BRIEF 1
A profile of forcibly displaced populations and
their hosts 1
Leveraging Harmonized Data to Improve Welfare among Forcibly Displaced Populations and
their Hosts: A Technical Brief Series
World Bank Poverty and Equity Global Practice
June 2023
Context and Motivation
This is the first in a series of three technical briefs produced by the World Bank’s Poverty and Equity
Global Practice to share results of a multi-country data harmonization exercise concerning forcibly
displaced populations (FDPs) and host communities. The work aims to produce knowledge to inform policy
and operational decisions in countries affected by forced population displacement. The briefs rely on a data
harmonization exercise covering 10 countries across five regions that hosted FDPs in the period 2015 to 2020.
This, the first brief in our series, explains the context and goals of the data harmonization work; describes the
types and sources of data included and the methods used; then draws on the harmonized data to develop a
profile of FDPs and host communities across country and regional contexts, considering: basic demographic
variables; household composition and the timing of displacement; living conditions and assets; and access
to education and employment. Subsequent briefs in the series will look in detail at policy regimes and labor
market outcomes and at evidence and strategies to improve welfare.
Prior to the COVID-19 pandemic, extreme poverty was concentrated in fragile and conflict-affected states
(FCS). Moreover, as recent trends have shown, fragility and violence are becoming increasingly relevant to
welfare outside the poorest parts of the world – in the Middle East, for example, and now in Europe. Internal
and external displacement of populations is one of the primary manifestations of severe insecurity, with wide-
ranging implications for the welfare for those forcibly displaced and the communities hosting these populations.
The COVID-19 pandemic has laid bare how humanitarian systems are overstretched in low- and middle-
income countries (LMICs), where most refugees reside (Grandi and Van Trostenburg 2021; Vishwanath et al.
2020). With needs largely exceeding resources allocated toward protection of FDPs, inclusion policies allowing
refugees to contribute to national economies are emerging as a necessary component of the response to the
global refugee crisis, in the economic recovery ahead and in the longer term. However, the design of such policies
is constrained by a dramatic lack of evidence about how the influx of FDPs influences hosting economies, how
service delivery systems hold up to the strain, and how different policies perform in improving outcomes for
affected populations.
Forced displacement disproportionately affects developing countries, but evidence to guide response in these
settings is scarce
Forced displacement is a development challenge and disproportionately affects developing countries and
their populations. Three-fourths of all refugees, refugee-like, and stateless populations are hosted in only 19
countries, of which all but two are developing countries. Six developing countries alone host more than half of
the world’s internally displaced populations, and 97% of UNHCR’s host communities of concern are in a handful
of developing countries.2
The responsibility of hosting most displaced populations falls on neighboring countries, who also bear the
wider socio-economic consequences of conflict and violence in their neighborhood. Of the three possible
durable solutions for forced displacement (voluntary repatriation, third country resettlement and integration
into the hosting country), the de facto outcome for most displaced populations has been some degree of
local integration in hosting countries, often in response to a protracted displacement situation. This implies
a triple challenge for hosting countries: an immediate humanitarian response, which eventually transitions
to development and integration policies, ultimately including liberalization of refugee policy regimes in some
contexts.
2 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
However, the bulk of evidence on the impact of hosting displaced populations; on the efficacy of different
humanitarian, development, and integration policies; and on the costs and benefits of integration of FDPs
comes from the developed world.3 In large part, this is due to the lack of adequate, timely, and regular systems for
generating data to measure and monitor these features in LMICs. In addition, many developing countries that host
FDPs are simultaneously affected by the potentially destabilizing consequences of fragility and violence in neighboring
countries. Often, these host countries face waves of displacement with little ability and time to prepare. As a result,
there is a lack of evidence on the efficacy of integration policies, especially in complex and long-lasting refugee-hosting
contexts (Devictor and Do, 2017).
The lack of systematic data collection on FDPs also hinders the tracking of the Sustainable Development Goals
(SDGs) and policy responses. For instance, global poverty numbers typically exclude refugees and forcibly displaced
immigrants, as highlighted in “Fragility and Conflict: On the Front Lines of the Fight against Poverty” (Corral et al.,
2020), a companion report to the World Bank’s FCS strategy. This data gap is a potential source of bias in tracking
progress toward Sustainable Development Goal 1 (SDG1) globally. These data gaps also extend to other SDGs and limit
the monitoring of socio-economic conditions, human capital and assets, and livelihoods of the displaced and how
they interact with and influence the local hosting economy. This also impacts the ability of development partners
and humanitarian agencies to design policies that support long-term development responses in countries affected by
protracted population displacement.
This brief series is an important first step to provide a harmonized profile of FDPs vis a vis their hosts.
This brief builds on a data harmonization exercise to describe elements that are common across key displacement
contexts, as well as features which are distinct across each. The analysis relies on a harmonized dataset of
representative surveys of forcibly displaced populations and host communities from multiple refugee contexts and
hosting countries. It incorporates survey findings from 10 countries across five regions that hosted FDPs in the period
2015 to 2020. The goal of this exercise is to be able to establish a comparative profile of forced displacement in key
developing country settings.
The remainder of this brief is structured as follows. The next section touches on some aspects of the harmonization
process, describes the data included in the harmonized dataset, and provides details on the specific country contexts
and surveys from which these data are derived. The ensuing sections then draw on the harmonized dataset to provide a
comparative description of forcibly displaced populations along key axes: basic demographic variables; living conditions
and assets; and access to education and employment.
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 3
Data sources and methodological considerations
In this landscape of data scarcity, there have been recent efforts to close data and evidence gaps in a representative
way by including displaced populations in national household surveys (for instance, in Chad, Niger, and Uganda) or by
generating data on specific populations and displacement events (for example, Syrian refugees in the Mashreq or Rohingya
refugees in Cox’s Bazar, Bangladesh). Since 2015/16, some 12 countries have sought to systematically include refugees and
other forcibly displaced populations in key surveys.
Building on these country-level efforts, investing in creating comparable data through an ex-post harmonization is
an important step to help cross-country comparisons and support analytics that can inform policies at the global
level. Recognizing this need, the World Bank Poverty and Equity Team has engaged in a data harmonization effort across
10 countries, designed to support analytics that can highlight how country conditions, including diverse refugee policies
and programs, may shape outcomes. The results obtained can orient future policy. The data harmonization effort builds
on important seed investments, while recognizing that an adequate evidence base on forced displacement remains an
aspirational goal.
Countries and surveys included in the ex-post harmonization exercise
The datasets included in the harmonization effort cover key recent displacement contexts: the Venezuelan influx in
Latin America’s Andean states; the Syrian crisis in the Mashreq; the Rohingya displacement in Bangladesh; and forcible
displacement in Sub-Saharan Africa (Sahel and East Africa) (Figure 1). The harmonization exercise encompasses 10 different
surveys. These include nationally representative surveys with a separate representative stratum for displaced populations;
sub-national representative surveys covering displaced populations and their host communities; and surveys designed
specifically to provide insights on displacement contexts. Most of the surveys were collected between 2015 and 2020 (Table
1).
