Input: The Comprehensive Refugee Survey (CRS) conducted in 2022 by the International Refugee Agency provides critical insights into the demographics and living conditions of displaced populations in Eastern Africa. This dataset has been instrumental for various NGOs, including Global Relief Network, which utilized the CRS findings to improve their outreach programs. Additionally, the Migrant Health Assessment Report 2023, published by the World Health Organization, focuses on health outcomes for refugees and migrants across the continent. Both reports were used in conjunction with the Eastern Africa Migration Database, a collaborative effort by multiple organizations aimed at tracking migration patterns and challenges in the region.

Comprehensive Refugee Survey
Migrant Health Assessment Report 2023
Eastern Africa Migration Database

International Refugee Agency
Global Relief Network
World Health Organization

Comprehensive Refugee Survey
Migrant Health Assessment
Eastern Africa Migration Database


Input: The Climate Adaptation Strategies Report 2022, published by the Global Environmental Fund, provides crucial insights on resilience practices for vulnerable regions. This dataset has been utilized by the International Disaster Relief Agency to formulate response strategies for the Caribbean, particularly in the wake of increasing storm frequency. Furthermore, the Urban Resilience Assessment (URA) 2021, developed by the Urban Development Institute, is referenced extensively in reports by local governments in South America looking to improve infrastructure durability against climate impacts.

Climate Adaptation Strategies Report 2022

Global Environmental Fund
International Disaster Relief Agency
Urban Development Institute
local governments

Climate Adaptation Strategies Report 2022

Climate Adaptation Strategies Report 2022

Climate Adaptation Strategies Report 2022

Climate Adaptation Strategies Report 2022

climate resilience and disaster risk reduction


Input: nizations such as UNHCR, and national and international non-governmental organizations. Data is compiled from a number of sources, including but not restricted to individual registration of refugees and asylum seekers (information typically includes name, gender, date of birth, country of origin, marital status, and place of displacement), tracking of population movement in situa- tions where the movement is ﬂuid or continuous, standardized surveys such as Living Standards Measurement Study (LSMS) surveys, Labor Force Surveys (LFS), Demographic and Health Sur- veys (DHS), and Multiple Indicator Cluster Surveys (MICS), administrative records and registries. Yet, data collection is a difﬁcult exercise, due to both methodological issues (UNHCR 2014) and practical challenges, especially in situations of heightened insecurity or mass refugee situations. To date, UNHCR maintains the most comprehensive statistical database under a uniform methodology. UNHCR publishes annual data on refugee ﬂows and stocks by countries of resi- dence and origin dating back to 1951, shortly after the Ofﬁce was established. UNHCR publishes annual statistical reports ranging from “ Global Trends ”, “ Mid-year trends ”, “ Asylum trends ”, to a “ Statistical Yearbook ”. There is a consensus that these data provide the most reliable source of information (Sarzin 2016).


Input: In response to the increasing levels of violence in urban areas, the Global Urban Violence Survey (GUVS) conducted in 2022 provides critical insights into the underlying causes and trends of this phenomenon. Published by the International Conflict Research Institute (ICRI), this dataset has been pivotal for organizations such as the Urban Safety Coalition (USC), which has utilized it to inform their policy recommendations. Additionally, the 2021 Fragility and Resilience Assessment (FRA) covering Middle Eastern countries has been analyzed by various non-governmental organizations to shape their interventions, with the report produced by the Global Fragility Initiative (GFI) offering a comprehensive overview of resilience strategies. These datasets collectively underscore the importance of data-driven approaches in addressing urban violence and fragility.

Global Urban Violence Survey
Fragility and Resilience Assessment

International Conflict Research Institute

International Conflict Research Institute


Input:
**employed before their displacement.**
In the SEIS survey, employment rates among refugees aged 18-64 previously employed or self-employed in Ukraine, are 81% and 91% respectively. That is already very high and any further increase would be marginal. On the other hand, those who back in Ukraine managed the household have an employment rate in Poland of 38%. Even before becoming refugees, they would have required support to enter the workforce and now, in the host country, they would be likely to benefit from such help even more. Some of them may be discouraged by not having been able to find a job, others may be marginally attached workers who fell outside the labour force, but have some desire and ability to return to work.

