
**Figure A.8. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage), Tunisia**

<!-- Start of picture text --> Tunisia 2005-2010 Tunisia 2010-2015 Tunisia 2015-2021<br>FHH wo/children FHH w/children Non-FHH<br>Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem. Self-reported Females>0.5 Potential Educated fem.<br>60 60 60<br>50 50 50<br>40 40 40<br>Percentage (%) Percentage (%) Percentage (%)<br>30 30 30<br>20 20 20<br>10 10 10<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

67
# **Figure A.9. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH Non-FHH<br>34<br>50<br>32 48<br>30 46<br>Percentage (%) Percentage (%)<br>28 44<br>46<br>56<br>54 44<br>52<br>42<br>50<br>40<br>48<br>Percentage (%) Percentage (%)<br>46 38<br>45<br>23<br>40 22<br>21<br>35<br>20<br>Percentage (%) Percentage (%)<br>30 19<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

68
# **Figure A.10. Probabilities of Female-Headed Households Falling in Poverty in Second Year Conditional on Being Non-poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH Non-FHH<br>17 14<br>16<br>13<br>15<br>12<br>14<br>11<br>13<br>Percentage (%) Percentage (%)<br>12 10<br>13 16<br>12 15<br>14<br>11<br>13<br>10<br>12<br>Percentage (%) 9 Percentage (%)<br>11<br>50 8.5<br>45 8<br>40 7.5<br>7<br>Percentage (%) Percentage (%)<br>35<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that enters poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps.

69
# **Appendix B: Additional Descriptive Statistics for Self-Reported FHHs and MHHs**

**<u>Table B.1. Descriptive Statistics, Arab Republic of Egypt 2012-2020</u>**

||||||**Egypt, A**<br>|**rab Rep.**<br>|||||
|---|---|---|---|---|---|---|---|---|---|---|
||**2**|**012**|**2**|**017**|**2**|**017**|**2**|**020**|**Pooled**|**2012-2020**|
||**MHH**<br>|**FHH**<br>|**MHH**<br>|**FHH**<br>|**MHH**<br>|**FHH**<br>|**MHH**<br>|**FHH**<br>|**MHH**<br>|**FHH**<br>|
|Heads age|47.17<br>(13.44)|54.11<br>(15.13)|48.71<br>(13.13)|56.05<br>(14.43)|49.99<br>(12.87)|57.19<br>(14.01)|47.01<br>(13.79)|55.49<br>(16.04)|48.37<br>(13.34)|55.91<br>(14.89)|
||0.40|0.69|0.36|0.63|0.34|0.63|0.31|0.58|0.35|0.63|
|Head does not complete primary school|(0.49)|(0.46)|(0.48)|(0.48)|(0.47)|(0.48)|(0.46)|(0.49)|(0.48)|(0.48)|
|'|0.13|0.09|0.15|0.12|0.15|0.11|0.14|0.11|0.15|0.11|
|Heads highest education level is primary|(0.33)|(0.29)|(0.36)|(0.32)|(0.36)|(0.31)|(0.35)|(0.31)|(0.35)|(0.31)|
|'|0.28|0.14|0.29|0.16|0.30|0.15|0.33|0.19|0.30|0.16|
|Heads highest education level is secondary|(0.45)|(0.35)|(0.45)|(0.36)|(0.46)|(0.36)|(0.47)|(0.39)|(0.46)|(0.37)|
|Hd' hih di ll i i|0.19|0.08|0.20|0.09|0.20|0.10|0.22|0.12|0.20|0.10|
|eas gest eucaton eve s tertary|(0.40)|(0.27)|(0.40)|(0.29)|(0.40)|(0.30)|(0.41)|(0.33)|(0.40)|(0.30)|
||0.02|0.03|0.01|0.02|0.01|0.03|0.01|0.03|0.01|0.03|
|Head is never married|(0.13)|(0.16)|(0.12)|(0.14)|(0.11)|(0.16)|(0.12)|(0.18)|(0.12)|(0.16)|
|Hd i id|<br>0.95|<br>0.21|<br>0.93|<br>0.16|<br>0.95|<br>0.14|<br>0.95|<br>0.20|<br>0.95|<br>0.17|
|ea s mono marre|(0.22)|(0.41)|(0.25)|(0.37)|(0.22)|(0.34)|(0.21)|(0.40)|(0.23)|(0.38)|
||0.01|0.00|0.02|0.00|0.00|0.00|0.00|0.00|0.01|0.00|
|Head is poly married|<br>(0.07)|<br>(0.00)|<br>(0.12)|<br>(0.00)|<br>(0.06)|<br>(0.00)|<br>(0.00)|<br>(0.00)|<br>(0.08)|<br>(0.00)|
||0.01|0.05|0.01|0.07|0.01|0.08|0.01|0.10|0.01|0.08|
|Head is divorced/separated|(0.08)|(0.22)|(0.09)|(0.26)|(0.09)|(0.28)|(0.09)|(0.30)|(0.09)|(0.27)|
|Hd i idd|0.02|0.71|0.03|0.74|0.03|0.75|0.02|0.66|0.03|0.72|
|ea s wowe|(0.15)|(0.46)|(0.17)|(0.44)|(0.16)|(0.43)|(0.15)|(0.47)|(0.16)|(0.45)|
|i l|0.86|0.19|0.83|0.20|0.81|0.19|0.85|0.21|0.84|0.20|
|Head s empoyed|(0.34)|(0.40)|(0.37)|(0.40)|(0.39)|(0.39)|(0.36)|(0.41)|(0.37)|(0.40)|
||0.01|0.00|0.01|0.00|0.01|0.01|0.01|0.02|0.01|0.01|
|Head is unemployed|(0.09)|(0.05)|(0.07)|(0.06)|(0.08)|(0.08)|(0.08)|(0.13)|(0.08)|(0.08)|
|Head is homemaker/housewife|0.00<br>|0.20<br>|0.00<br>|0.48<br>|0.00<br>|0.51<br>|0.00<br>|0.49<br>|0.00<br>|0.44<br>|
||(0.00)|(0.40)|(0.00)|(0.50)|(0.00)|(0.50)|(0.00)|(0.50)|(0.00)|(0.50)|
|i|<br>0.00|<br>0.00|<br>0.00|<br>0.00|<br>0.00|<br>0.00|<br>0.00|<br>0.01|<br>0.00|<br>0.00|
|Head s student|(0.05)|(0.00)|(0.04)|(0.04)|(0.01)|(0.04)|(0.03)|(0.07)|(0.03)|(0.05)|
||0.11|0.51|0.15|0.31|0.18|0.29|0.14|0.27|0.15|0.33|
|Head is pensioner/retired/disabled|(0.31)|(0.50)|(0.36)|(0.46)|(0.38)|(0.46)|(0.35)|(0.45)|(0.36)|(0.47)|
||0.02|0.09|0.01|0.00|0.00|0.00|0.00|0.00|0.01|0.02|
|Head is other activities|(0.13)|(0.29)|(0.08)|(0.06)|(0.07)|(0.02)|(0.06)|(0.03)|(0.08)|(0.13)|
||671896|840976|1022128|1311456|1435090|1935674|1674403|2153011|1248320|1627927|
|Per capita consumption|,.<br>(5,294)|,.<br>(6,273)|,.<br>(10,335)|,.<br>(12,830)|,.<br>(11,865)|,.<br>(13,604)|,.<br>(18,062)|,.<br>(16,090)|,.<br>(13,131)|,.<br>(14,000)|
|P i f|<br>1,201.68|<br>5,234.46|<br>2,281.21|<br>8,402.00|<br>3,864.17|<br>12,784.78|<br>4,060.60|<br>15,846.50|<br>3,007.98|<br>11,034.81|
|er capta transers|(3,334)|(5,406)|(5,429)|(9,957)|(8,474)|(11,940)|(8,253)|(15,900)|(7,046)|(12,376)|
|Hhld i|4.63|2.97|4.54|3.00|4.49|2.72|4.35|2.63|4.50|2.82|
|ouseo sze|(1.81)|(1.85)|(1.71)|(1.92)|(1.71)|(1.73)|(1.60)|(1.67)|(1.70)|(1.80)|
|Nb f hild 014|1.47|0.72|1.43|0.72|1.39|0.56|1.53|0.69|1.45|0.67|
|umer o cren age -|(1.35)|(1.14)|(1.39)|(1.21)|(1.40)|(1.04)|(1.38)|(1.18)|(1.38)|(1.15)|
||<br>0.20|<br>0.31|<br>0.21|<br>0.32|<br>0.25|<br>0.36|<br>0.21|<br>0.36|<br>0.22|<br>0.34|
|Number of seniors|(0.49)|(0.47)|(0.50)|(0.47)|(0.55)|(0.49)|(0.51)|(0.49)|(0.51)|(0.48)|
|1-2 adults no child|0.12|0.42|0.13|0.42|0.15|0.49|0.14|0.50|0.14|0.46|
|,|(0.32)|(0.49)|(0.34)|(0.49)|(0.36)|(0.50)|(0.35)|(0.50)|(0.34)|(0.50)|
|12 dl 12 hild|<br>0.23|<br>0.18|<br>0.19|<br>0.16|<br>0.16|<br>0.15|<br>0.25|<br>0.18|<br>0.20|<br>0.16|
|- auts, - cren|(0.42)|(0.38)|(0.39)|(0.37)|(0.36)|(0.35)|(0.43)|(0.38)|(0.40)|(0.37)|
||<br>0.23|<br>0.11|<br>0.25|<br>0.10|<br>0.26|<br>0.09|<br>0.25|<br>0.11|<br>0.25|<br>0.10|
|1-2 adult, 3 or more children|(0.42)|(0.31)|(0.43)|(0.30)|(0.44)|(0.29)|(0.43)|(0.31)|(0.43)|(0.30)|
||0.23|0.20|0.25|0.21|0.26|0.20|0.21|0.16|0.24|0.19|
|3 adults or more, 0-1 child|(0.42)|(0.40)|(0.43)|(0.41)|(0.44)|(0.40)|(0.41)|(0.36)|(0.43)|(0.40)|
||014|007|014|008|014|005|012|004|014|006|
|3 adults or more, 2-3 children|.<br>(0.35)|.<br>(0.25)|.<br>(0.34)|.<br>(0.28)|.<br>(0.35)|.<br>(0.23)|.<br>(0.33)|.<br>(0.21)|.<br>(0.34)|.<br>(0.24)|
|3 adults or more 4 children or more|<br>0.05|<br>0.02|<br>0.04|<br>0.02|<br>0.03|<br>0.01|<br>0.03|<br>0.01|<br>0.04|<br>0.02|
|,|(0.21)|(0.14)|(0.19)|(0.15)|(0.18)|(0.12)|(0.17)|(0.11)|(0.19)|(0.13)|
|Rl|<br>0.56|<br>0.55|<br>0.55|<br>0.52|<br>0.55|<br>0.49|<br>0.57|<br>0.54|<br>0.56|<br>0.52|
|ura area|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|(0.50)<br>|
||0.44|0.45|0.45|0.48|0.45|0.51|0.43|0.46|0.44|0.48|
|Urban area|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