Figure 1. Displacement contexts and populations included in the data harmonization exercise
Venezuelan Syrian Rohingya Sub-Saharan Africa
Peru Lebanon Cox's Bazar, Bangladesh Chad
Ecuador Jordan Niger
Kurdistan - Iraq Ethiopia
Uganda
4 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Table 1. Surveys contributing data to the harmonized dataset
Country Year Survey name Displaced household’s Representativeness Number of households
countries of origin surveyed
Ecuador 2019 Encuesta a Personas en Movilidad Venezuela Venezuelans and hosts Venezuelan: 665
Humana y en Comunidades de
Acogida en Ecuador (EPEC) Host: 1,206
Total: 1,871
Peru 2018 Encuesta Dirigida a la Población Venezuela Venezuelan: 3,697
Venezolana que Reside en el Perú
(ENPOVE) Total: 3,697
Lebanon 2015 – Syrian Refugee and Host Syria Refugees and nationals Refugee: 1,079
2016 Community Survey (SRHCS)
Host: 1,786
Total: 2,865
Jordan 2015 – Syrian Refugee and Host Syria Refugees and hosts Refugee: 1,328
2016 Community Survey (SRHCS)
Host: 1,024
Total: 2,352
Iraq (Kurdistan 2015 – Syrian Refugee and Host Syria, Iraq Refugees, IDPs, and Refugee: 724
region) 2016 Community Survey (SRHCS) hosts in Kurdistan
IDP: 800
Host: 756**
Total: 2,280
Bangladesh 2019 – Cox’s Bazar Panel Survey (CBPS) Myanmar Rohingya and hosts in Rohingya: 2,493
(Cox’s Bazar) 2020 Cox’s Bazar district
Host: 2,527**
Total: 5,020
Chad 2018 Refugees and Host Communities Central African Republic, Refugees, hosts, and Refugee: 1,195
Household Survey in Chad (RHCH)* Sudan nationals
Host: 598
National: 7,493
Total: 9,286
Niger 2018 Enquête Harmonisée sur les Multiple Refugees and nationals Refugee: 1,113
Conditions de Vie des Ménages
(EHCVM) IDP: 471
Host: 364
National: 6,007
Total: 7,955
Ethiopia 2017 Skills Profile Survey (SPS) Eritrea, Somalia, South Refugees living in Refugee: 3,629
Sudan, Sudan camps
Host: 1,691
Total: 5,320
Uganda 2018 Uganda Refugee and Host DR of Congo, South Refugees and host Refugee: 879
Communities Household Survey Sudan, Somalia
(URHS) Host: 1,122
Total: 2,001
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 5
Countries considered in the harmonization exercise are highly illustrative of regions hosting populations displaced
by the most recent displacement crises as well as some key protracted crises. Countries included in the harmonized
database host a substantial part of displaced populations in each context (Figure 2). Figure 3 presents the cumulative
percentage of displaced populations leaving their countries of origin over time based on data from the harmonized
surveys. This provides a useful visualization of the different starting times for the diverse displacement events and contexts
considered, with the Venezuelan crisis and the Rohingya displacement in Bangladesh as the most recent events. Venezuela
is going through one of the deepest economic crises in history. Its Gross Domestic Product per capita halved between 2013
and 2018 and by then 9 out of 10 people lived in poverty.4 A combination of factors led to the mass exodus of Venezuelans
out of their country. Three countries in Latin America host 72 percent of displaced Venezuelans: Colombia (1.4 million),
Peru (1 million), and Ecuador (400 thousand). However, Venezuelan migrants represent only between 2 and 3 percent of the
local populations in those countries. In 2017, many Rohingya displaced arrived in the Cox’s Bazar district of Bangladesh,
fleeing violence from Myanmar. Within a period of four months, some 724,000 newly arrived persons joined other Rohingya
who had fled earlier waves of violence. By the end of 2018, nearly 2,000 campsites in Cox’s Bazar hosted around 912,000
Rohingya, more than doubling the population living in the Cox’s Bazar sub-districts of Teknaf and Ukhia.
Figure 2. Share of displaced people in different countries of asylum, by context
Venezuelan Syrian
Iraq 5%
Brazil 6%
Peru 19% Jordan 12 %
Chile 10%
Turkey 49%
Other 16% Lebanon 21%
Colombia 40%
Ecuador 9%
Other 13%
Rohingya Sub−Saharan Africa
Chad 6%
Uganda 17%
Other 10%
Cote d’Ivoire 9 %
Malaysia 14% DR Congo 7%
Sudan 14%
Ethiopia 12 %
Kenya 6%
Bangladesh 77% Other 26% Niger 3%
Source: UNHCR Refugee Data Finder.
Note: Includes refugees, asylum seekers, stateless persons, and other people in need of international protection, according to UNHCR definitions. Year
varies across regions to match the year of the surveys included in the harmonized data. Years of data used are: 2019 Venezuelan, 2015 Syrian, 2019
Rohingya, and 2018 Sub-Saharan Africa.
In Sub-Saharan Africa, the protracted crisis worsened in the years 2013 and 2015. With refugee populations of more than
one million each, Uganda and Ethiopia are currently the third and sixth largest refugee-hosting nations in the world. In
Sub-Saharan Africa, most refugees settle in camps located in areas bordering their country of origin, some of which also
suffer from domestic conflict. While some displacement crises in the region date from decades ago, the influx of displaced
people between 2014 and 2018 almost doubled the number of asylum seekers in Eastern Africa. By contrast, the number of
Syrian households in the three countries of origin covered in this exercise has remained stable since 2013. The Syrian crisis
has caused one of the largest episodes of forced displacement since World War II. In effect, more than half of Syria’s prewar
population has been forcibly displaced. As of 2016, five years from the start of the conflict, almost 5 million Syrians were
registered as refugees in other countries, a number that has increased to 5.4 million by 2023. A handful of Syria’s neighbors,
like Turkey, Iraq, Jordan, and Lebanon, continue hosting the bulk of Syrian refugees.
6 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Figure 3. Cumulative percentage of arriving displaced households
Venezuelan Syrian
100% 100%
75% 75%
50% 50%
25% 25%
2010 2014 2018 2010 2014 2018
Rohingya Sub−Saharan Africa
100% 100%
75% 75%
50% 50%
25% 25%
2010 2014 2018 2010 2014 2018
Note: Year of displacement not available for Chad. Percentages are computed using the year of displacement of household heads and their sampling
weights
Variables used in the harmonization
The selection of variables included in the harmonized dataset is oriented toward building the evidence needed
to support the pivot from the humanitarian to development response in refugee policy. As with any harmonization
effort, there is a substantial tradeoff between broadening the set of variables included and the ability to compare across
many settings. In this case, the variables selected for harmonization may be considered a minimum common denominator
which would be needed to be able to contrast different displacement contexts. The harmonized variables include key
demographics (e.g., age, gender), welfare indicators (e.g., housing and access to basic services), human capital indicators
(education), and economic variables (e.g., labor, sources of income, assets). Such indicators are important for the design
of policies oriented toward the protection and self-sufficiency of FDPs and to mitigate real and perceived risks to hosts.
This type of harmonization exercise conducted ex-post poses substantial challenges because of the diversity of
displacement contexts considered and the differing strategies for generating statistics from appropriate surveys.
The surveys included in this exercise differ in their objectives at the time they were implemented. For instance, while some
were designed to understand the implications on crises as they were ongoing (Syria, Venezuela, Rohingya), others were
designed to include displaced populations into national data collection efforts (such as in sub-Saharan Africa). Just as
there is significant heterogeneity within FCS, so there is also heterogeneity among forcibly displaced populations. As shown
before, we observe substantial variation in legal status and protection; pre-displacement socio-economic characteristics;
policy environments and other contextual conditions in the hosting country; and the potential for integration in the host
society and/or for return to FDPs’ home country.