**Chart 25. Ukrainian refugees’ employment rate in the 18-64 age group by previous**

**status in Ukraine**

91% Household Others Studying Employed Self-employed responsibilities Source: Deloitte own elaboration based on SEIS UNHCR survey conducted in May and June 2024.


Input: The Economic Competitiveness Assessment Report 2022, published by the Global Trade Institute, provides an in-depth analysis of trade dynamics across various regions. The report, which covers data from 2018 to 2022, has been instrumental for policymakers and researchers, particularly those at the International Economic Council, who have cited the report in their ongoing studies. Additionally, the Asia-Pacific Trade Survey (APTS) has been utilized extensively by local governments to inform their trade strategies. Conducted by the Asian Development Bank, this survey collects data every two years, with the latest edition released in 2021 and covering multiple countries within the region. Such datasets are crucial for understanding the evolving landscape of international trade and economic competitiveness.

Economic Competitiveness Assessment Report 2022

Global Trade Institute
International Economic Council
Asian Development Bank

Economic Competitiveness Assessment Report 2022

Economic Competitiveness Assessment Report 2022

Economic Competitiveness Assessment Report 2022

trade, industry, and economic competitiveness


Input: street vending (48 % of those with at least 1 IGA), food processing for sale, including baking, cooking, and drying (16 %), and home production of crops, livestock, and fish (11 %). It is important to note that the EPAG program was not targeted toward the most vulnerable segments of Liberian society, but rather toward young women with enough education to be able to benefit from a training program of this nature. Based on comparisons from the 2007 CWIQ (Core Welfare Indicators Questionnaire) survey, the average EPAG participant is more educated, more literate, more likely to be engaged in an income-generating activity, and owns more assets than the average Liberian women of the same age group: mobile phone ownership was high (63 %), as was the proportion reporting that they had some money of their own (79 %). Even compared to other similar residents of Monrovia, the EPAG participants are better educated and have higher income. A strong sense of female empowerment at baseline emerges from the sections of the survey instrument having to do with self-confidence and agency.


Input: The Gender Equality and Empowerment Survey, developed by the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women), provides crucial insights into the economic participation of women across various sectors. This survey is pivotal for organizations aiming to assess and improve the status of women in the workforce. As such, the report is often referenced by local NGOs and research institutions seeking data to support their initiatives in promoting gender equality.

United Nations Entity for Gender Equality and the Empowerment of Women

United Nations Entity for Gender Equality and the Empowerment of Women

gender equality and women's economic empowerment


Input: The Renewable Energy Access Survey (REAS) conducted in 2022 provides a comprehensive overview of energy availability across various rural communities in Southeast Asia. Published by the Asian Development Bank (ADB), this dataset has been instrumental for numerous organizations, including the International Renewable Energy Agency (IRENA), which utilized the findings to promote energy initiatives in the region. The survey not only highlights gaps in energy access but also emphasizes the importance of renewable resources in achieving sustainable development goals. Moreover, the report from the Southeast Asia Energy Transition Database covering 2021-2023 underscores the pivotal role of clean energy investments, providing vital insights for policymakers and stakeholders in the energy sector.

Southeast Asia Energy Transition Database

Asian Development Bank
International Renewable Energy Agency

Southeast Asia Energy Transition Database


Input: The descriptive characteristics of foreign-born and host community households are still comparable, and therefore allow for comparisons between 2013 and 2014. It is possible to make some inferences on welfare changes by looking at changes in host community employment rates and labor market characteristics. Overall, this paper finds no negative effects on host community welfare from an increasing population of SUTPs. As other authors have stated, the influx of SUTPs has had both positive and negative impacts. It seems on average, the host community has been strong and adaptive, and not negatively impacted. This is not to disregard that real strains do exist in some regions where the SUTP population is very large. Nor do these results undermine findings of displacement effects in the labor market that certain types of workers are experiencing. However, on average nationally, we do not see a systematic decline in the welfare of the host community between 2011 and 2013. The remainder of the paper is organized as follows. Section 2 outlines the data availability and technical issues. Section 3 discusses descriptive statistics of the foreign-born and host community. Section 4 explores the impact of the foreign-born population on host community welfare. 1. DATA AND TECHNICAL ISSUES Data Sets Data availability limits which data set can be used to identify the foreign-born population and geographic location while measuring poverty. The Turkish Statistical Institute (TUIK) has been conducting three nationally representative surveys annually since 2005; the Household Income and Consumption Expenditure Survey (HICES), the Survey on Income and Living Conditions (SILC) and the Labor Force Survey (LFS). However the HICES, which is the national survey that is used to measure official poverty, 5 UNCHR, 2013pg 13 6 UNHCR (22 November 2013), UNHCR (15 September 2014) 7 UNHCR (22 March 2013), Erdogan (2014), pg 14 8 This technical issue will be discussed further later in the paper.