70
# **<u>Table B.2. Descriptive Statistics, West Bank and Gaza, 2007-2017</u>**

||**20**|**07**|**2**|**009**|**West Ban**<br>**2**|**k and Gaza**<br>**011**|**2**|**017**|**Pooled **|**2007-2017**|
|---|---|---|---|---|---|---|---|---|---|---|
||**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|
||44.45|57.75|43.99|57.96|45.06|58.27|45.37|59.97|44.77|58.61|
|Heads age|<br>(13.29)|<br>(16.31)|<br>(13.21)|<br>(15.03)|<br>(12.95)|<br>(13.61)|<br>(12.96)|<br>(13.16)|<br>(13.08)|<br>(14.16)|
|Hd d l i hl|0.15|0.52|0.14|0.53|0.12|0.50|0.12|0.43|0.13|0.49|
|ea oes not compete prmary scoo|(0.35)|(0.50)|(0.35)|(0.50)|(0.33)|(0.50)|(0.32)|(0.50)|(0.34)|(0.50)|
|Hd' hiht dti ll i i|0.52|0.24|0.48|0.28|0.49|0.31|0.49|0.37|0.49|0.31|
|eas ges eucaon eve s prmary|(0.50)|(0.43)|(0.50)|(0.45)|(0.50)|(0.46)|(0.50)|(0.48)|(0.50)|(0.46)|
|Head's hihest education level is secondar|0.16|0.12|0.17|0.11|0.18|0.10|0.16|0.08|0.17|0.10|
|g y|(0.36)|(0.32)|(0.38)|(0.31)|(0.38)|(0.30)|(0.37)|(0.28)|(0.38)|(0.30)|
|'|0.17|0.11|0.21|0.08|0.21|0.09|0.23|0.11|0.21|0.10|
|Heads highest education level is tertiary|(0.38)|(0.32)|(0.41)|(0.28)|(0.41)|(0.29)|(0.42)|(0.31)|(0.41)|(0.30)|
|Hd i id|0.01|0.06|0.01|0.11|0.01|0.10|0.00|0.00|0.01|0.07|
|ea s never marre|(0.10)|(0.25)|(0.09)|(0.31)|(0.08)|(0.30)|(0.00)|(0.00)|(0.08)|(0.26)|
|Head is mono married|<br>0.96|<br>0.09|<br>0.97|<br>0.12|<br>0.97|<br>0.10|<br>0.99|<br>0.20|<br>0.97|<br>0.13|
||(0.19)|(0.29)|(0.18)|(0.33)|(0.17)|(0.30)|(0.10)|(0.40)|(0.16)|(0.34)|
|Hd i l id|0.02|0.00|0.01|0.00|0.01|0.00|0.00|0.00|0.01|0.00|
|ea s poy marre|(0.12)|(0.00)|(0.11)|(0.00)|(0.10)|(0.00)|(0.00)|(0.00)|(0.09)|(0.00)|
|Hd i did/d|0.00|0.11|0.00|0.06|0.00|0.10|0.01|0.72|0.00|0.26|
|ea s vorceseparate|(0.00)|(0.31)|(0.05)|(0.25)|(0.06)|(0.30)|(0.09)|(0.45)|(0.06)|(0.44)|
|Hd i idd|0.01|0.73|0.01|0.71|0.01|0.70|0.00|0.08|0.01|0.53|
|ea s wowe|(0.11)|(0.44)|(0.10)|(0.46)|(0.10)|(0.46)|(0.05)|(0.27)|(0.09)|(0.50)|
|Hd i ld|<br>0.76|<br>0.21|<br>0.76|<br>0.23|<br>0.78|<br>0.24|||<br>0.77|<br>0.23|
|ea s empoye|(0.43)|(0.41)|(0.43)|(0.42)|(0.42)|(0.43)|||(0.42)|(0.42)|
|Hd i ld|0.12|0.02|0.08|0.01|0.08|0.02|||0.08|0.02|
|ea s unempoye|(0.32)|(0.14)|(0.27)|(0.11)|(0.27)|(0.15)|||(0.28)|(0.13)|
|Hd i hk/hif|0.00|0.56|0.00|0.47|0.14|0.08|||0.06|0.29|
|ea s omemaerousewe|(0.05)|(0.50)|(0.05)|(0.50)|(0.34)|(0.28)|||(0.24)|(0.45)|
|Hd i tdt|0.00|0.00|0.00|0.00|0.00|0.00|||0.00|0.00|
|ea s suen|(0.06)|(0.00)|(0.03)|(0.06)|(0.04)|(0.04)|||(0.04)|(0.04)|
||0.08|0.18|0.10|0.27|0.00|0.00|||0.05|0.13|
|Head is pensioner/retired/disabled|(0.27)|(0.39)|(0.30)|(0.44)|(0.00)|(0.00)|||(0.22)|(0.33)|
|Hd i h iii|0.04|0.03|0.06|0.02|0.01|0.66|||0.03|0.33|
|ea s oter actvtes|(0.20)|(0.18)|(0.24)|(0.13)|(0.10)|(0.48)|||(0.18)|(0.47)|
||9,147.45|14,179.85|11,758.84|15,823.72|13,164.33|16,983.40|12,202.69|16,567.52|12,095.51|16,304.18|
|Per capita consumption|<br>(9,668)|<br>(13,757)|<br>(10,971)|<br>(12,594)|<br>(12,794)|<br>(13,025)|<br>(9,668)|<br>(13,757)|<br>(11,135)|<br>(12,622)|
|Hhld i|<br>6.62|<br>3.84|<br>6.31|<br>3.44|<br>6.27|<br>3.63|<br>5.76|<br>3.34|<br>6.17|<br>3.51|
|ouseo sze|(2.75)|(2.86)|(2.67)|(2.34)|(2.54)|(2.86)|(2.31)|(2.51)|(2.55)|(2.62)|
||2.69|0.99|2.42|0.71|2.38|0.81|2.31|0.70|2.40|0.77|
|Number of children age 0-14|(1.95)|(1.60)|(1.93)|(1.41)|(1.85)|(1.52)|(1.86)|(1.32)|(1.89)|(1.44)|
|Nb f i|<br>0.22|<br>0.40|<br>0.19|<br>0.42|<br>0.19|<br>0.42|<br>0.17|<br>0.41|<br>0.19|<br>0.42|
|umer o senors|(0.51)|(0.50)|(0.50)|(0.51)|(0.49)|(0.53)|(0.46)|(0.50)|(0.49)|(0.51)|
||0.07|0.37|0.07|0.42|0.07|0.44|||0.07|0.43|
|1-2 adults, no child|(0.25)|(0.49)|(0.25)|(0.49)|(0.25)|(0.50)|||(0.25)|(0.49)|
||0.09|0.15|0.13|0.08|0.10|0.08|||0.11|0.09|
|1-2 adults, 1-2 children|(0.29)|(0.36)|(0.34)|(0.28)|(0.31)|(0.27)|||(0.32)|(0.28)|
||0.37|0.12|0.33|0.11|0.34|0.09|||0.34|0.10|
|1-2 adult, 3 or more children|(0.48)|(0.32)|(0.47)|(0.32)|(0.47)|(0.29)|||(0.47)|(0.31)|
|dl 1 hild|<br>0.13|<br>0.22|<br>0.14|<br>0.26|<br>0.17|<br>0.22|||<br>0.15|<br>0.23|
|3 auts or more, 0- c|(0.33)|(0.42)|(0.35)|(0.44)|(0.37)|(0.42)|||(0.36)|(0.42)|
||<br>0.15|<br>0.07|<br>0.15|<br>0.08|<br>0.14|<br>0.09|||<br>0.15|<br>0.09|
|3 adults or more, 2-3 children|(0.36)|(0.25)|(0.36)|(0.28)|(0.35)|(0.29)|||(0.35)|(0.28)|
||0.20|0.08|0.18|0.04|0.18|0.07|||0.18|0.06|
|3 adults or more, 4 children or more|<br>(0.40)|<br>(0.27)|<br>(0.38)|<br>(0.20)|<br>(0.38)|<br>(0.26)|||<br>(0.38)|<br>(0.24)|
|Rral area|<br>0.29|<br>0.26|<br>0.17|<br>0.22|<br>0.17|<br>0.18|0.18|0.17|<br>0.18|<br>0.20|
|u|(0.45)<br>|(0.44)<br>|(0.37)<br>|(0.42)<br>|(0.38)<br>|(0.39)<br>|(0.38)<br>|(0.37)<br>|(0.39)<br>|(0.40)<br>|
||0.57|0.60|0.74|0.68|0.74|0.72|0.73|0.72|0.72|0.70|
|Urban area|(0.50)|(0.49)|(0.44)|(0.47)|(0.44)|(0.45)|(0.44)|(0.45)|(0.45)|(0.46)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