While variables such as demographics and labor market participation have been harmonized across numerous
datasets globally, standard definitions are lacking for some categories related to forced displacement. For example,
the definition of “host” can range from designating only persons who live near a refugee camp to including any national of
a country hosting refugees. The notion of forcible displacement is also relative to the specific country context. In working
to harmonize the dataset, this complexity calls for particular attention to the way we categorize households and individuals
as hosts, refugees, asylum seekers, displaced immigrants, or internally displaced people (IDPs). Finally, certain survey
modules, such as those on consumption expenditure, are not harmonized. Beyond the harmonization of variables across
datasets, understanding patterns across displacement contexts requires some adaptation of sampling weights (Box 1).
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 7
Box 1. Technical considerations around generating representative data and sampling weights
Obtaining representative information on hosts and displaced populations in a single survey is a complex endeavor. The surveys used in
the harmonization exercise combined traditional and nontraditional sampling frames, telephone data, geospatial information, and listing
exercises to design representative surveys. All these efforts required introducing innovations to overcome lack of updated sampling frames
for host populations or inexistent sampling frames for displaced populations. The surveys also made context-specific decisions in terms of
how to stratify the sample to cover different groups and areas.5
One of the earliest efforts, the Syrian Refugee and Host Community Surveys (SRHCS), was implemented over 2015–2016 in Lebanon,
Jordan, and the Kurdistan region of Iraq. In all three settings, the main challenge to implementing a survey that would yield estimates
representative of the refugee and host community populations, was the lack of an updated or comprehensive sample frame, including for
hosting populations and especially for displaced populations. Defining a sampling strategy to yield representative samples of hosts and
displaced populations in this context involved two key innovations. The first was the creation of a sample frame feasible for household
listing operations from large geographical divisions where it did not exist. This was the case in Lebanon and among the two largest refugee
camps in Jordan. In Lebanon, cartographic divisions of the country were only available for large areas and had to be segmented and
sub-segmented based on satellite imagery and dwelling counts to yield geographic areas small enough for listing. These segmentations
attempted to divide the larger areas into equal population size subdivisions or segments, much the same way as enumeration areas are
generated. Similarly, for the two largest refugee camps in Jordan, Zaatari, and Azraq, satellite imagery was used to divide the camps
into mutually exhaustive and exclusive sampling units of roughly equal population size. The second innovation was the use of available
information from different sources on displaced population prevalence which were incorporated into the sample frames of host population
prevalence.6
In the case of Cox’s Bazar, Bangladesh, the survey was designed to be representative of post-2017 displaced Rohingya, hosts in high exposure
areas, defined as up to 3 hours walking time from Rohingya campsites; and hosts in low exposure areas in Cox’s Bazar. Two different data
collection exercises were carried out to assess the prevalence of Rohingya displaced outside the camps to inform the sampling strategy
for Rohingya displaced. Administrative data from humanitarian agencies were used to design the sampling frame within the camps. One
innovation was the use of drone imagery and digital maps to implement the listing within camps and host communities. Two different
open-source data sets were used to inform the design of the host strata and help generate the host enumeration areas. Government data
such as the 2011 population census and administrative shapefiles were also used. 7
In Uganda, the survey is representative of the refugee and host community population of Uganda at the national level. Moreover, it is
representative of the refugee and host population in the regions of West Nile and Southwest, and the city of Kampala. The host population
is defined as the native population in districts where refugee settlements are situated. The survey used two different sampling frames.
The first one, based on the list of Enumeration Areas (EAs) and the information of used to determine the samples for the host and refugee
populations of Kampala, and the host populations in West Nile and Southwest. The second one was a newly developed sampling frame
for the refugee population in the West Nile and Southwest regions. Primary sampling units were selected in a first stage using a Probability
Proportional to Size (PPS) sampling method. Between the first and second stages, household listing operations were carried out in the
selected enumeration areas. 8
In the case of Ecuador despite reliable and up-to-date sampling frame for the national census, the lack of information on the numbers of
Venezuelans displaced in Ecuador and their locations in the country posed challenges for the design and implementation of the EPEC. This
survey used Call Detail Records and External Detail Records between June 2018 and March 2019 provided by the main phone company
Telefónica de Ecuador. Telefónica de Ecuador analyzed their database to determine how many of their active mobile phones in each primary
sampling unit (PSU) were likely to belong to Venezuelans displaced abroad, based on the name of the account holder or the volume of
calls and messages to/from Venezuela. To estimate the total number of Venezuelans in each PSU, figures were adjusted using Telefónica’s
market shares (to estimate the total number of Venezuelan phones from all companies in each PSU) and the fraction of the population
using mobile phones. In the first sampling stage, were stratified into three categories depending on the Venezuelan migrant density.
Within each stratum, the sample was selected with probability proportional to the number of households reported by the 2010 Census.
In the second sampling stage, all households in each of the selected sectors were listed and stratified into three categories considering
nationality and demographic composition. Within each stratum, the sample was selected by systematic equal-probability sampling.9
While each survey includes sampling weights to aggregate to the host population and displaced population, these weights need to be
adjusted when the harmonized data are pooled across countries or regions. This is because whist a surveyed displaced population group
may account for a relatively large share of the displaced persons within a given country, they may correspond to just a small share of the
hosting country’s overall population (or vice versa). When pooling data across surveys for comparisons or regression purposes, the sample
survey weights are rescaled so that each country has equal weight, preserving the share of displaced populations in each country. When
aggregating across countries in a specific displacement context, we weight each displaced group equally to produce summary statistics
for the displacement context. For instance, each sample of Syrian refugees in Jordan, Lebanon, and Kurdistan-Iraq are weighted equally
when creating summary statistics for the Syrian refugee context in the Mashreq. An alternate approach could be to rescale the weights of
these three sample groups to aggregate up to their contribution to the total of all displaced persons in the Mashreq, total Syrian refugees
in the Mashreq, or the total of Syrian refugees in the world. Given that our harmonized dataset covers only 10 countries and by no means
provides comprehensive coverage of displaced populations, for simplicity, we choose equal weights for producing summary statistics by
displacement context.
8 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Group categories used in the harmonization
We classify households into five categories, namely: (1) refugees (including populations in refugee-like situations or
covered under UNHCR’s stateless mandate); (2) Venezuelan migrants; (3) internally displaced populations (IDPs); (4)
host population (defined as living close to displaced populations, not nationally representative); and (5) national sample
(nationally representative). Each survey covers different categories of households. The surveys from Chad, Niger, Lebanon,
Iraq (Kurdistan Region), and Bangladesh (Cox’s Bazar) include explicit strata of displaced populations, a separate stratum
for IDPs where relevant, and nationally or sub-nationally representative samples of national populations. Chad and Niger
also include a stratum of host communities. In Cox’s Bazar, the district population is further stratified into “high exposure”
(akin to host community) and “low exposure” (district populations living further away from the Rohingya camps). The
surveys from Ecuador, Ethiopia, Jordan, and Uganda do not include nationally representative samples, but include strata
for host and displaced populations. The survey from Peru included only Venezuelan migrants. Table 1 presents the number
of households by category in each country that are present in the dataset. Figure 4 displays the (unweighted) sample
composition in each of the 10 surveys by the percentage of households in each category.
Figure 4. Sample composition in the harmonized dataset by country and household category
100%
33 32
80% 44
50
56
64 62
76
60% 81
100 35
40%
68
56
50
5 44
20% 36 38
32 6 6
13 14
ECU PER LBN JOR IRQ BGD TCD NER ETH UGA
Refugee Venezuelan IDP Host National
migrant
Note. Unweighted percentages.