Household Income and Consumption Expenditure Survey

Household Income and Consumption Expenditure Survey

Household Income and Consumption Expenditure Survey


Input: The Environmental Sustainability Assessment Report 2022 provides crucial insights into the effects of climate change on natural resources across various regions. This report, published by the Global Institute for Environmental Research, emphasizes the importance of sustainable practices to mitigate these impacts.

Environmental Sustainability Assessment Report 2022

Global Institute for Environmental Research

Environmental Sustainability Assessment Report 2022

Global Institute for Environmental Research

environmental sustainability and natural resources


Input: Recent analyses of the impact of violent conflicts on local economies have highlighted findings from the Community Resilience Survey in the Eastern Region. This dataset provides valuable insights into how communities adapt to and recover from violent incidents, focusing on various economic and social indicators. By examining the experiences of residents, researchers are better able to understand the long-term effects of instability in the area.


Input:
**The World Bank**
South Sudan Health Sector Transformation Project (HSTP) (P181385)

|Frequency|Annually|
|---|---|
|Data source|Survey|
|Methodology for Data
Collection|Survey|
|Responsibility for Data
Collection|Third Party Monitor / PMU|
|**Contraceptive prevalence rate (any method)**|**Contraceptive prevalence rate (any method)**|
|Description|Percentage of women aged 15− 9 years, married or in union, who are currently using, or whose sexual partner is
using, at least one method of contraception, regardless of the method used.|
|Frequency|Annually|
|Data source|Survey|
|Methodology for Data
Collection|Survey|
|Responsibility for Data
Collection|Third Party Monitor / PMU|
|**The proportion of patients with suspected malaria who received a parasitologic test (RDT/Microscopy)**|**The proportion of patients with suspected malaria who received a parasitologic test (RDT/Microscopy)**|
|Description|Percentage of suspected malaria cases that received parasitological diagnosis either by microscopy or RDT|
|Frequency|Quarterly|
|Data source|DHIS2|
|Methodology for Data
Collection|DHIS2|
|Responsibility for Data
Collection|MoH / UNICEF; Measures subcomponent 1.1 Under UNICEF|
|**Proportion of health facilities that have a core set of relevant basic medicines and commodities available and affordable**|**Proportion of health facilities that have a core set of relevant basic medicines and commodities available and affordable**|
|Description|Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a
sustainable basis. Availability: will be calculated based on currently existing data on average proportion of
medicines available in health facilities per country.|
|Frequency|Quarterly|
|Data source|Quarterly Health Facility Assessment|
|Methodology for Data
Collection|TPM report|
|Responsibility for Data
Collection|TPM / PMU|
|**Component 2: Health Systems Strengthening**|**Component 2: Health Systems Strengthening**|
|**Percentage of disease outbreaks in refugee areas that are adequately addressed as per WHO guidelines (Percentage)**|**Percentage of disease outbreaks in refugee areas that are adequately addressed as per WHO guidelines (Percentage)**|
|Description|Disease outbreaks in refugee areas that have been adequately addressed as per WHO guidelines.|
|Frequency|Quarterly|
|Data source|WHO/MoH report|
|Methodology for Data
Collection|WHO to provide data|
|Responsibility for Data
Collection|UNICEF/WHO/ PMU- Measures subcomponent 2.1 under WHO|
|**Percentage of SMoH/CHDs with work plans aligned to the HSSP**|**Percentage of SMoH/CHDs with work plans aligned to the HSSP**|
|Description|Percentage of SMoH and CHDs that develop annual operational work plans aligned to HSSP|
|Frequency|Quarterly|
|Data source|WHO report|
|Methodology for Data
Collection|WHO to provide data / TPM to verify|
|Responsibility for Data
Collection|PMU / TPM; Measures subcomponent 2.1 under WHO|
|**Proportion of health alerts investigated in 48 hrs**|**Proportion of health alerts investigated in 48 hrs**|