71
**<u>Table B.3. Descriptive Statistics, Tunisia 2005-2021</u>**

||**2**|**005**|**2**|**010**|**Tu**<br>**20**|**nisia**<br>**15**|**2**|**021**|**Pooled **|**2005-2021**|
|---|---|---|---|---|---|---|---|---|---|---|
||**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|
|Heads ae|52.12|57.74|53.44|59.52|53.38|60.99|55.40|61.95|53.72|60.31|
|g|(14.07)|(15.18)|(13.74)|(15.60)|(13.65)|(14.86)|(13.53)|(14.47)|(13.78)|(15.04)|
|Head does not complete|0.75|0.92|0.77|0.93|0.19|0.57|0.13|0.48|0.42|0.68|
|primary school|(0.43)|(0.27)|(0.42)|(0.26)|(0.39)|(0.50)|(0.34)|(0.50)|(0.49)|(0.47)|
|Head's highest education level|0.04|0.01|0.03|0.02|0.39|0.25|0.42|0.30|0.25|0.17|
|is primary|(0.20)|(0.12)|(0.18)|(0.12)|(0.49)|(0.43)|(0.49)|(0.46)|(0.43)|(0.38)|
|Head's highest education level|0.12|0.05|0.11|0.04|0.29|0.13|0.32|0.16|0.22|0.10|
|is secondary|(0.32)|(0.21)|(0.31)|(0.20)|(0.46)|(0.34)|(0.47)|(0.36)|(0.42)|(0.31)|
|Head's highest education level|0.09|0.02|0.09|0.02|0.13|0.05|0.13|0.06|0.11|0.04|
|is tertiary|(0.28)|(0.14)|(0.29)|(0.14)|(0.33)|(0.22)|(0.33)|(0.23)|(0.31)|(0.20)|
|<br>|<br>0.02|<br>0.06|<br>0.01|<br>0.04|<br>0.03|<br>0.08|<br>0.03|<br>0.08|<br>0.02|<br>0.07|
|Head is never married|(0.13)|(0.24)|(0.11)|(0.19)|(0.17)|(0.27)|(0.17)|(0.27)|(0.15)|(0.25)|
|Head is mono married|0.96|0.19|0.97|0.20|0.95|0.13|0.95|0.10|0.95|0.15|
||(0.20)|(0.39)|(0.18)|(0.40)|(0.22)|(0.34)|(0.22)|(0.30)|(0.21)|(0.35)|
||0.01|0.08|0.00|0.08|0.01|0.09|0.01|0.10|0.00|0.09|
|Head is divorced/separated|(0.07)|(0.26)|(0.06)|(0.27)|(0.07)|(0.29)|(0.07)|(0.30)|(0.07)|(0.29)|
|Head is widowed|0.02|0.67|0.02|0.69|0.02|0.70|0.02|0.71|0.02|0.69|
||(0.14)|(0.47)|(0.14)|(0.46)|(0.13)|(0.46)|(0.13)|(0.45)|(0.13)|(0.46)|
|Hd i ld|<br>0.74|<br>0.24|<br>0.71|<br>0.17|||||<br>0.72|<br>0.21|
|ea s empoye|(0.44)|(0.43)|(0.46)|(0.38)|||||(0.45)|(0.40)|
|Hd i ld|0.02|0.01|0.02|0.01|||||0.02|0.01|
|ea s unempoye|(0.15)|(0.10)|(0.15)|(0.07)|||||(0.15)|(0.09)|
|Head is|<br>0.00|<br>0.41|<br>0.01|<br>0.49|||||<br>0.00|<br>0.45|
|homemaker/housewife|(0.05)|(0.49)|(0.07)|(0.50)|||||(0.06)|(0.50)|
|Head is student|0.00|0.01|0.00|0.00|||||0.00|0.00|
||(0.04)|(0.09)|(0.02)|(0.02)|||||(0.03)|(0.06)|
|Head is|<br>0.22|<br>0.32|<br>0.26|<br>0.33|||||<br>0.24|<br>0.32|
|pensioner/retired/disabled|(0.42)|(0.46)|(0.44)|(0.47)|||||(0.43)|(0.47)|
||000|002|000|001|||||000|001|
|Head is other activities|.<br>|.<br>|.<br>|.<br>|||||.<br>|.<br>|
||(0.07)|(0.15)|(0.05)|(0.08)|||||(0.06)|(0.12)|
|P it ti|<br>2,027.76|<br>2,252.64|<br>2,823.94|<br>3,156.40|4,310.95|4,892.92|5,999.25|6,886.89|<br>3,976.12|<br>4,634.09|
|er capa consumpon|(2,206.66)|(2,473.81)|(2,604.83)|(2,640.10)|(4,590.12)|(4,002.85)|(7,378.56)|(6,515.51)|(5,136.62)|(4,910.49)|
|Household size|4.77<br>|3.25<br>|4.55<br>|3.11<br>|4.26<br>|2.79<br>|3.97<br>|2.61<br>|4.35<br>|2.89<br>|
||(1.88)|(1.96)|(1.73)|(1.75)|(1.60)|(1.60)|(1.45)|(1.39)|(1.68)|(1.67)|
|Nb f hild 014|1.21|0.57|1.01|0.50|1.08|0.40|0.95|0.36|1.05|0.44|
|umer o cren age -|(1.26)|(1.07)|(1.19)|(0.99)|(1.23)|(0.86)|(1.18)|(0.83)|(1.21)|(0.93)|
||0.38|0.43|0.38|0.46|0.35|0.47|||0.37|0.45|
|Number of seniors|(0.66)|(0.52)|(0.66)|(0.54)|(0.66)|(0.53)|||(0.66)|(0.53)|
|12 dlt hild|0.10|0.38|0.11|0.40|||0.19|0.52|0.14|0.45|
|- aus, no c|(0.31)<br>|(0.49)<br>|(0.32)<br>|(0.49)<br>|||(0.39)<br>|(0.50)<br>|(0.35)<br>|(0.50)<br>|
||0.20|0.12|0.20|0.13|||0.18|0.09|0.19|0.11|
|1-2 adults, 1-2 children|(0.40)|(0.32)|(0.40)|(0.33)|||(0.38)|(0.29)|(0.39)|(0.31)|
|1-2 adult 3 or more children|0.17|0.08|0.14|0.08|||0.10|0.03|0.13|0.06|
|,|(0.37)|(0.28)|(0.35)|(0.27)|||(0.30)|(0.17)|(0.34)|(0.23)|
||<br>0.32|<br>0.32|<br>0.39|<br>0.33|||<br>0.44|<br>0.32|<br>0.39|<br>0.32|
|3 adults or more, 0-1 child|(0.47)|(0.47)|(0.49)|(0.47)|||(0.50)|(0.47)|(0.49)|(0.47)|
|3 adults or more 2-3 children|0.16<br>|0.08<br>|0.14<br>|0.06<br>|||0.09<br>|0.04<br>|0.13<br>|0.06<br>|
|,|(0.37)|(0.27)|(0.35)|(0.24)|||(0.28)|(0.19)|(0.33)|(0.23)|
|3 adults or more, 4 children or|<br>0.04|<br>0.02|<br>0.02|<br>0.01|||<br>0.01|<br>0.00|<br>0.02|<br>0.01|
|more|(0.20)|(0.14)|(0.15)|(0.08)|||(0.07)|(0.04)|(0.14)|(0.09)|
||0.32|0.33|0.32|0.34|0.30|0.26|0.31|0.27|0.31|0.29|
|Rural area|(0.46)|(0.47)|(0.47)|(0.47)|(0.46)|(0.44)|(0.46)|(0.44)|(0.46)|(0.45)|
|Ub|0.68|0.67|0.68|0.66|0.70|0.74|0.69|0.73|0.69|0.71|
|ran area|(0.46)|(0.47)|(0.47)|(0.47)|(0.46)|(0.44)|(0.46)|(0.44)|(0.46)|(0.45)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