The displaced populations in the dataset can also be distinguished by their type of settlement in the country of
hosting. For instance, the sample of displaced populations in Chad, Bangladesh, Uganda, and Ethiopia live almost entirely
in camps, in contrast with migrants and displaced populations in Peru, Ecuador, and Lebanon (Figure 5). In Jordan and
Kurdistan-Iraq, displaced populations both within and outside camps are included in the sample.
The focus of these briefs is on refugees, stateless people, and Venezuelan migrants, and excludes Internally Displaced
populations. We consider refugees and Venezuelan migrants as displaced households, and host and national population
groups as non-displaced. For an easier exposition, in the analysis we restrict attention to refugees, stateless people, and
Venezuelan migrants. In other words, we do not to include IDPs. Summary statistics are computed at the regional (context)
level and by displacement status.10 The annex at the end of this document presents summary statistics for all variables
referred throughout the text, for both countries and regions, by displacement status.11
The next section presents a comparative profile of FDPs and their hosts across the varied displacement contexts reflected
in the dataset. The data allow us to investigate three key dimensions: basic demographic variables; living conditions and
assets; and access to education and employment.
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 9
Figure 5. Percentage of displaced households in the dataset living in camps
100 100 100
100% 97
80%
60
60%
52
40% 35
20%
0 0 0
ECU PER LBN JOR IRQ BGD TCD ETH UGA
Displaced from abroad Internally displaced
Note: Data for Niger are missing.
Demographics
The demographic characteristics of displaced populations reflect the type of households and individuals who
were forced to leave their country of origin and how they might differ from the types of households in the hosting
country. In this section, we offer some insights into forced migration patterns in each context by comparing the age and
gender of individuals and the household composition across displaced and non-displaced populations. Similarly, we look
at the timing of arrival to the host country of different household members. In making those comparisons, we assume
that demographic patterns are broadly similar across countries in the same region (e.g., Uganda, a host country, and
South Sudan, an origin country). Therefore, within-region differences between refugees or Venezuelan migrants and host
populations suggest that specific types of individuals or households are more likely to arrive in neighboring countries
because of the subjacent conditions in their country of origin and their socioeconomic conditions.
In three of the four contexts considered, the presence of children is substantially higher among refugees. The
age profile of displaced and non-displaced populations shows that only in one region, Sub-Saharan Africa, do the two
population groups present a similar age distribution (Figure 6). Among the age differences between displaced and non-
displaced populations by region, we note the relatively higher proportion of children (0-14 years old) among displaced
households relative to non-displaced households in the same region. Given this demographic profile of the displaced
populations, there is a critical need to ensure access to education for the large influx of children to ensure continuity to
schooling at the outset and to avoid a permanent negative impact on the achievements of children in the long term.
Figure 6. Population pyramids by displacement status and gender
Latin America Middle East
60+ Female Male 60+ Female Male
45−59 45−59
30−44 30−44
15−29 15−29
0−14 0−14
40% 20% 0% 20% 40% 40% 20% 0% 20% 40%
Cox’s Bazar Sub−Saharan Africa
60+ Female Male 60+ Female Male
45−59 45−59
30−44 30−44
15−29 15−29
0−14 0−14
40% 20% 0% 20% 40% 40% 20% 0% 20% 40%
Displaced Non−displaced
Note: Peru was omitted due to missing data for the local population.
10 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Forcibly displaced women and children tend to precede the family when leaving their home country. In all regions
but Latin America, the percentage of female household heads is larger among displaced than non-displaced populations.
While this difference is minor in the Middle East, the share of female household heads among refugees is twice as wide in
Sub-Saharan Africa and 60% higher in Cox’s Bazar relative to their host communities and the national population. Cultural
differences or intra-family dynamics might not explain these differences. Instead, while women represent roughly 50% of
the displaced population in all contexts analyzed, females constitute 57% and 63% among individuals of ages 30 to 44 in
Cox’s Bazar and Sub-Saharan Africa, respectively. Moreover, we observe that, across contexts, husbands are not present
in more than 8 out of 10 displaced households with a female head. By contrast, the percentage of displaced households
where wives are absent is relevant only in Latin America. At the same time, women are the ones who typically take children
with them to their destination. We find a substantial fraction of children migrating with their mothers but not their fathers,
ranging from 17% in the Middle East to 47% in Sub-Saharan Africa (Figure 7). These two facts could be explained by a
broader trend in which women and children tend to precede the family when leaving the home country, especially when
the risk to life is a fundamental determinant of fleeing.
The demographic profile of displaced populations in Latin America substantially differs from other displaced
populations, reflecting the economic nature of the Venezuelan crisis. In contrast with the other three regions, the most
relevant age disparity between Venezuelans in Latin America and their hosts is the relatively larger presence of youth and
young adults among the former. About 66 percent of Venezuelan migrants in Peru and Ecuador are individuals between 15
and 44 years of age, by far the highest share across displacement contexts. This figure is more than 10 percentage points
higher for Venezuelans in Ecuador than is for Ecuadorians. Moreover, among Venezuelan between the ages of 15 and 59
who migrated between 2015 and 2017, the share of men was 56%, suggesting that men may have been the first to arrive in
many families. For instance, since 2018, following a large influx of Venezuelan female migrants, the population shares for
these age groups are balanced across genders. Still, by 2019, the wife had yet not migrated into the hosting country for 2 in
every 10 Venezuelan displaced households. These demographic patterns are explained by the fact that, in the early years
of the crisis, most Venezuelans left their country because of economic hardships, and a third of the men migrated before
their families to find a job in neighboring countries (World Bank, 2020).
Figure 7. Share of children migrating with a single parent, both parents, or separately from parents
Latin America 38 51 9
Middle East 17 79
Sub−Saharan Africa 47 3 48
25% 50% 75% 100%
With Female Parent With Male Parent With Both Parents Separetely From Parents
Note: Year of displacement not available for Bangladesh or Chad
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 11
Living conditions and assets
Displaced populations fare substantially worse than hosts, on average, and inequalities within a country are
exacerbated for refugees living in camps.
With respect to housing conditions and access to basic services, displaced populations generally lag behind with
respect to host communities. Figure 8 contrasts the living conditions of displaced and non-displaced households along
four dimensions: formal housing (i.e., not living in a tent, caravan, worksite, or abandoned building); access to electricity
in dwelling; improved sanitation facilities (toilet or latrine in the house connected to sewage or septic tank); and improved
water source (piped, bottled, tanker trucks, or community tanks). For each dot in these plots, the vertical axis represents
the percentage of displaced households with access to a given amenity. The horizontal axis expresses the same quantity
for host and national households. The dashed diagonal lines indicate an equal distance to the vertical and horizontal axes,
or in other words, parity in access between the hosts and the displaced. Dots closer to the line represent countries in which
the two populations experience similar conditions. The plots further distinguish countries where displaced households are
settled in camps from those where they live outside camps. Because of that, two sets of points appear for Iraq and Jordan,
where both settings exist.
Figure 8. Housing and access to basic services
Formal dwelling Electricity
100% JOR IRQ 100% ECU LBN
JOR IRQ
ECU
LBN
IRQ
TCD
50% UGA 50% UGA
BGD
ETH ETH
NER
Displaced households
TCD
0% JOR 0% NER
0% 50% 100% 0% 50% 100%
Improved sanitation Improved water source
ECU JOR UGA ECU JOR
JOR
100% 100% NER LBN IRQ
IRQ LBN ETH
TCD
IRQ
JOR
50% 50%
UGA
TCD ETH
0% NER BGD 0% BGD
0% 50% 100% 0% 50% 100%
Non−displaced households
Living in camp Living outside camp
Notes: Peru was omitted due to missing data for the local population. Data on formal house is missing for Bangladesh. Data on camp situation is missing for
Niger.