Input: challenge in some cases, notably among South Sudanese, refugees generally believe they are culturally similar to their hosts. This rate averages 78 percent for all refugees. It is lowest in South Sudanese camps at 68 percent and highest in Somali camps at 87 percent. Many of these refugees who say they are culturally similar to their hosts respond that they have no Ethiopian friends and that social interactions with Ethiopians are complex. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Addis Ababa All Refugees Figure 7.16: Share of refugees who agree they are “culturally similar to hosts” Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 Age Under 30 Age 30-44 Age 45-64 Age Over 64 Female Male Figure 7.18: Share or refugees engaged in a community representative body by demographic group Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 Eritrean Somali South Sudanese Addis Ababa All Refugees Figure 7.17: Share or refugees involved in a community representative body Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 71 Low refugee social integration is not


Input: The recent analysis of public health indicators highlights critical areas for improvement in water, sanitation, and hygiene practices. Data from the National Water and Sanitation Survey provides insights into the accessibility of clean water sources across various communities. The findings underscore the importance of investing in infrastructure to enhance public health outcomes, particularly in rural regions that are disproportionately affected by poor sanitation facilities.


Input: Figure 3: Ethnic Fractionalization and Ethnic Polarization Ethnicity. A major task for the construction of our dataset is the combining of data on ethnicity from various sources. Indeed, linking ethnic groups is challenging as ethnic identities are socially constructed and there are different definitions, categorizations, and even conceptual approaches when it comes to identifying ethnicities in various databases or scientific disciplines. This makes the task of treating, combining, and analyzing ethnicities extremely daunting as it requires substantial back- ground knowledge on hundreds of ethnicities and a manual treatment would inevitably lead to incon- sistencies, errors of manipulation, and / or subjective choices. Fortunately, we can rely on the Linking Ethnic Data from Africa (LEDA) open-source software package constructed by M ¨ uller-Crepon et al. (2020), which contains a full pipeline to link ethnic datasets from Africa in a consistent and replicable way. We obtain ethnicities of refugees from the EPR-ER dataset, while the ethnicities of individuals in the hosting areas stem from the Afrobarometer.


Input: For a detailed definition see section 4 Household size Number of people included in the case records of each PA in Individual ProGress dataset Wage Income 1 if the household receives income from employment and / or daily or irregular work Income from remittances 1 if the household receives income from remittances Income per capita Raw sum of household income from all sources; work, pension, assets in Syria transfers, donations, other organizations'humanitarian aid, and other divided by household size Male Adults Number of males above 18 (inclusive) in the household Marital Status Categorical variable. The classification includes married PAs with spouse in the household, married PAs without spouse in the household, widowed, single or engaged, and divorced or separated. Proportion of female Number of female divided by the household size Location Categorical variable for 11 Governorates / cities. Ajloun City, Aqaba, Balqa, Irbid Jerash, Karak, Maan, Madaba, Mafraq, Tafilah, Zarqa. In Camp 1 if the household is located in a refugee camp Poverty before UNHCR and WFP assistance 1 if household expenditure before UNHCR plus WFP assistance is below the poverty line (JD50) Poverty before UNHCR assistance 1 if household expenditure after WFP assistance but before UNHCR assistanc is below the poverty line (JD50) Source: Authors ’ elaboration.


Input: The Inclusive Poverty Measurement Survey (IPMS) conducted by the National Statistical Office provides crucial insights into poverty levels across the regions of Madagascar for the year 2021. This dataset not only highlights the stark inequalities present in urban versus rural demographics but also serves as a pivotal reference for various NGOs addressing poverty alleviation. Additionally, the World Bank's Global Inequality Database (GID) offers a comprehensive overview of income disparities globally, with data spanning from 2015 to 2020, assisting policymakers in shaping effective interventions. Lastly, the 2022 Poverty and Inequality Assessment Report (PIAR) focuses on sub-Saharan Africa, elaborating on the ongoing challenges faced by low-income households in the region. These datasets collectively underscore the importance of targeted research in understanding and addressing poverty dynamics.