72
# **<u>Table B.4. Descriptive Statistics, Jordan 2010-2013</u>**

||**20**|**10**|**Jo**<br>**2**|**rdan**<br>**013**|**Pooled **|**2010-2013**|
|---|---|---|---|---|---|---|
||**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|
||47.62|58.63|47.49|58.96|47.55|58.80|
|Heads age|(14.13)|(13.68)|(14.04)|(13.24)|(14.08)|(13.45)|
|Hd d t lt i hl|0.15|0.53|0.12|0.49|0.13|0.51|
|ea oes no compee prmary scoo|(0.36)|(0.50)|(0.32)|(0.50)|(0.34)|(0.50)|
|'|0.47|0.27|0.47|0.30|0.47|0.28|
|Heads highest education level is primary|(0.50)|(0.44)|(0.50)|(0.46)|(0.50)|(0.45)|
|Head's hihest education level is secondar|0.15|0.08|0.14|0.09|0.15|0.09|
|g y|(0.36)|(0.28)|(0.34)|(0.28)|(0.35)|(0.28)|
|'|0.22|0.12|0.28|0.12|0.25|0.12|
|Heads highest education level is tertiary|(0.42)|(0.33)|(0.45)|(0.33)|(0.44)|(0.33)|
|Hd i id|0.02|0.06|0.02|0.07|0.02|0.07|
|ea s never marre|(0.13)|(0.25)|(0.14)|(0.25)|(0.14)|(0.25)|
|Head is mono married|<br>0.97|<br>0.19|<br>0.96|<br>0.17|<br>0.97|<br>0.18|
||(0.17)|(0.39)|(0.20)|(0.37)|(0.18)|(0.38)|
|Hd i l id|0.00|0.00|0.00|0.00|0.00|0.00|
|ea s poy marre|(0.06)|(0.00)|(0.06)|(0.00)|(0.06)|(0.00)|
|Hd i did/td|0.00|0.04|0.00|0.05|0.00|0.04|
|ea s vorceseparae|(0.03)|(0.19)|(0.06)|(0.22)|(0.05)|(0.20)|
|Hd i idd|0.01|0.71|0.01|0.72|0.01|0.72|
|ea s wowe|(0.08)|(0.45)|(0.11)|(0.45)|(0.10)|(0.45)|
|Hd i ld|0.66|0.04|0.67|0.05|0.66|0.05|
|ea s empoye|(0.47)|(0.20)|(0.47)|(0.22)|(0.47)|(0.21)|
|Hd i ld|0.04|0.01|0.07|0.04|0.06|0.02|
|ea s unempoye|(0.20)|(0.09)|(0.26)|(0.19)|(0.24)|(0.15)|
|Hd i hk/hif|0.00|0.79|0.00|0.75|0.00|0.77|
|ea s omemaerousewe|(0.02)|(0.41)|(0.00)|(0.43)|(0.01)|(0.42)|
|Head is student|0.00|0.00|0.00|0.00|0.00|0.00|
||(0.01)<br>|(0.00)<br>|(0.05)<br>|(0.04)<br>|(0.04)<br>|(0.03)<br>|
||0.12|0.15|0.14|0.14|0.13|0.14|
|Head is pensioner/retired/disabled|(0.33)|(0.35)|(0.35)|(0.34)|(0.34)|(0.35)|
||0.17|0.02|0.12|0.02|0.14|0.02|
|Head is other activities|(0.38)|(0.13)|(0.32)|(0.15)|(0.35)|(0.14)|
||206345|291621|223836|310082|215559|301097|
|Per capita consumption|,.<br>(3,263.14)|,.<br>(2,417.35)|,.<br>(1,578.64)|,.<br>(2,442.96)|,.<br>(2,521.48)|,.<br>(2,431.02)|
|P i f|<br>377.77|<br>1,107.40|<br>469.79|<br>1,114.52|<br>426.24|<br>1,111.05|
|er capta transers|(703.55)|(1,489.48)|(839.28)|(1,364.42)|(779.30)|(1,425.88)|
|Hhld i|5.66|3.64|5.36|3.49|5.50|3.56|
|ouseo sze|(2.18)|(2.28)|(2.12)|(2.51)|(2.15)|(2.40)|
||<br>1.93|<br>0.59|<br>1.80|<br>0.57|<br>1.86|<br>0.58|
|Number of children age 0-14|(1.70)|(1.14)|(1.66)|(1.42)|(1.68)|(1.29)|
||<br>0.26|<br>0.38|<br>0.23|<br>0.41|<br>0.24|<br>0.40|
|Number of seniors|(0.57)|(0.49)|(0.54)|(0.51)|(0.55)|(0.50)|
|1-2 adults no child|0.07<br>|0.36<br>|0.09<br>|0.39<br>|0.08<br>|0.37<br>|
|,|(0.26)|(0.48)|(0.28)|(0.49)|(0.27)|(0.48)|
|1-2 adlts 1-2 children|<br>0.13|<br>0.14|<br>0.15|<br>0.10|<br>0.14|<br>0.12|
|u,|(0.34)<br>|(0.35)<br>|(0.35)<br>|(0.30)<br>|(0.35)<br>|(0.32)<br>|
||0.30|0.06|0.29|0.06|0.29|0.06|
|1-2 adult, 3 or more children|(046)|(025)|(045)|(023)|(046)|(024)|
||.<br>0.23|.<br>0.29|.<br>0.25|.<br>0.34|.<br>0.24|.<br>0.32|
|3 adults or more, 0-1 child|(0.42)|(0.46)|(0.43)|(0.47)|(0.43)|(0.47)|
||015|010|013|008|014|009|
|3 adults or more, 2-3 children|.<br>(0.36)|.<br>(0.30)|.<br>(0.34)|.<br>(0.27)|.<br>(0.35)|.<br>(0.29)|
|3 adults or more 4 children or more|<br>0.11|<br>0.05|<br>0.09|<br>0.04|<br>0.10|<br>0.04|
|,|(0.31)|(0.22)|(0.29)|(0.18)|(0.30)|(0.20)|
|Rl|<br>0.16|<br>0.13|<br>0.17|<br>0.19|<br>0.17|<br>0.16|
|ura area|(0.37)<br>|(0.34)<br>|(0.37)<br>|(0.39)<br>|(0.37)<br>|(0.37)<br>|
||0.84|0.87|0.83|0.81|0.83|0.84|
|Urban area|(0.37)|(0.34)|(0.37)|(0.39)|(0.37)|(0.37)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

73
# **<u>Table B.5. Descriptive Statistics, Iraq 2007-2013</u>**

||**20**|**07**|**Ir**<br>**2**|**aq**<br>**012**|**Pooled **|**2007-2013**|
|---|---|---|---|---|---|---|
||**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|
||45.15|54.29|46.93|54.28|46.73|54.28|
|Heads age|(13.71)|(13.04)|(13.06)|(12.51)|(13.14)|(12.58)|
|Hd d t lt i hl|0.31|0.75|0.34|0.72|0.34|0.72|
|ea oes no compee prmary scoo|(0.46)|(0.43)|(0.47)|(0.45)|(0.47)|(0.45)|
|'|0.41|0.17|0.41|0.20|0.41|0.20|
|Heads highest education level is primary|(0.49)|(0.38)|(0.49)|(0.40)|(0.49)|(0.40)|
|Hd' hih di ll i d|0.11|0.02|0.09|0.03|0.09|0.03|
|eas gest eucaton eve s seconary|(0.31)|(0.14)|(0.28)|(0.17)|(0.28)|(0.17)|
|Hd' hiht dti ll i tti|0.17|0.06|0.16|0.05|0.16|0.05|
|eas ges eucaon eve s erary|(0.38)|(0.23)|(0.36)|(0.22)|(0.37)|(0.22)|
|Head i neer married|0.02|0.04|0.01|0.02|0.01|0.02|
|s v|(0.13)|(0.20)|(0.09)|(0.14)|(0.10)|(0.15)|
|Head is mono married|<br>0.95|<br>0.08|<br>0.95|<br>0.15|<br>0.95|<br>0.14|
||(0.21)|(0.27)|(0.22)|(0.35)|(0.22)|(0.34)|
|Hd i l id|0.01|0.00|0.03|0.00|0.03|0.00|
|ea s poy marre|(0.11)|(0.00)|(0.17)|(0.00)|(0.16)|(0.00)|
|Hd i did/td|0.00|0.07|0.00|0.06|0.00|0.06|
|ea s vorceseparae|(0.04)|(0.25)|(0.04)|(0.25)|(0.04)|(0.25)|
|Hd i idd|0.01|0.81|0.01|0.77|0.01|0.77|
|ea s wowe|(0.12)|(0.39)|(0.10)|(0.42)|(0.11)|(0.42)|
|Head is emloed|<br>0.79|<br>0.19|<br>0.78|<br>0.15|<br>0.78|<br>0.16|
|py|(0.41)|(0.40)|(0.42)|(0.36)|(0.42)|(0.36)|
|Head is unemloed|0.03|0.02|0.02|0.01|0.02|0.01|
|py|(0.18)|(0.13)|(0.15)|(0.08)|(0.15)|(0.09)|
|Hd i hk/hif|0.00|0.69|0.00|0.53|0.00|0.55|
|ea s omemaerousewe|(0.02)|(0.46)|(0.03)|(0.50)|(0.03)|(0.50)|
|Hd i tdt|0.00|0.00|0.00|0.00|0.00|0.00|
|ea s suen|(0.04)|(0.00)|(0.04)|(0.02)|(0.04)|(0.02)|
|i iiil|<br>0.14|<br>0.08|<br>0.18|<br>0.30|<br>0.18|<br>0.27|
|Head s pensoner/retred/dsabed|(0.35)|(0.27)|(0.39)|(0.46)|(0.38)|(0.45)|
||0.03|0.03|0.02|0.01|0.02|0.01|
|Head is other activities|(0.17)|(0.16)|(0.12)|(0.08)|(0.13)|(0.10)|
||187883975|201149891|285561371|307240417|274644313|293369042|
|Per capita consumption|,,.<br>(1,662,430)|,,.<br>(1,562,966)|,,.<br>(2,612,256)|,,.<br>(2,728,793)|,,.<br>(2,542,574)|,,.<br>(2,630,373)|
|P it tf|166.71|409.56|249.20|647.95|239.98|616.79|
|er capa ransers|(415.53)|(941.59)|(902.11)|(1,940.46)|(861.86)|(1,842.51)|
|Hhld i|7.00|5.76|8.49|7.64|8.33|7.39|
|ouseo sze|(3.43)|(3.46)|(4.21)|(4.22)|(4.16)|(4.18)|
|Nb f hild 014|2.69|1.64|3.46|2.75|3.37|2.61|
|umer o cren age -|(2.12)|(2.00)|(2.55)|(2.68)|(2.51)|(2.63)|
||0.22|0.27|0.24|0.24|0.24|0.25|
|Number of seniors|(0.51)|(0.49)|(0.52)|(0.46)|(0.52)|(0.46)|
|1-2 adults no child|0.04|0.14|0.01|0.04|0.01|0.05|
|,|(0.20)|(0.35)|(0.11)|(0.19)|(0.12)|(0.22)|
|12 dlt 12 hild|<br>0.14|<br>0.08|<br>0.06|<br>0.05|<br>0.07|<br>0.06|
|- aus, - cren|(0.34)|(0.28)|(0.25)|(0.23)|(0.26)|(0.23)|
||<br>0.29|<br>0.13|<br>0.27|<br>0.15|<br>0.27|<br>0.15|
|1-2 adult, 3 or more children|(0.45)|(0.34)|(0.44)|(0.35)|(0.44)|(0.35)|
||0.15|0.30|0.11|0.21|0.11|0.22|
|3 adults or more, 0-1 child|(0.35)|(0.46)|(0.31)|(0.41)|(0.32)|(0.42)|
||016|018|018|026|018|025|
|3 adults or more, 2-3 children|.<br>(0.37)|.<br>(0.38)|.<br>(0.39)|.<br>(0.44)|.<br>(0.39)|.<br>(0.43)|
|3 adults or more 4 children or more|<br>0.22|<br>0.16|<br>0.36|<br>0.29|<br>0.35|<br>0.27|
|,|(0.42)|(0.37)|(0.48)|(0.45)|(0.48)|(0.45)|
|Rl|<br>0.27|<br>0.20|<br>0.33|<br>0.22|<br>0.32|<br>0.22|
|ura area|(0.44)<br>|(0.40)<br>|(0.47)<br>|(0.42)<br>|(0.47)<br>|(0.41)<br>|
||0.73|0.80|0.67|0.78|0.68|0.78|
|Urban area|(0.44)|(0.40)|(0.47)|(0.42)|(0.47)|(0.41)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