Displaced households experience poorer access to basic services, especially those living in camps. Broadly speaking,
host populations are better off than the group of refugees and Venezuelan migrants in every aspect, as indicated by the
large number of dots in the bottom right portion of the plots. The only exception in that instance is access to improved
water sources in Sub-Saharan Africa, where the fact that most displaced households live in formal camps may play a role. In
Latin America and the Middle East, where public service coverage reaches most people in our sample, the living conditions
of host households and displaced people living outside of camps are similar and better than those of all populations in
the other two regions. On the other hand, 40 percent of Syrian refugees living in camps in Jordan lack access to improved
sanitation, and nearly all of them live in improvised dwellings, in sharp contrast with the living conditions of refugees living
outside camps in the same country. Those differences are also noticeable in Iraqi Kurdistan, although to a lesser extent.
Displaced households in the African countries more often live in improvised dwellings. In addition, these households suffer
from precarious access to basic services, although this fact is explained for the most part by the low coverage of such
services in the host countries. When comparing displaced and non-displaced populations in the same region, Rohingya
people present the most notable disadvantages for all available variables.
12 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
In addition, refugees typically arrive in the host country with very few assets, as forcibly displaced persons flee
without much time to prepare, and fixed assets (land, home, and durables) in their home country are usually lost.
Asset ownership in the host country for displaced households is low. Except for Latin America, where asset ownership
data was not collected, the most frequently owned asset among refugees across regions is cell phones. Ownership of this
item ranges from 34% of displaced households in Ethiopia to 97% in Jordan. In the Middle East, refugees in the dataset
own items such as refrigerators, cookstoves, televisions, and radio in proportions similar to those of the local population.
Conversely, ownership rates among refugees in Bangladesh and Sub-Saharan Africa are close to zero for those same items.
In the case of Sub-Saharan Africa, we additionally find that hosts are as deprived as the displaced populations, especially
in Chad and Niger.
The overall living conditions and future prospects of displaced populations, however, depend on factors other than
access to basic services and asset ownership: among others, access to education and jobs. Although the measures
presented above are useful, they miss important dimensions that are key for understanding and implementing development
policies in displacement contexts. These include displaced populations’ opportunity to attend school, participate in the
labor market, and, overall, make independent choices to achieve their desired outcomes. While a full analysis of these
dimensions is beyond the scope of this brief, in what follows we discuss the education and employment outcomes of
displaced individuals in their respective host countries.
Education and employment
In terms of school attendance, displaced children lag behind host and national populations by several percentage
points in 3 of the 4 regions. Figure 9 and 10 present school attendance rates for children across settings. In Latin America,
the Middle East, and Cox’s Bazar school attendance for displaced children is significantly below their hosts. The fact that
school attendance is higher for displaced children in Sub-Saharan Africa is explained by the existence of international
assistance programs providing education in camps. For instance, 7 in every 10 refugee children between 6 and 18 years of
age living in camps in Ethiopia attend schools run by NGOs, which contrasts with children in host community households
who overwhelmingly attend government schools (World Bank, 2018). Schooling is particularly lower for displaced children
between 12 and 18 years of age when compared to national and host children. In addition, a pronounced educational
gender gap exists for displaced teenagers in all regions but the Middle East, which is not observed among locals nor children
in primary school.
Displaced adults are generally less educated than hosts; Venezuelan migrants are a notable exception. Figure 11
compares the distribution of education across displaced and non-displaced working-age populations (ages 20 to 60).
Adults who eventually sought asylum in three of the four host regions generally appear to be less educated compared to
the local population. The exception is Latin America, where the population of Venezuelan migrants is highly educated:
virtually all attained at least secondary education and half of the Venezuelan migrants had some type of schooling beyond
secondary education.
These educational gaps may be the result of differential migration patterns across the socio-economic status of
displaced people in their home country if, for example, only wealthier (more educated) displaced individuals can afford
the journey to developed countries. For instance, the educational level of Syrian refugees in the Middle East differs from
that of the Syrian asylum seekers in Europe: 21% of the Syrian asylum seekers who arrived in Germany in 2013–14 reported
having tertiary education, which is close to the average of the host population (Aiyar et al., 2016).
Despite their origin, these disparities may hinder the labor market integration of refugees in host countries, as
educational and training skills are critical determinants of employment rates and wages. Simultaneously, refugees
and Venezuelan migrants face institutional and legal obstacles to fully participate in the labor market, regardless of their
education. In Ecuador, for example, 60% of employed Venezuelans work in the informal sector, 72% have temporary jobs,
and they often do low-skilled labor (World Bank, 2020).
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 13
Figure 9. Children’s school attendance by gender (ages 6-12)
100%
97 100
95 95
92 90
80% 84 85
78
73 72 75
69 71
60%
67
64
40%
20%
F M F M F M F M
Latin America Middle East Coxʼs Bazar Sub−Saharan Africa
Displaced Non−displaced
Note: Peru was omitted due to missing data for the local population.
Figure 10. Children’s school attendance by gender (ages 13-18)
100%
80% 83 84 85
80
72 73
60% 63 65
59
53 54
40%
37
33 31 30
20%
F M F M F M F M
Latin America Middle East Coxs Bazar Sub−Saharan Africa
Displaced Non−displaced
Note: Peru was omitted due to missing data for the local population.
Figure 11. Adult educational attainment
100% 5 6 5
9
22 17 17
11 17
80% 45
29
36 14
17
60% 43
49
37 20
40% 79
67
50 18 61
20% 25 39
29
22
5 5
Displaced Not Displaced Not Displaced Not Displaced Not
Latin America Middle East Coxʼs Bazar Sub−Saharan Africa
Canʼt read / Some Some Higher than
No education primary secondary secondary
Note: Peru was omitted due to missing data for the local population
14 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Displaced populations face challenges in accessing employment
Employment rates for male adults (18 years or older) are more or less uniform for locals and are substantially higher
than those for refugees in almost every region. Larger differences with the local population are observed in countries
with camp policies for refugees, such as Bangladesh, Ethiopia, and Uganda. Such differences are also evident when
refugees in camps and outside camps are compared; among refugees in Iraq and Jordan, the employment rate is roughly
20 percentage points lower for those living in camps. These data, however, do not distinguish between paid jobs and those
performed in camps for an in-kind or a low monetary remuneration, possibly explaining the high employment rate for
refugees living in camps in Chad in when compared to other countries in Sub-Saharan Africa.
Women’s employment shows marked regional contrasts but gaps between displaced and non-displaced individuals
are more pronounced in the case of women. With the exception of Chad and Ecuador, women’s employment rates are
substantially lower among refugees. The disparities between displaced and non-displaced woman are markedly larger
than those between men. The lowest employment rates for women, whether displaced or not, correspond to the Middle
Eastern countries, but the largest difference is observed in Cox’s Bazar. Countries where woman refugees live in camps do
not exhibit larger employment gaps, except for Ethiopia. Regional differences in women’s employment are pronounced.
It is worth noting that the fraction of displaced women out of the labor force is as high as 90% in Bangladesh and 50% in
Sub-Saharan Africa, while it amounts to only 25% in the Middle East and 2% in Latin America.