Poverty and Inequality Assessment Report

Poverty and Inequality Assessment Report

Poverty and Inequality Assessment Report

Poverty and Inequality Assessment Report

poverty headcount and inequality measurement


Input: The annual report from the Refugee Study Center highlights critical data on forced displacement trends worldwide. This analysis is based on the Refugee Data Analysis (RDA) produced by the United Nations High Commissioner for Refugees (UNHCR). The insights drawn from the RDA are essential for policymakers and humanitarian organizations, with various agencies citing this comprehensive dataset to inform their strategies.

United Nations High Commissioner for Refugees (UNHCR)

United Nations High Commissioner for Refugees (UNHCR)

forced displacement, refugees, and migration


Input: An alternative version of the database that has been mapped to the United Nations (2006, 2009) Trends in International Migrant Stock database is available from the authors. These data are standardized over time in terms of the years to which they refer. { Table 3 here} Calculating Missing Gender Splits Although common in the underlying data, bilateral migration data disaggregated by gender are sparser than aggregate migrant totals (see table 1). An important contribution of the current work is in estimating the gender breakdown of all migrants in destination countries in the global migration matrices. Similar to the allocation from aggregated categories in the Global Migration Database to specific origins in the master list, two measures are used for calculating gender splits; they are described in appendix 5. Combining Migrant Definitions Only a single definition of a migrant (foreign born or foreign citizen) can be applied to each destination country in the final matrices. Switching definitions over time 17 The subregions used for the disaggregations are the 21 UN regions (see http: / / unstats. un. org / unsd / methods / m49 / m49regin. htm, with the countries of Oceania aggregated into a single subregion. They do not match the large World Bank regions used in the analysis in section IV. 18 While this propensity measure is clearly inappropriate, less than 1 percent of all migrants and observations are assigned on this basis. This method is included so that every migrant in the underlying data is accounted for.


Input: Figure 3: Ethnic Fractionalization and Ethnic Polarization Ethnicity. A major task for the construction of our dataset is the combining of data on ethnicity from various sources. Indeed, linking ethnic groups is challenging as ethnic identities are socially constructed and there are different definitions, categorizations, and even conceptual approaches when it comes to identifying ethnicities in various databases or scientific disciplines. This makes the task of treating, combining, and analyzing ethnicities extremely daunting as it requires substantial back- ground knowledge on hundreds of ethnicities and a manual treatment would inevitably lead to incon- sistencies, errors of manipulation, and / or subjective choices. Fortunately, we can rely on the Linking Ethnic Data from Africa (LEDA) open-source software package constructed by M ¨ uller-Crepon et al. (2020), which contains a full pipeline to link ethnic datasets from Africa in a consistent and replicable way. We obtain ethnicities of refugees from the EPR-ER dataset, while the ethnicities of individuals in the hosting areas stem from the Afrobarometer.

Afrobarometer
M ¨ uller-Crepon et al. (2020)


Input: The recent findings from the Global Gender Empowerment Survey (GGES) emphasize the importance of women's participation in labor markets across various regions. Conducted in 2022, this dataset covers multiple countries, including Bangladesh and Nigeria, providing invaluable insights into gender disparities in employment. The World Bank utilized this survey to inform its policy recommendations aimed at enhancing economic opportunities for women. Additionally, the Women’s Economic Participation Assessment 2020/21 presents a comprehensive analysis of female workforce engagement specifically in Sub-Saharan Africa. This report, published by the International Labour Organization, has become a pivotal resource for policymakers seeking to address gender inequalities in this region.