74
# **<u>Table B.6. Descriptive Statistics, Mauritania 2004-2019</u>**

||||||**Maurita**|**nia**|||||
|---|---|---|---|---|---|---|---|---|---|---|
||**20**|**04 **|**20**|**08**|**20**|**14**|**2**|**019**|**Pooled **|**2004-2019**|
||**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|**MHH**|**FHH**|
|Hd|48.10|53.29|48.22|47.33|49.11|48.05|49.63|46.83|48.83|48.01|
|eas age|(13.60)|(14.09)|(14.06)|(15.24)|(14.49)|(15.80)|(14.29)|(15.25)|(14.16)|(15.40)|
|Head does not complete primary school|0.77<br>|0.93<br>|0.72<br>|0.85<br>|0.70<br>|0.81<br>|0.48<br>|0.50<br>|0.66<br>|0.72<br>|
||(0.42)|(0.25)|(0.45)|(0.35)|(0.46)|(0.39)|(0.50)|(0.50)|(0.47)|(0.45)|
|'|0.08|0.03|0.11|0.09|0.11|0.11|0.26|0.33|0.15|0.18|
|Heads highest education level is primary|(0.28)|(0.17)|(0.31)|(0.29)|(0.32)|(0.32)|(0.44)|(0.47)|(0.35)|(0.38)|
|d' hih di ll i d|0.11|0.03|0.12|0.05|0.13|0.07|0.18|0.16|0.14|0.09|
|Heas gest eucaton eve s seconary|(0.31)|(0.18)|(0.33)|(0.21)|(0.34)|(0.25)|(0.38)|(0.36)|(0.34)|(0.29)|
|Hd' hih di ll i i|<br>0.04|<br>0.01|<br>0.05|<br>0.01|<br>0.06|<br>0.01|<br>0.08|<br>0.01|<br>0.06|<br>0.01|
|eas gest eucaton eve s tertary|(0.19)|(0.08)|(0.22)|(0.08)|(0.24)|(0.08)|(0.27)|(0.10)|(0.23)|(0.09)|
|Hd i id|<br>0.03|<br>0.02|<br>0.02|<br>0.01|<br>0.03|<br>0.02|<br>0.03|<br>0.02|<br>0.03|<br>0.02|
|ea s never marre|(0.17)|(0.15)|(0.16)|(0.12)|(0.17)|(0.13)|(0.17)|(0.13)|(0.16)|(0.13)|
|Head is mono married|0.94|0.10|0.95|0.39|0.94|0.43|0.88|0.50|0.93|0.41|
||(0.24)|(0.30)|(0.22)|(0.49)|(0.23)|(0.50)|(0.32)|(0.50)|(0.26)|(0.49)|
|Hd i l id|0.00|0.00|0.00|0.00|0.00|0.00|0.06|0.03|0.02|0.01|
|ea s poy marre|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.23)|(0.17)|(0.12)|(0.11)|
|Hd i did/d|<br>0.02|<br>0.33|<br>0.01|<br>0.22|<br>0.02|<br>0.21|<br>0.02|<br>0.18|<br>0.02|<br>0.21|
|ea s vorceseparate|(0.14)|(0.47)|(0.12)|(0.42)|(0.13)|(0.40)|(0.13)|(0.39)|(0.13)|(0.41)|
|Hd i idd|0.01|0.55|0.01|0.37|0.01|0.35|0.01|0.27|0.01|0.35|
|ea s wowe|(0.11)|(0.50)|(0.11)|(0.48)|(0.11)|(0.48)|(0.12)|(0.44)|(0.11)|(0.48)|
|Hd i ld|0.86|0.54|0.78|0.40|0.87|0.40|0.81|0.37|0.83|0.41|
|ea s empoye|(0.35)|(0.50)|(0.41)|(0.49)|(0.33)|(0.49)|(0.39)|(0.48)|(0.37)|(0.49)|
||0.02|0.02|0.04|0.02|0.01|0.02|0.01|0.01|0.02|0.02|
|Head is unemployed|(0.15)|(0.12)|(0.19)|(0.13)|(0.08)|(0.13)|(0.11)|(0.11)|(0.14)|(0.12)|
|Head is not searched and not work|0.12<br>|0.45<br>|0.18<br>|0.59<br>|0.12<br>|0.58<br>|0.18<br>|0.61<br>|0.15<br>|0.58<br>|
||(0.32)|(0.50)|(0.38)|(0.49)|(0.32)|(0.49)|(0.38)|(0.49)|(0.36)|(0.49)|
|i i|<br>184,984.25|<br>147,570.28|<br>240,551.50|<br>219,258.68|<br>341,658.92|<br>350,431.69|<br>373,240.01|<br>403,696.14|<br>294,662.55|<br>315,850.25|
|Per capta consumpton|(2587509)|(205663)|(234972)|(168764)|(299510)|(247036)|(264805)|(268529)|(1,189,714)|(252,048)|
|Hhld i|5.94|4.40|5.87|4.68|6.05|5.03|6.46|5.59|6.10|5.08|
|ouseo sze|(2.77)|(2.44)|(2.88)|(2.47)|(3.44)|(2.61)|(3.59)|(2.98)|(3.24)|(2.73)|
|Number of children age 0-14|2.56<br>|1.63<br>|2.53<br>|2.12<br>|2.68<br>|2.33<br>|2.86<br>|2.66<br>|2.67<br>|2.32<br>|
||(2.01)|(1.73)|(2.03)|(1.84)|(2.29)|(1.98)|(2.41)|(2.01)|(2.21)|(1.96)|
||0.19|0.27|0.21|0.20|0.25|0.23|0.27|0.23|0.23|0.23|
|Number of seniors|(0.44)|(0.46)|(0.47)|(0.41)|(0.51)|(0.44)|(0.56)|(0.46)|(0.50)|(0.44)|
|12 dlt hild|0.08|0.19|0.10|0.13|0.10|0.11|0.09|0.07|0.09|0.11|
|- aus, no c|(0.28)|(0.39)|(0.29)|(0.33)|(0.29)|(0.31)|(0.28)|(0.25)|(0.29)|(0.31)|
|1-2 adults 1-2 children|0.16|0.21|0.16|0.22|0.14|0.19|0.12|0.19|0.14|0.20|
|,|(0.37)|(0.40)|(0.36)|(0.41)|(0.35)|(0.40)|(0.33)|(0.39)|(0.35)|(0.40)|
||<br>0.20|<br>0.14|<br>0.20|<br>0.24|<br>0.23|<br>0.26|<br>0.20|<br>0.26|<br>0.21|<br>0.24|
|1-2 adult, 3 or more children|(0.40)|(0.35)|(0.40)|(0.43)|(0.42)|(0.44)|(0.40)|(0.44)|(0.41)|(0.43)|
|dl 1 hild|<br>0.19|<br>0.26|<br>0.19|<br>0.20|<br>0.18|<br>0.20|<br>0.18|<br>0.17|<br>0.18|<br>0.19|
|3 auts or more, 0- c|(0.39)|(0.44)|(0.39)|(0.40)|(0.38)|(0.40)|(0.38)|(0.37)|(0.39)|(0.40)|
||017|013|018|013|017|014|019|017|018|015|
|3 adults or more, 2-3 children|.<br>(0.38)|.<br>(0.34)|.<br>(0.38)|.<br>(0.34)|.<br>(0.38)|.<br>(0.34)|.<br>(0.39)|.<br>(0.37)|.<br>(0.38)|.<br>(0.35)|
||<br>0.19|<br>0.07|<br>0.18|<br>0.09|<br>0.18|<br>0.11|<br>0.23|<br>0.15|<br>0.20|<br>0.12|
|3 adults or more, 4 children or more|(0.39)|(0.25)|(0.38)|(0.28)|(0.39)|(0.31)|(0.42)|(0.36)|(0.40)|(0.32)|
||<br>0.62|<br>0.57|<br>0.54|<br>0.64|<br>0.49|<br>0.56|<br>0.52|<br>0.57|<br>0.54|<br>0.58|
|Rural area|||||||||||
||(0.49)|(0.49)|(0.50)|(0.48)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.49)|
|Ub|0.38|0.43|0.46|0.36|0.51|0.44|0.48|0.43|0.46|0.42|
|ran area|(0.49)|(0.49)|(0.50)|(0.48)|(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|(0.49)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

75
# **-** **<u>Table B.7. Descriptive Statistics, all countries years</u>**

||**MHH**<br>|**FHH**<br>|
|---|---|---|
|Heads ae|48.14|55.52|
|g|(13.61)<br>|(14.10)<br>|
||0.36|0.70|
|Head does not complete primary school|(0.48)<br>|(0.46)<br>|
|Head's highest education level is primary|0.38<br>(0.48)<br>|0.19<br>(0.40)<br>|
|Head's hihest education level is secondar|0.12|0.06|
|g y|(0.32)<br>|(0.23)<br>|
|Hd' hiht dti ll i tti|0.15|0.05|
|eas ges eucaon eve s erary|(0.36)<br>|(0.21)<br>|
||0.01|0.04|
|Head is never married|(0.11)|(0.19)|
|Hd i id|0.95|0.17|
|ea s mono marre|(0.22)|(0.37)|
||0.02|0.03|
|Head is poly married|(0.15)|(0.16)|
||0.01|0.25|
|Head is divorced/separated|<br>(0.07)|<br>(0.43)|
|Head is widowed|0.01<br>|0.71<br>|
||(0.11)<br>|(0.45)<br>|
|Hd i ld|0.77|0.19|
|ea s empoye|(0.42)|(0.39)|
||0.03|0.01|
|Head is unemployed|<br>(0.16)|<br>(0.10)|
|Head is homemaker/housewife|0.01<br>|0.55<br>|
||(0.08)<br>|(0.50)<br>|
|d i d|0.00|0.00|
|Hea s stuent|(0.04)|(0.03)|
||0.18|0.27|
|Head is pensioner/retired/disabled|<br>(0.39)|<br>(0.45)|
|Head is other activities|0.02|0.01|
||(0.15)<br>|(0.11)<br>|
|P it ti|2,034,242.98|1,731,419.27|
|er capa consumpon|(2,496,523)|(2,451,185)|
|Per capita transfers|204.12<br>|471.50<br>|
||(805.10)|(1,655.70)|
|Household size|7.39|5.75|
||(4.05)<br>|(3.99)<br>|
||2.85|1.89|
|Number of children|(2.46)|(2.38)|
||0.26|0.29|
|Number of seniors|<br>(0.54)|<br>(0.48)|
|12 dlt hild|0.04|0.16|
|- aus, no c|(0.19)<br>|(0.37)<br>|
||0.10|0.09|
|1-2 adults, 1-2 children|(0.29)|(0.28)|
|1-2 adult, 3 or more children|0.25<br>|0.13<br>|
||(0.43)|(0.34)|
|3 adults or more 0-1 child|0.16|0.25|
|,|(0.37)<br>|(0.43)<br>|
|3 adults or more, 2-3 children|0.17<br>(0.38)|0.19<br>(0.39)|
||028|019|
|3 adults or more, 4 children or more|.<br>(0.45)|.<br>(0.39)|
|Rural area|0.32|0.27|
||(0.47)<br>|(0.45)<br>|
||0.68|0.73|
|Urban area|(0.47)|(0.45)|

Note: Household sampling weights are applied. Standard deviations are in parentheses. FHHs and MHHs are self-reported.