Figure 12. Employment rate for male adults
100%
93
81 80
80%
72
69
64
60% 56
42
40%
20%
Latin America Middle East Coxʼs Bazar Sub−Saharan Africa
Displaced Non−displaced
Note: Peru was omitted due to missing data for the local population.
Figure 13. Employment rate for female adults
100%
80% 77
60
60% 55
40% 35
20
20% 14
7 7
Latin America Middle East Coxʼs Bazar Sub−Saharan Africa
Displaced Non−displaced
Note: Peru was omitted due to missing data for the local population
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 15
Conclusions
This is the first in a series of three technical briefs building on a multi-country data harmonization exercise concerning
forcibly displaced populations and host communities. The briefs are designed with different objectives in mind. This
brief is designed to provide a quick overview of the harmonized dataset and explains the sources of data and the methods
and principles used in the data harmonization exercise. In addition, it draws on the harmonized data to offer a profile of
FDPs and host communities across regional contexts. The brief presents a series of descriptive statistics on demographic
characteristics, access to basic services and asset ownership, schooling and educational attainments, and labor market
outcomes. In general, these findings confirm descriptive pattens on the socio-economic characteristics of displaced and
hosting populations from country level analysis. The second brief demonstrates how such harmonized data can be used to
draw inferences that are of broad relevance, and can be combined with other multi-country datasets, while the third brief
provides more detailed analysis and comparisons of distinct displacement contexts, and the implications for measuring
wellbeing among the displaced. This series of briefs are an important first step to provide a broader picture of FDPs and
their hosts with the aim of producing policy-relevant knowledge, motivate future analyses that rely on this harmonized
data, and encourage more systematic data collection in fragile and displacement settings.
The harmonization effort incorporates representative survey data from 10 countries across five regions that hosted
FDPs in the period 2015 to 2020. The construction of the ex-post harmonized dataset posed substantial technical
challenges given the diversity of displacement contexts considered, the differing strategies for generating statistics across
surveys, the lack of standard definitions for some categories related to forced displacement, among others. As with any
harmonization effort, decisions on which variables to harmonize and how to make them comparable had to be made.
In addition to expanding the set of surveys included in the harmonization, the core harmonized dataset could provide a
template for collecting consistent data in future surveys. The contexts included in the database cover some of the most
recent displacement crises and some protracted ones that have intensified in the last decade: the Venezuelan influx in
Latin America; the Syrian crisis in the Mashreq; the Rohingya displacement in Bangladesh; and forcible displacement in
Sub-Saharan Africa.
We find that the demographic characteristics of displaced populations differ in several aspects from those of their
hosts. Displaced households from Syria, Myanmar, and Sub-Saharan Africa are composed of a larger number of children
under 14 years of age. For these three contexts, women and children preceded male adults in arriving to the host country,
and for almost half of cases, husbands of household heads were not present with the household at the time of the survey.
In contrast, the Venezuelan migrant population is characterized by a large share of youth and young adults who arrived in
Ecuador and Peru seeking jobs and were later joined by their families.
In terms of housing conditions and access to basic services, displaced populations generally lag with respect to host
communities, except for Venezuelan migrants in Ecuador, where no substantial differences exist vis-à-vis Ecuadorians.
In the Middle East, the gaps in housing and access to basic services depends on whether they are in camps or outside;
while displaced households living outside camps in the Middle Eastern countries experience living conditions similar to
those of the local population, refugees living in camps in Jordan and Iraq are generally worse off, with up to 40 percent of
them either living in poor quality dwellings or without adequate sanitation facilities. Countries where the bulk of FDPs live
in camps (in Sub-Saharan Africa and Bangladesh) present the biggest gaps in terms of access to services and assets. This
is especially marked in Bangladesh, where virtually none of the Rohingya households have access to improved sanitation
or water and less than half of them have access to electricity. Lastly, the ability to accumulate assets in the host country
appears to be very limited in Bangladesh and Sub-Saharan Africa, where the main asset own by refuges is a cell phone.
Regarding education, there exist substantial gaps in schooling rates for displaced children compared to their
hosts in all regions but Sub-Saharan Africa. Attendance gaps in Ecuador contrasts with the widespread access to other
public services. One important reason could be limited capacity in nearly schools, as reported by half of the Venezuelan
respondents with children in the survey. Education for refugee children in Sub-Saharan Africa is mostly administered by
NGOs and humanitarian agencies, which may explain the higher rates of schooling observed among this population group
compared to their hosts. Moreover, across the board displaced adults are significantly less educated than their hosts. The
exception is Latin America, where Venezuelan migrants are a relatively highly educated group.
Employment rates among male and female adults are substantially lower for displaced individuals in almost
every region. Employment gaps are especially pronounced in for displaced men living in camps. As for women, a large
heterogeneity exists across regions, but employment gaps for displaced females are more pronounced than those observed
for men.
16 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Against this backdrop and considering the complex nature of designing and implementing development policies
in displacement contexts, the accompanying two briefs of this series explore in detail some of the aspects only
briefly highlighted here. Displaced individuals often struggle to integrate into host countries, and to find employment.
Accordingly, the second brief uses data from a recently created legal database, the Developing World Refugee and Asylum
Policy (DWRAP), to investigate whether legal restrictions affect education and labor market outcomes. Finally, the third brief
examines the appropriateness of using standard economic indicators to monitor the wellbeing of displaced populations.
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 17
Acknowledgments
This brief series and the associated harmonized database were prepared by a team led by Tara Vishwanath, Nandini
Krishnan, and Maria Eugenia Genoni. The core team for the briefs included Jacob Hennig, Alexander Irwin, and Alejandro
Lopez Aguilar. The harmonized dataset core team included Joseph Andrew Green, Arthur Alik Lagrange, and Alejandro
Lopez Aguilar. The work has been carried out under the general direction of Luis Felipe Lopez-Calva and Benu Bidani.
The team gratefully acknowledges advice from the peer reviewers Kevin Carey, Sergio Olivieri, Silvia Redaelli, and Sharad
Tandon. In addition, the team gratefully acknowledges help from the many people who have led the country-specific
survey efforts, as well as from those who have supported the preparation of these briefs including Jessica Adler and Karem
Edwards.
Bibliography / End Notes
1. Front page photo by World Bank / Tanvir Murad Topu. Last page photo © World Bank.
2. In this series of briefs, the term “host community” refers to a community that hosts large populations of refugees or
internally displaced persons, whether in camps, integrated into households, or independently.
3. For instance, Brell, et al 2020.
4. Based on Venezuela’s national poverty line with data from Encuesta Nacional de Condiciones de Vida 2018 (Universidad
Católica Andrés Bello).
5. Details about the sampling strategies for each survey can be in the following references. Bangladesh (See Endara et al.,
2022.), Chad (Nguyen, Savadogo, and Tanaka, 2021), Ecuador (World Bank, 2020), Ethiopia (World Bank, 2020), Jordan,
Lebanon, and Kurdistan - Iraq (Krishnan et al, n.d.), Niger (Niger’s National Institute of statistics, 2021), Uganda (World
Bank, 2019).
6. Aguilera et al (2020).
7. See Endara et al., 2022.
8. World Bank. 2019. Informing the Refugee Policy Response in Uganda. Results from the Uganda Refugee and Host
Communities 2018 Household Survey.
9. See Munoz, Munoz, and Olivieri (2020).
10. Since the ENPOVE survey does not cover nationals or hosts, Peru is omitted from all comparisons at the region level
between Venezuelan migrants and the local population.