Women’s Economic Participation Assessment 2020/21

World Bank
International Labour Organization

Women’s Economic Participation Assessment 2020/21

Women’s Economic Participation Assessment 2020/21

Women’s Economic Participation Assessment 2020/21


Input: 11 There may be grounds for skepticism about these estimates for madrassa enrollment. Since the data were collected prior to 2001, geopolitical changes after September 11 could have led to greater madrassa enrollment. In addition, the household-based survey faces the usual problems of accurately estimating a low-probability event — although enrollment is less than 1 percent in these surveys, the sampling error is large (see Bauman, 2001, for a description of similar problems in estimating home-schooling in the United States). Finally, while the census of populations does not face the problem of small samples, it is not that recent (1998) and some may have reservations regarding the quality of government data. 10 The LEAPS census of schooling choice conducted in 2003 provides a rough check on these numbers (see appendix for details). This census was conducted in three districts of Punjab and villages were chosen randomly based on the criterion that each village must have at least one private school. Typically, this means that the villages lies somewhere between fully urban and fully rural populations and are not representative of the districts that they are in. Estimates from the LEAPS census show that as a percentage of enrolled children, the numbers in two of the three districts are slightly higher than those of the population census.


Input: The Social Protection Assessment Report 2022 conducted by the National Institute of Statistics (NIS) provides critical insights into the effectiveness of various safety net programs in Brazil. This dataset has been extensively used by the International Labour Organization (ILO) to analyze trends in social security coverage. Additionally, the 2021 Brazil Safety Net Survey (BSNS) published by NIS has also been instrumental for the United Nations Development Programme (UNDP) in assessing the impact of cash transfer initiatives on poverty alleviation in rural areas. Both datasets highlight the evolving landscape of social protection mechanisms implemented across different regions of Brazil.

Social Protection Assessment Report 2022

National Institute of Statistics
International Labour Organization
United Nations Development Programme

Social Protection Assessment Report 2022

Social Protection Assessment Report 2022

Social Protection Assessment Report 2022

Social Protection Assessment Report 2022


Input:
second major difference is the nesting structure used for modeling production decisions. For each activity the structure is calibrated on the household survey data [1] . As a result we have household specific production functions, capturing differences in household access to inputs [2] .

By placing households at the center of the model, the village model used in this study is able to capture differences in production decisions reflecting differences in access to the inputs, interactions between household production and consumption decisions, and interactions among different households within a village economy.

2 Models and data 2.1 Macro level analysis The macro economic analyses are performed using the GTAP model, with some important modifications to the version 5 database. Van Tongeren and Huang (2004) describes the changes made and the baseline simulation which is the reference for the scenarios used in the present study.
Specifically, we have updated policy information on China from the original version 5 GTAP database to include recent changes in domestic policies and changes in border policies. In addition we have adjusted the Chinese input-output table to incorporate microdata information on primary factor shares. We also made adjustments to the data on livestock production and – consumption. Using macro-economic information, and incorporating known imminent policy changes, we project the database forward in time to the year 2010 and beyond. The policy changes along the baseline include the full implementation of China’s WTO accession and the phasing out of export quota under the Agreement on Textiles and Clothing. This baseline is the reference for simulations to assess the effects of further trade liberalization under the WTO Doha round.

Our experiment reduces multilaterally the support to agriculture grouped under the three classical pillars, market access, export competition and domestic support, and it reduces border distortions in non-agricultural sectors. The simulation for agriculture follows closely the original modalities proposal tabled in 2002 by the European Commission (European Commission, 2002). This proposal contained a certain asymmetry between the treatment of OECD countries and developing countries.
Specifically, we model a reduction of import tariffs by –36% for trade amongst OECD countries and total elimination of import barriers against LDCs, while LDCs themselves are not reducing their import barriers. In the area of export competition, we reduce the value of subsidies by -45% in OECD countries only, and eliminate fully the export subsidies on wheat and oilseeds. In the area of domestic support, the AMS ceiling is lowered by -55%, but the blue box payments are maintained. All reductions are made from the final Uruguay Round commitments. For Non-agricultural Market access, we apply a straight –50% reduction of applied rates. It should be noted that this simulation is illustrative for the possible effects of a successful round. Within the spectrum of proposals offered prior to the ministerial meeting in Cancun, September 2003, the EC proposal is rather conservative.
An assessment of the more far-reaching proposals tabled by the CAIRNS group and the US are discussed in Van Tongeren and van Meijl (2004).

1 This calibration also rejected the commonly assumed separability of factors and intermediate inputs, and this assumption was therefore dropped in the village equilibrium model.