76
# **Appendix C: Synthetic Panel Method**

This appendix offers a brief overview of the synthetic panel method based on Dang and Lanjouw (2023). Recent validations and applications of the synthetic panel methods by various researchers for different country contexts ranging from Africa to Latin America, the Middle East, and Europe have been encouraging in terms of accurate projections of economic status (Ferreira _et al._ , 2012; Beegle _et al._ , 2016; UNDP, 2016; OECD, 2018; Salvuci and Tarp, 2021; Ghomi, 2022). Let i be a vector of household characteristics observed in survey round _j_ (j= 1 or 2) that are also observed in the other survey round for household _i_ , i= 1,..., N.<sup>17</sup> These household characteristics can include such time-invariant variables as ethnicity, religion, language, place of xx birth, parental education, and other time-varying household characteristics if retrospective questions about the round-1 values of such characteristics are asked in the second round survey. To reduce spurious changes due to changes in household composition over time, we usually restrict the estimation samples to household heads in a certain age range, say 25 to 55, in the first cross section and adjust this age range accordingly in the second cross section. This restriction also helps ensure certain variables such as heads’ education attainment remains relatively stable over time (assuming most heads are finished with their schooling).<sup>18</sup> This age range is usually used in traditional pseudo-panel analysis but can vary depending on the cultural and economic factors in each specific setting. Population weights are then employed to provide estimates that represent the whole population. Then let i represent household consumption or income in survey round _j_ , j= 1 or 2. The linear projection of household consumption (or income) on household characteristics for each survey round is given by yy ′ i i i (C1) Let be the poverty line in period _j_ . We are interested in knowing the unconditional measures ii yy = ββ xx + εε of poverty mobility such as ii zz 1 2) (C2) which represents the percentage of households that are poor in the first survey round (year) but ii1 ii2 nonpoor in the second survey round, or the conditional measures such as PP(yy < zz aai yy > zz 2 1) (C3) which represents the percentage of poor households in the first round that escape poverty in the ii2 ii1 second round. PP(yy > zz | yy < zz

If true panel data are available, we can straightforwardly estimate the quantities in (C2) and (C3); but in the absence of such data, we can use synthetic panels to study mobility. To operationalize the framework, we make two standard assumptions. First, we assume that the underlying population being sampled in survey rounds 1 and 2 are identical such that their timeinvariant characteristics remain the same over time. More specifically, coupled with equation (C1), this implies the conditional distribution of expenditure in a given period is identical whether it is conditional on the given household characteristics in period 1 or period 2 (i.e., implies and have identical distributions) (Assumption 1). Second, we assume that i1 and ii1 ii2 i2 have a bivariate normal distribution with positive correlation coefficient ρ and standard xx = xx ii1 ii1 ii1 ii2 yydeviations |xx yy1 and |xx σ 2 respectively (Assumption 2). Quantity (2) can be estimated by εε εε εε εε σσ

> 17 We suppress the index for countries and FHH types to make notation less cluttered in this appendix.

> 18 While household heads may still increase their educational achievement in theory, this rarely happens in practice.

77
1−β1<sup>′</sup> <u>i2</u> 2−β2<sup>′</sup> <u>i2</u> 1 2) = Φ2 , − (C4) ~~�~~ zz xx zz xx where Φ 2(. ) stands for the bivariate normal cumulative distribution function (cdf), and PP(yyii1 < zz aai yyii2 > zz σσεε1 σσεε2 , −ρρ� 2(. ) stands for the bivariate normal probability density function (pdf). Note that in Equation (1), the estimated parameters obtained from data in both survey rounds are applied to data from the second φφ survey round (x2) (or the base year) for prediction, but we can use data from the first survey round as the base year as well. It is then straightforward to estimate quantity (C3) by dividing quantity 1−β1<sup>′</sup> <u>i2</u> (C2) by Φ , where Φ (. ) stands for the univariate normal cumulative distribution � ~~�~~ zz xx function (cdf). σσεε1 In Equation (4), the parameters and are estimated from Equation (C1), and ρ can be estimated using an approximation of the correlation of the cohort-aggregated household ii εεii ββ σσ consumption between the two surveys ( ). In particular, given an approximation of , where c indexes the cohorts constructed from the household survey data, the partial correlation yycc1yycc2 yycc1yycc2 coefficient ρ can be estimated by ρρ ρρ <u>i1 i2</u> ) 1<sup>′</sup> 2 (C5) ρρyy yy �vvaavv(yyii1)vvaavv(yyii2 −ββ vvaavv(xxii)ββ An alternative way to estimate ρρ= is to further assume that there is a cohort fixed effect in the σσεε1σσεε2 error terms and aggregate all the time-invariant variables to the cohort level and use the following equation ρρ i i i (C6) where the error term i includes a cohort fixed effect and the error i . ii yy = ββ ′xx + εε Note that the standard errors of estimates based on the synthetic panels can in fact be even ii εε ττ νν smaller than that of the true (or design-based) rate if there is a good model fit (or the sample size in the target survey is significantly larger than that in the base survey; see Dang and Lanjouw, 2023, for discussion).

Tables C.1-C.6 present the estimation results using Equation (C1) for all the countries and survey rounds. Tables C.7-C.12 present the descriptive statistics of the estimation sample. These tables show that while most of the time-invariant characteristics show similar distributions across survey rounds (and satisfy Assumption 1), some do not. For example, these include the shares of household heads achieving primary education or secondary education in the Arab Republic of Egypt during 2012-2015 (Table C.7). But the differences are practically very close to 0. Table C.13 presents the estimates for using Equations (C5) and (C6), where are estimated using Equation (C5) for all countries with cohorts being defined by age interacted with household heads’ education. ρρ ρρ We also provide alternative estimates for using Equation (C6). Using these estimates, Figures C.1 and C.2 offer qualitatively similar results to Figures 5 and 6. ρρ 78
# **<u>Table C.1 First-stage regressions, Arab Republic of Egypt</u>**

||**2012-2**|**015**|**2015-2**|**017**|**2017-2**|**020**|
|---|---|---|---|---|---|---|
||**2012**|**2015**|**2015**|**2017**|**2017**|**2020**|
|Head`s age|0.006***|0.012***|0.010***|0.011***|0.009***|0.012***|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Head is female|0.141***|0.141***|0.136***|0.234***|0.226***|0.198***|
||(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|Highest education level is primary|0.142***|0.126***|0.123***|0.097***|0.099***|0.091***|
||(0.02)|(0.01)|(0.01)|(0.01)|(0.01)|(0.02)|
|Highest education level is secondary|0.199***|0.215***|0.209***|0.179***|0.173***|0.194***|
||(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
|Highest education level is tertiary|0.461***|0.482***|0.481***|0.395***|0.394***|0.486***|
||(0.02)|(0.01)|(0.01)|(0.01)|(0.01)|(0.02)|
|Urban|0.241***|0.210***|0.215***|0.126***|0.126***|0.162***|
||(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|(0.01)|
|_cons|7.995***|8.091***|8.196***|8.555***|8.604***|8.632***|
||(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
|adjusted R2|0.23|0.25|0.24|0.17|0.16|0.21|
|N|5102|8338|7836|8301|7799|7286|

**Note:** ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. Regression is estimated using Weighted Ordinary Least Squares. Household heads’ ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second round. The reference groups are household with no primary education and living in rural areas.

79
# **<u>Table C.2 First-stage regressions, Iraq</u>**

||**2007-**<br>**2007**|**2012**<br>**2012**|
|---|---|---|
|Head`s age|-0.001**<br>(0.00)|0.005***<br>(0.00)|
|Head is female|0.012|0.114***|
||(0.02)|(0.02)|
|Highest education level is primary|-0.015|0.069***|
||(0.01)|(0.01)|
|Highest education level is secondary|0.059***|0.305***|
||(0.02)|(0.02)|
|Highest education level is tertiary|0.183***|0.441***|
||(0.02)|(0.01)|
|Urban|0.326***|0.317***|
||(0.01)|(0.01)|
|_cons|13.917***|13.966***|
||(0.03)|(0.03)|
|adjusted R2|0.08|0.13|
|N|12895|18552|

**Note:** ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. Regression is estimated using Weighted Ordinary Least Squares. Household heads’ ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second round. The reference groups are household with no primary education and living in rural areas.

80
# **<u>Table C.3 First-stage regressions, Jordan</u>**

||**2010-**<br>**2010**|**2013**<br>**2013**|
|---|---|---|
|Head`s age|-0.002|0.004***|
||(0.00)|(0.00)|
|Head is female|0.213***|0.107***|
||(0.05)|(0.03)|
|Highest education level is primary|0.171***|0.280***|
||(0.04)|(0.03)|
|Highest education level is secondary|0.320***|0.449***|
||(0.05)|(0.04)|
|Highest education level is tertiary|0.666***|0.729***|
||(0.05)|(0.03)|
|Urban|0.022|0.037*|
||(0.03)|(0.02)|
|_cons|6.976***|6.718***|
||(0.08)|(0.06)|
|adjusted R2|0.16|0.18|
|N|1873|3437|

**Note:** ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. Regression is estimated using Weighted Ordinary Least Squares. Household heads’ ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second round. The reference groups are household with no primary education and living in rural areas.