11. All three reports in this series use the most recent version of the harmonized data set as of February 2023.
18 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
References
• Aguilera, Ana, Nandini Krishnan, Juan Muñoz, Flavio Russo Riva, Dhiraj Sharma, and Tara Vishwanath, 2020. Sampling
for Representative Surveys of Displaced Populations. In: Hoogeveen, J., Pape, U. (eds) Data Collection in Fragile States.
Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-25120-8_8
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Huidan Lin, Linda Kaltani, Sebastian Sosa, Antonio Spilimbergo, and Petia Topalova, 2016. Fragility and Conflict: On
the Front Lines of the Fight against Poverty. Staff Discussion Notes No. 2016/002, International Monetary Fund
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Income Countries.” Journal of Economic Perspectives, 34 (1): 94-121.DOI: 10.1257/jep.34.1.94
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Venezolana-en-Ecuador.pdf
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 19
Annex
Table A.1. Summary statistics at the household level, by country and displacement status
Country Ecuador Peru Lebanon Jordan Iraq
Displaced Yes No Yes No Yes No Yes No Yes No
Observations 665 1,206 3,697 1,079 1,786 1,328 1,024 724 756
Living in camps 0.0% 0.0% 0.0% 0.0% 0.0% 52.0% 1.4% 60.2% 0.1%
Female household head 22.2% 33.2% 30.1% 9.7% 12.8% 17.2% 12.8% 9.7% 6.7%
Housing and services
formal dwelling 86.2% 88.0% 100.0% 79.8% 99.8% 48.8% 98.5% 78.9% 99.9%
electricity in dwelling 99.9% 99.9% 99.7% 99.8% 100.0% 98.5% 99.0% 98.9% 100.0%
improved sanitation 99.6% 89.6% 100.0% 94.3% 99.8% 78.9% 97.1% 86.2% 98.4%
improved water source 99.9% 97.2% 100.0% 98.1% 97.2% 99.1% 99.0% 100.0% 100.0%
Asset ownership
motor vehicle 27.3% 80.0% 2.6% 49.6% 23.9% 65.3%
refrigerator 12.8% 74.6% 99.7% 60.0% 98.0% 88.4% 92.3%
cookstove 98.0% 99.4% 93.7% 97.5% 97.1% 99.8%
television 55.4% 93.3% 99.9% 82.5% 98.7% 96.7% 99.9%
radio 10.5% 25.9% 6.1% 13.0% 12.0% 19.6%
cell phone 90.4% 89.4% 93.7% 97.6% 98.2% 97.5% 99.2%
20 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Table A.1. Summary statistics at the household level, by country and displacement status
Country Bangladesh Chad Niger Ethiopia Uganda
Displaced Yes No Yes No Yes No Yes No Yes No
Observations 2,493 2,527 1,195 8,091 1,113 6,371 3,629 1,691 879 1,122
Living in camps 100.0% 0.0% 100.0% 0.6% 100.0% 0.0% 96.9% 95.1%
Female household head 24.5% 15.0% 52.0% 24.2% 29.4% 17.3% 66.2% 34.6% 53.0% 29.4%
Housing and services
formal dwelling 50.8% 53.2% 11.5% 82.0% 22.8% 73.1% 46.2% 64.5%
electricity in dwelling 40.3% 83.3% 0.5% 6.4% 1.0% 15.8% 19.0% 57.1% 49.3% 46.7%
improved sanitation 2.1% 43.1% 6.7% 3.2% 0.5% 5.2% 11.3% 12.4% 23.0% 13.0%
improved water source 0.7% 50.4% 88.7% 65.2% 96.9% 62.8% 97.4% 92.8% 97.0% 66.7%
Asset ownership
motor vehicle 0.0% 9.6% 2.0% 10.0% 0.1% 12.3% 0.0% 0.6% 2.0% 8.7%
refrigerator 0.0% 26.9% 0.1% 1.0% 0.1% 2.5% 0.1% 10.0% 1.3% 2.2%
cookstove 73.1% 48.5% 2.2% 0.5% 7.1% 4.7% 1.0% 4.8% 0.8% 0.5%
television 0.0% 27.3% 0.3% 5.0% 0.5% 10.4% 1.5% 24.5% 2.9% 9.3%
radio 2.4% 20.0% 3.2% 17.4% 5.3% 14.3% 10.7% 36.2%
cell phone 82.1% 96.1% 48.1% 58.6% 61.1% 68.4% 34.0% 64.8% 51.2% 67.0%
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 21
Table A.2.Summary statistics at the individual level, by country and displacement status
Country Ecuador Peru Lebanon Jordan Iraq
Displaced Yes No Yes No Yes No Yes No Yes No
Age distribution female
0-14 23.5% 28.1% 17.3% 42.8% 19.9% 46.0% 35.1% 41.3% 35.4%
15-29 33.9% 27.0% 44.0% 29.4% 31.8% 25.8% 27.2% 27.3% 28.6%
30-44 27.5% 19.2% 26.5% 17.6% 21.5% 17.6% 19.1% 20.8% 19.5%
45-59 11.6% 15.3% 9.6% 6.6% 16.9% 7.4% 11.6% 7.8% 10.6%
60+ 3.6% 10.4% 2.6% 3.6% 9.9% 3.2% 7.0% 2.8% 5.9%
Age distribution male
0-14 30.1% 30.0% 17.4% 42.9% 22.7% 50.4% 36.3% 42.4% 38.9%
15-29 30.6% 28.2% 42.7% 25.7% 29.3% 24.6% 29.3% 28.0% 26.0%
30-44 25.9% 19.7% 31.9% 19.9% 19.1% 15.9% 17.2% 19.8% 19.3%
45-59 8.4% 12.8% 6.5% 8.6% 18.7% 6.5% 11.5% 7.4% 9.6%
60+ 5.0% 9.3% 1.5% 2.8% 10.2% 2.6% 5.6% 2.4% 6.1%
Children 6-12 in school
girls 84.4% 97.4% 48.1% 58.4% 98.5% 80.8% 93.9% 74.9% 92.1%
boys 68.6% 99.9% 42.6% 62.3% 97.2% 78.2% 92.3% 76.9% 87.5%
Educational level female 20-60
no education 0.7% 4.5% 0.1% 25.6% 7.3% 28.3% 12.6% 45.2% 60.2%
some primary 4.8% 24.5% 0.0% 32.1% 13.3% 52.4% 16.8% 24.2% 12.4%
some secondary 39.7% 50.5% 27.0% 40.7% 64.2% 15.4% 46.0% 19.9% 15.2%
higher than secondary 54.8% 20.5% 72.9% 1.6% 15.3% 3.9% 24.6% 10.7% 12.3%
Educational level male 20-60
no education 0.8% 4.8% 0.2% 20.1% 5.0% 20.4% 7.5% 32.6% 37.9%
some primary 4.4% 25.6% 0.0% 28.6% 24.5% 55.7% 19.1% 31.7% 19.6%
some secondary 61.1% 46.8% 36.6% 48.9% 55.5% 18.4% 51.2% 29.5% 27.6%