81
# **<u>Table C.4 First-stage regressions, Mauritania</u>**

||**2004-**|**2008**|**2008-**|**2014**|**2014-**|**2019**|
|---|---|---|---|---|---|---|
||**2004**|**2008**|**2008**|**2014**|**2014**|**2019**|
|Head`s age|-0.007***|-0.003***|-0.006***|-0.004***|-0.007***|-0.004***|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Head is female|0.022|0.075***|0.065***|0.128***|0.103***|0.130***|
||(0.02)|(0.01)|(0.01)|(0.02)|(0.02)|(0.01)|
|Highest education level is primary|0.187***|0.143***|0.146***|0.073***|0.079***|-0.014|
||(0.03)|(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|Highest education level is secondary|0.384***|0.383***|0.382***|0.223***|0.245***|0.145***|
||(0.03)|(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|Highest education level is tertiary|0.708***|0.609***|0.621***|0.382***|0.408***|0.382***|
||(0.04)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
|Urban|0.342***|0.605***|0.596***|0.353***|0.380***|0.368***|
||(0.02)|(0.01)|(0.01)|(0.01)|(0.02)|(0.01)|
|_cons|11.532***|11.710***|11.819***|12.279***|12.356***|12.421***|
||(0.05)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|
|adjusted R2|0.18|0.32|0.32|0.16|0.18|0.18|
|N|6065|9269|9088|6672|6219|6425|

**Note:** ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. Regression is estimated using Weighted Ordinary Least Squares. Household heads’ ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second round. The reference groups are household with no primary education and living in rural areas.

82
# **<u>Table C.5 First-stage regressions, West Bank and Gaza</u>**

||**2007-**|**2009**|**2009-**|**2011**|**2011**|**-2017**|
|---|---|---|---|---|---|---|
||**2007**|**2009**|**2009**|**2011**|**2011**|**2017**|
|Head`s age|0.005|0.006***|0.005***|0.002|-0.000|0.012***|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Head is female|0.226**|0.206***|0.226***|0.133***|0.141***|0.160***|
||(0.11)|(0.05)|(0.06)|(0.05)|(0.05)|(0.06)|
|Highest education level is primary|0.177**|0.220***|0.214***|0.218***|0.210***|0.260***|
||(0.07)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|
|Highest education level is secondary|0.276***|0.344***|0.346***|0.339***|0.341***|0.373***|
||(0.09)|(0.04)|(0.04)|(0.04)|(0.04)|(0.05)|
|Highest education level is tertiary|0.585***|0.607***|0.606***|0.602***|0.606***|0.518***|
||(0.08)|(0.04)|(0.04)|(0.04)|(0.04)|(0.04)|
|Urban|-0.034|0.014|0.012|-0.064**|-0.070**|-0.240***|
||(0.05)|(0.03)|(0.03)|(0.03)|(0.03)|(0.03)|
|Refugee|-0.327***|-0.039|-0.034|-0.314***|-0.314***|-0.538***|
||(0.07)|(0.05)|(0.05)|(0.04)|(0.04)|(0.05)|
|_cons|8.288***|8.388***|8.457***|8.718***|8.828***|8.381***|
||(0.15)|(0.07)|(0.07)|(0.08)|(0.08)|(0.08)|
|adjusted R2|0.08|0.09|0.09|0.09|0.09|0.11|
|N|962|2944|2938|3288|3229|2815|

**Note:** ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. Regression is estimated using Weighted Ordinary Least Squares. Household heads’ ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second round. The reference groups are household with no primary education and living in rural areas.

83
# **<u>Table C.6 First-stage regressions, Tunisia</u>**

||**2005-**|**2010**|**2010-**|**2015**|**2015-**|**2021**|
|---|---|---|---|---|---|---|
||**2005**|**2010**|**2010**|**2015**|**2015**|**2021**|
|Head`s age|0.004***|0.008***|0.005***|0.008***|0.006***|0.014***|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Head is female|0.143***|0.053**|0.006|0.197***|0.184***|0.113***|
||(0.03)|(0.02)|(0.03)|(0.02)|(0.02)|(0.02)|
|Highest education level is primary|0.312***|0.305***|0.300***|0.210***|0.227***|0.142***|
||(0.04)|(0.04)|(0.04)|(0.01)|(0.02)|(0.02)|
|Highest education level is secondary|0.386***|0.293***|0.266***|0.443***|0.460***|0.354***|
||(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|(0.02)|
|Highest education level is tertiary|0.945***|0.764***|0.754***|0.904***|0.911***|0.704***|
||(0.03)|(0.02)|(0.03)|(0.02)|(0.02)|(0.02)|
|Urban|0.495***|0.497***|0.499***|0.355***|0.370***|0.287***|
||(0.02)|(0.01)|(0.02)|(0.01)|(0.01)|(0.01)|
|_cons|6.547***|6.747***|6.881***|7.006***|7.084***|7.183***|
||(0.05)|(0.04)|(0.05)|(0.03)|(0.03)|(0.04)|
|adjusted R2|0.30|0.29|0.29|0.29|0.29|0.21|
|N|6769|7507|6425|16456|13635|10520|

**Note:** ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. Regression is estimated using Weighted Ordinary Least Squares. Household heads’ ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second round. The reference groups are household with no primary education and living in rural areas.

84
# **<u>Table C.7. Descriptive statistics of estimation sample, Arab Republic of Egypt</u>**

|**Variables**||**2012-2015**|||**2015-2017**|||**2017-2020**||
|---|---|---|---|---|---|---|---|---|---|
||**2012**|**2015**|**diff**|**2015**|**2017**|**diff**|**2017**|**2020**|**diff**|
|L f r it nmtin|8.58|8.97|0.4***|8.95|9.32|0.4***|9.30|9.48|0.2***|
|og o pe capa cosupo|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd`|41.32|43.97|2.7***|42.23|44.20|2.0***|43.14|42.89|-0.3*|
|eas age|(0.12)|(0.09)|(0.1)|(0.09)|(0.09)|(0.1)|(0.09)|(0.10)|(0.1)|
|Hd i fml|0.13|0.13|0.0|0.12|0.13|0.0|0.12|0.13|0.0|
|ea s eae|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i i|0.13|0.15|0.0***|0.15|0.15|0.0|0.15|0.14|-0.0***|
|eas ges eucaon eve s prmary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i d|0.31|0.34|0.0**|0.35|0.36|0.0|0.37|0.37|0.0|
|eas ges eucaon eve s seconary|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd' hiht dti ll i tti|0.20|0.19|-0.0|0.19|0.18|-0.0|0.18|0.21|0.0***|
|eas ges eucaon eve s erary|(0.01)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Ub|0.42|0.42|-0.0|0.41|0.42|0.0|0.41|0.43|0.0**|
|ran area|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. The data are unweighted. Household heads' ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second survey round. The reference groups are household with no primary education and living in rural areas.

85
# **<u>Table C.8 Descriptive statistics of estimation sample, Iraq</u>**

||**2007**|**2007-2012**<br>**2012**|**diff**|
|---|---|---|---|
|Lo of er caita consumtion|14.22|14.67|0.1***|
|g p p p|(0.01)|(0.01)|(0.0)|
|Head` ae|40.46|44.28|1.7***|
|s g|(0.07)|(0.06)|(0.2)|
|Hd i fl|0.09|0.09|0.0|
|ea s emae|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i i|0.41|0.40|0.0***|
|eas ges eucaon eve s prmary|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i d|0.12|0.08|-0.0|
|eas ges eucaon eve s seconary|(0.00)|(0.00)|(0.0)|
|Hd' hih di ll i i|0.19|0.15|-0.0***|
|eas gest eucaton eve s tertary|(0.00)|(0.00)|(0.0)|
||0.68|0.60|-0.1***|
|Urban area|(0.00)|(0.00)|(0.0)|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. The data are unweighted. Household heads' ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second survey round. The reference groups are household with no primary education and living in rural areas.

86
# **<u>Table C.9 Descriptive statistics of estimation sample, Jordan</u>**

||**2010**|**2010-2013**<br>**2013**|**diff**|
|---|---|---|---|
|Lo of er caita consumtion|7.29|7.35|0.1***|
|g p p p|(0.01)|(0.01)|(0.0)|
|Hd`|41.00|42.72|1.7***|
|eas age|(0.18)|(0.14)|(0.2)|
|Hd i fl|0.09|0.09|0.0|
|ea s emae|(0.01)|(0.00)|(0.0)|
|Hd' hiht dti ll i i|0.51|0.55|0.0***|
|eas ges eucaon eve s prmary|(0.01)|(0.01)|(0.0)|
|Hd' hiht dti ll i d|0.16|0.15|-0.0|
|eas ges eucaon eve s seconary|(0.01)|(0.01)|(0.0)|
|Hd' hih di ll i i|0.23|0.19|-0.0***|
|eas gest eucaton eve s tertary|(0.01)|(0.01)|(0.0)|
||0.74|0.63|-0.1***|
|Urban area|(0.01)|(0.01)|(0.0)|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. The data are unweighted. Household heads' ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second survey round. The reference groups are household with no primary education and living in rural areas.

87
**<u>Table C.10 Descriptive statistics of estimation sample, Mauritania</u>**

|||**2004-2008**|||**2008-2014**|||**2014-201**|**9**|
|---|---|---|---|---|---|---|---|---|---|
||**2004**|**2008**|**diff**|**2008**|**2014**|**diff**|**2014**|**2019**|**diff**|
|L f i i|11.66|12.09|0.4***|12.10|12.54|0.4***|12.56|12.68|0.1***|
|og o per capta consumpton|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd`|42.41|43.90|1.5***|41.90|46.40|4.5***|42.42|45.49|3.1***|
|eas age|(0.10)|(0.08)|(0.1)|(0.08)|(0.10)|(0.1)|(0.10)|(0.11)|(0.1)|
|Hd i fl|0.16|0.29|0.1***|0.30|0.30|0.0|0.31|0.37|0.1***|
|ea s emae|(0.00)|(0.00)|(0.0)|(0.00)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd' hih di ll i i|0.10|0.11|0.0|0.12|0.12|-0.0|0.14|0.29|0.1***|
|eas gest eucaton eve s prmary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.01)|(0.0)|
|Hd' hiht dti ll i d|0.13|0.13|-0.0|0.13|0.13|0.0|0.15|0.19|0.0***|
|eas ges eucaon eve s seconary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hih di ll i i|0.05|0.05|0.0|0.05|0.05|0.0**|0.05|0.06|0.0|
|eas gest eucaton eve s tertary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Ub|0.51|0.48|-0.0***|0.47|0.59|0.1***|0.59|0.50|-0.1***|
|ran area|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. The data are unweighted. Household heads' ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second survey round. The reference groups are household with no primary education and living in rural areas.

88
**<u>Table C.11. Descriptive statistics of estimation sample, West Bank and Gaza</u>**

|||**2007-20**|**09**||**2009-20**|**11**||**2011-2**|**017**|
|---|---|---|---|---|---|---|---|---|---|
||**2007**|**2009**|**difference**|**2009**|**2011**|**difference**|**2011**|**2017**|**difference**|
|L f i i|8.78|9.06|0.3***|9.06|9.13|0.1***|9.13|9.23|0.1***|
|og o per capta consumpton|(0.02)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd`|40.03|40.72|0.7**|39.80|41.65|1.9***|40.71|44.94|4.2***|
|eas age|(0.25)|(0.15)|(0.3)|(0.15)|(0.14)|(0.2)|(0.14)|(0.16)|(0.2)|
|Hd i fl|0.06|0.06|0.0|0.06|0.07|0.0*|0.07|0.08|0.0|
|ea s emae|(0.01)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i i|0.55|0.50|-0.0***|0.50|0.51|0.0|0.51|0.51|-0.0|
|eas ges eucaon eve s prmary|(0.02)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd' hiht dti ll i d|0.18|0.17|-0.0|0.17|0.18|0.0|0.18|0.16|-0.0**|
|eas ges eucaon eve s seconary|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd' hiht dti ll i tti|0.17|0.22|0.0***|0.21|0.22|0.0|0.22|0.23|0.0|
|eas ges eucaon eve s erary|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Ub|0.54|0.70|0.2***|0.70|0.53|-0.2***|0.53|0.56|0.0***|
|ran area|(0.02)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|
|Rf|0.18|0.12|-0.1***|0.12|0.21|0.1***|0.21|0.12|-0.1***|
|eugee area|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|(0.01)|(0.01)|(0.0)|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. The data are unweighted. Household heads' ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second survey round. The reference groups are household with no primary education and living in rural areas.

89
**<u>Table C.12. Descriptive statistics of estimation sample, Tunisia</u>**

|||**2005-2010**|||**2010-2015**|||**2015-2021**||
|---|---|---|---|---|---|---|---|---|---|
||**2005**|**2010**|**diff**|**2010**|**2015**|**diff**|**2015**|**2021**|**diff**|
|L f it ti|7.23|7.58|0.4***|7.55|7.98|0.4***|7.96|8.36|0.4***|
|og o per capa consumpon|(0.01)|(0.01)|(0.0)|(0.01)|(0.00)|(0.0)|(0.01)|(0.01)|(0.0)|
|Hd`|43.55|46.72|3.2***|44.24|47.23|3.0***|44.32|48.40|4.1***|
|eas age|(0.09)|(0.09)|(0.1)|(0.09)|(0.06)|(0.1)|(0.06)|(0.08)|(0.1)|
|Hd i fl|0.12|0.11|-0.0*|0.11|0.11|0.0|0.10|0.12|0.0***|
|ea s emae|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i i|0.04|0.03|-0.0***|0.03|0.46|0.4***|0.44|0.44|0.0|
|eas ges eucaon eve s prmary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i d|0.14|0.11|-0.0***|0.12|0.30|0.2***|0.32|0.32|0.0|
|eas ges eucaon eve s seconary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Hd' hiht dti ll i tti|0.08|0.09|0.0|0.09|0.11|0.0***|0.12|0.12|0.0|
|eas ges eucaon eve s erary|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|
|Ub|0.65|0.66|0.0|0.65|0.62|-0.0***|0.61|0.62|0.0**|
|ran area|(0.01)|(0.01)|(0.0)|(0.01)|(0.00)|(0.0)|(0.00)|(0.00)|(0.0)|

Note: ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels. Standard errors are in parentheses. The data are unweighted. Household heads' ages are restricted to between 25 and 55 for the first survey round and adjusted accordingly for the second survey round. The reference groups are household with no primary education and living in rural areas.

90
|**Table C.13. Estimated rho (**ρ**) from**<br>|**cross-sectional data**<br><br>||
|---|---|---|
|**Country**|**Period**<br>ρ|**Alternative**ρ|
||2012-2015<br>0.84|0.52|
|**Egypt, Arab Rep.**|2015-2017<br>0.89|0.46|
||2017-2020<br>0.79|0.61|
||2007-2009<br>0.54|0.56|
|**West Bank and Gaza**|2009-2011<br>0.62|0.66|
||2011-2017<br>0.34|0.59|
||2005-2010<br>0.57|0.67|
|**Tunisia**|2010-2015<br>0.73|0.65|
||2015-2021<br>0.89|0.61|
||2004-2008<br>0.77|0.57|
|**Mauritania**|2008-2014<br>0.63|0.56|
||2014-2019<br>0.70<br>|0.61<br>|
|**Iraq**<br><br>|2007-2012<br>0.68<br><br>|0.37<br>|
|**Jordan**<br><br>|2010-2013<br>0.63<br><br>|0.63<br>|
|**Note:** ρare estimated using Equati<br>education. Alternativeρ’s are estima|on (C5) for all countries with cohorts being defined by age i<br>ted using Equation (C6).|nteracted with household heads’|

91
# **Figure C.1. Probabilities of Female-Headed Households Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH wo/children FHH w/children Non-FHH<br>75<br>45<br>70<br>40<br>65<br>35<br>Percentage (%) Percentage (%)<br>60<br>30<br>60 55<br>55 50<br>50<br>45<br>Percentage (%) Percentage (%)<br>45<br>40<br>40 55<br>35<br>50<br>30<br>45<br>25<br>Percentage (%) Percentage (%)<br>20 40<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that moves out of poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps. ’s are estimated using Equation (C6). ρρ 92
**Figure C.2. Probabilities of Female-Headed Households Falling in Poverty in Second Year Conditional on Being Non-poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH wo/children FHH w/children Non-FHH<br>20 20<br>18 18<br>16 16<br>14 14<br>Percentage (%) 12 12 Percentage (%)<br>10 10<br>14 18<br>12 16<br>10 14<br>8 12<br>Percentage (%) Percentage (%)<br>6 10<br>45 16<br>40 14<br>35 12<br>30<br>10<br>Percentage (%) Percentage (%)<br>25 8<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that enters poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps. ’s are estimated using Equation (C6). ρρ 93
# **Appendix D: Further Analysis with Equivalence Scale**

Given our consistent observation of self-reported FHHs having an advantage in terms of greater mobility, the question arises as to whether this conclusion remains valid if we extend to selecting a measure of household members' welfare that goes beyond household expenditure per capita.

Within the context of poverty dynamics, we show two scenarios for self-reported FHHs as an example: one in which FHHs have a greater probability to escape poverty compared to non-FHHs (denoted by the orange-shaded region in Figure D.1), and another where FHHs are less likely to escape poverty than non-FHHs (represented by the blue-shaded area in Figure D.1). Importantly, the selection of specific scale parameters can significantly alter the conclusions drawn regarding poverty dynamics among FHHs.

In particular, when assessing consumption on a per capita basis (i.e., when β=1 and θ=1), selfreported FHHs consistently exhibit a higher probability of escaping poverty than non-FHHs and it holds true across all countries. Intriguingly, these findings align with those in Abanokova _et al._ (2022), which demonstrated a persistent upward mobility when income is evaluated on a per capita basis.

The conclusions regarding poverty dynamics shift when adopting OECD-recommended (modified) equivalence scales, which assign a value of 0.3 to each child aged 0-13 (indicated by the green dashed line) and/or the "square root scale" set at 0.5 (represented by the red dashed line). Under the "square root scale," self-reported FHHs become less likely to escape poverty than nonFHHs in Jordan, the West Bank and Gaza, and Tunisia, regardless of the child parameter value. The use of a lower scale parameter than the “square root scale” alters the conclusion in the Arab Republic of Egypt, but the sensitivity to the child parameter is also observed. Significant sensitivity to the child parameter is found in the West Bank and Gaza. When the child parameter is set to 0.4 or lower, there is a shift in the scenario from FHHs experiencing upward mobility to FHHs facing downward mobility. However, varying the parameters of economies of scale and child parameters from 0 to 1 does not alter the conclusions regarding poverty dynamics for Mauritania, Iraq and Jordan.

The absolute difference in the percentage of the population transitioning out of poverty between FHHs and non-FHHs is also influenced by the scale parameters. In the case of Mauritania, where self-reported FHHs are more likely to escape poverty than non-FHHs, fluctuations in scale parameters can result in significant changes in the percentage of self-reported FHHs escaping poverty. These variations can yield a discrepancy of up to 6.8 percentage points, depending on the scale parameters applied.

The overarching finding is that the parameter dictating the economies of scale and the private– public nature of household consumption contributes non-trivially to the poverty ranking between FHHs and non-FHHs across most countries and FHH definitions, while the child parameter having a comparatively smaller impact compared to household size. These results mirror our earlier observation in Abanokova _et al._ (2022) regarding the sensitivity of income dynamics to scale parameters.

94
**Figure D.1. Self-reported FHHs– non-FHHs Differences in Probabilities of Escaping Poverty in Second Year Conditional on Being Poor in First Year (percentage points), by Scale Parameters**

δ **Note:** Each figure shows 2-parameter equivalence scale that adjusts household consumption: (aij + αkij) where a– number of adults in the household, k – number of children in the household, α is “child parameter” that accounts for the needs of children aged 0-13 and δ is “size parameter” that measures the degree of economies of scale in household consumption. Both parameters are varying between 0 and 1. The blue zone indicates lower probabilities of escaping poverty among FHHs compared to non-FHHs. The orange zone indicates higher probabilities of escaping poverty among FHHs compared to non-FHHs. Each bar shows the difference in the percentage of the population that moves out of poverty among FHHs compared to non-FHHs in the second year (expressed in percentage points). We use OECD recommended (modified) equivalence scale that assigns a value of 0.3 to each child aged 0-13 (green dashed line) and “square root scale” that equals to 0.5 (red dashed line). The top right corner of the box (marked ×) illustrates the case when δ = 1 and α= 1, which represents per capita expenditure (“Per Capita”).

95