higher than secondary 33.7% 22.8% 63.2% 2.5% 14.9% 5.5% 22.2% 6.2% 15.0%
Employment rate (18 and older)
female 76.8% 60.3% 90.2% 8.7% 18.0% 4.8% 11.8% 7.1% 11.6%
male 92.9% 80.5% 96.8% 78.2% 76.9% 41.3% 59.1% 69.4% 70.0%
22 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Table A.2.Summary statistics at the individual level, by country and displacement status
Country Bangladesh Chad Niger Ethiopia Uganda
Displaced Yes No Yes No Yes No Yes No Yes No
Age distribution female
0-14 43.7% 32.2% 45.7% 50.8% 51.5% 51.7% 55.4% 47.9% 52.8% 47.5%
15-29 32.4% 35.5% 25.0% 24.6% 23.0% 23.3% 22.8% 26.5% 25.8% 26.9%
30-44 11.3% 16.3% 16.3% 14.4% 17.3% 14.5% 15.8% 15.0% 13.3% 13.5%
45-59 8.8% 10.2% 8.4% 6.4% 5.3% 7.2% 3.9% 6.4% 4.5% 6.9%
60+ 3.7% 5.9% 4.6% 3.7% 2.9% 3.4% 2.1% 4.2% 3.7% 5.2%
Age distribution male
0-14 48.5% 32.6% 54.4% 55.8% 59.1% 56.2% 62.0% 51.5% 61.5% 49.9%
15-29 29.7% 33.9% 23.8% 19.0% 14.5% 17.9% 22.8% 20.6% 23.1% 27.4%
30-44 8.9% 15.5% 9.2% 13.1% 13.0% 12.4% 9.0% 15.5% 9.1% 11.5%
45-59 7.6% 9.0% 7.7% 7.3% 8.6% 8.0% 4.1% 7.0% 3.1% 6.9%
60+ 5.3% 9.0% 4.9% 4.8% 4.8% 5.5% 2.1% 5.4% 3.2% 4.2%
Children 6-12 in school
girls 77.6% 95.3% 79.0% 44.7% 38.7% 46.7% 78.8% 72.1% 93.7% 94.1%
boys 84.7% 89.8% 83.0% 50.2% 37.1% 51.8% 83.9% 74.3% 93.8% 93.0%
Educational level female 20-60
no education 90.3% 45.2% 76.4% 83.1% 98.6% 87.3% 73.6% 64.2% 57.8% 41.7%
some primary 7.5% 15.6% 9.5% 5.7% 0.9% 4.7% 15.1% 14.3% 27.0% 34.8%
some secondary 2.1% 36.6% 13.6% 9.7% 0.5% 7.0% 10.8% 16.8% 13.2% 16.9%
higher than secondary 0.1% 2.6% 0.5% 1.5% 0.0% 1.0% 0.6% 4.7% 1.9% 6.6%
Educational level male 20-60
no education 66.8% 32.2% 56.8% 63.4% 91.0% 75.7% 37.4% 40.7% 21.6% 20.5%
some primary 15.3% 23.8% 12.3% 9.3% 5.8% 9.3% 15.0% 18.3% 32.8% 43.9%
some secondary 17.2% 34.7% 28.3% 21.7% 3.0% 12.4% 41.9% 29.8% 38.3% 26.9%
higher than secondary 0.7% 9.3% 2.6% 5.7% 0.3% 2.7% 5.7% 11.2% 7.3% 8.7%
Employment rate (18 and older)
female 7.1% 20.3% 51.5% 51.9% 34.7% 47.9% 18.7% 49.6% 34.0% 71.4%
male 41.6% 71.8% 66.2% 77.8% 81.8% 81.3% 30.0% 78.7% 43.4% 80.2%
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 23
Table A3. Summary statistics at the household level, by region and displacement status
Region Latin America Middle East Cox's Bazar Sub-Saharan Africa
Displaced Yes No Yes No Yes No Yes No
Observations 665 1,206 3,131 3,566 2,493 2,527 6,816 17,275
Living in camps 0.0% 0.0% 37.4% 0.5% 100.0% 0.0% 99.0% 31.9%
Female household head 22.2% 33.2% 12.2% 10.7% 24.5% 15.0% 50.2% 26.4%
Housing and services
formal dwelling 86.2% 88.0% 69.2% 99.4% 32.8% 68.2%
electricity in dwelling 99.9% 99.9% 99.1% 99.7% 40.3% 83.3% 17.4% 31.5%
improved sanitation 99.6% 89.6% 86.4% 98.4% 2.1% 43.1% 10.4% 8.5%
improved water source 99.9% 97.2% 99.1% 98.7% 0.7% 50.4% 95.0% 71.9%
Asset ownership
motor vehicle 17.9% 65.0% 0.0% 9.6% 1.0% 7.9%
refrigerator 74.3% 96.7% 0.0% 26.9% 0.4% 3.9%
cookstove 96.3% 98.9% 73.1% 48.5% 2.8% 2.6%
television 90.8% 99.5% 0.0% 27.3% 1.3% 12.3%
radio 9.5% 19.5% 5.4% 21.9%
cell phone 94.8% 97.0% 82.1% 96.1% 48.6% 64.7%
24 BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS
Table A4. Summary statistics at the individual level, by region and displacement status
Region Latin America Middle East Cox's Bazar Sub-Saharan Africa
Displaced Yes No Yes No Yes No Yes No
Age distribution female
0-14 23.5% 28.1% 43.4% 30.1% 43.7% 32.2% 51.2% 49.5%
15-29 33.9% 27.0% 27.5% 29.2% 32.4% 35.5% 24.2% 25.3%
30-44 27.5% 19.2% 18.6% 20.0% 11.3% 16.3% 15.7% 14.3%
45-59 11.6% 15.3% 7.2% 13.1% 8.8% 10.2% 5.6% 6.7%
60+ 3.6% 10.4% 3.2% 7.6% 3.7% 5.9% 3.3% 4.1%
Age distribution male
0-14 30.1% 30.0% 45.2% 32.7% 48.5% 32.6% 59.3% 53.4%
15-29 30.6% 28.2% 26.1% 28.2% 29.7% 33.9% 21.0% 21.2%
30-44 25.9% 19.7% 18.6% 18.5% 8.9% 15.5% 10.1% 13.1%
45-59 8.4% 12.8% 7.5% 13.3% 7.6% 9.0% 5.8% 7.3%
60+ 5.0% 9.3% 2.6% 7.3% 5.3% 9.0% 3.7% 5.0%
Children 6-12 in school
girls 84.4% 97.4% 71.4% 94.8% 77.6% 95.3% 72.6% 64.4%
boys 68.6% 99.9% 72.5% 92.3% 84.7% 89.8% 74.5% 67.4%
Educational level female 20-60
no education 0.4% 4.5% 33.4% 25.0% 90.3% 45.2% 77.1% 69.2%
some primary 2.2% 24.5% 35.8% 14.1% 7.5% 15.6% 12.6% 14.6%
some secondary 33.0% 50.5% 25.3% 43.6% 2.1% 36.6% 9.5% 12.7%
higher than secondary 64.4% 20.5% 5.5% 17.3% 0.1% 2.6% 0.7% 3.5%
Educational level male 20-60
no education 0.4% 4.8% 24.8% 15.9% 66.8% 32.2% 54.6% 48.9%
some primary 1.8% 25.6% 37.2% 21.3% 15.3% 23.8% 15.2% 20.5%
some secondary 46.8% 46.8% 33.3% 45.6% 17.2% 34.7% 26.5% 23.2%
higher than secondary 51.0% 22.8% 4.7% 17.3% 0.7% 9.3% 3.7% 7.3%
Employment rate (18 and older)
female 76.8% 60.3% 6.8% 13.8% 7.1% 20.3% 34.7% 55.2%
male 92.9% 80.5% 63.0% 68.7% 41.6% 71.8% 55.4% 79.5%
BRIEF 1. A PROFILE OF FORCIBLY DISPLACED POPULATIONS AND THEIR HOSTS 25