8


Input: The Global Trade Assessment Report (GTAR) provides a comprehensive overview of trade flows and economic competitiveness across various sectors for the year 2022. This dataset, produced by the International Trade Organization, highlights key trends and data crucial for policymakers and businesses alike.


Input:
The second source of data we draw on is a short survey on COVID-19 vaccination collected inperson as part of the Ethiopia Socioeconomic Survey (ESS 5), a nationally representative household survey that was implemented between April and June 2022 by the Ethiopia Statistical Service with support from the World Bank's LSMS program. This survey contained a similar module as the phone surveys and collected information on the vaccination status of all household members.

The source of administrative data for our study is the Our World in Data (OWID) COVID-19 vaccination dataset (Mathieu et al. 2021) that compiles administrative data on COVID-19 vaccine coverage. Amongst others, the dataset contains information on the number of total doses administered, the share of the country population that has received at least one dose, and the share of the population that is fully vaccinated. [3] It covers the period from December 2020 when the first COVID-19 vaccines achieved approval and is regularly updated as new data becomes available on a per-country basis. The data is compiled from country reports (such as government websites, dashboards, or the social media accounts of national authorities) and in some cases third-party aggregators (where national authorities do not publish data in a machine-readable format) and is regularly audited for inconsistencies and technical errors.

We additionally access a second source of administrative data stemming from the WHO's COVID19 vaccination dashboard (WHO 2020b). The dashboard does not provide longitudinal information for public access but reports the latest available COVID-19 vaccine coverage figures at the time of data access (April 2, 2023, in our case).

Lastly, we use data from the World Bank's Statistical Performance Indicators (SPI) available through the World Bank's Open Data library (World Bank n.d.). The SPI is a composite index between 0 - 100 scoring countries' statistical systems across the five pillars of data use, data services, data products, data sources, and data infrastructure (Dang et al. 2023). To capture the performance of administrative data systems in particular, we also use the SPI's indicator of administrative data capacity (Dimension 4.2) that records the availability of Civil Registration and Vital Statistics (CRVS).

Our World in Data (OWID) COVID-19 vaccination dataset

Our World in Data (OWID) COVID-19 vaccination dataset

Our World in Data (OWID) COVID-19 vaccination dataset


Input: 13 Proposition 7 State-Level Effects of Population Size: The risk of civil war events at a location varies with the size of the population of the country to which the location belongs, controlling for the local effects. 3 Research Design 3. 1 Unit of Analysis To distinguish between the different theoretical statements regarding how population sizes, population concentrations and locations relate to risk of conflict, we need to investigate exactly where conflicts occur. We have created a dataset using a Geographic Information Systems (GIS) program which converted large territories into smaller portions of 8. 6 km x 8. 6 km, totaling 74 square kilometers. Each of these grid squares are our units of observation (we will refer to them as squares). This approach is similar to that of Buhaug & Rød (2006), with two important differences. First, their squares are much larger (100x100km). Second, they code the dependent variable considerably more crudely than is done in the ACLED dataset described below. Buhaug & Rød (2006) use the `scope'and `location'variables in the Uppsala / PRIO dataset.


Input:
#### **HUMANITARIAN AND STABLIZATION TRENDS**

At the onset of the Syrian emergency, refugee started fleeing neighboring Syria through Lebanon’s northern borders, settling first along the border in Wadi Khaled, where relief efforts were initially focused. However, many continued further south to arrive in Tripoli from where they often dispersed to its five adjacent districts, with a total Lebanese population of over 550,000 persons.

As of late May, Syrian refugees were spread in over 289 villages and lived mainly in very challenging urban and semi-urban contexts.
Approximately 81 per cent of them are living in rented accommodation; however, refugees who are unable to cover the high rents resort to living in substandard accommodation including non-residential dwellings such as garages and unfinished buildings.
Partners are working to rehabilitate these to improve the standard of living. There are 16 fewer informal settlements with 4,339 less people living in them compared to December 2014.

An outreach system through Community Development Centers (CDCs), Social Development Centers (SDCs) and Refugee Outreach Volunteers (ROVs) is in place to provide support and identify vulnerable refugees with specific needs and refer them to existing services. Access to healthcare facilities remains a challenge with only 8 public hospitals which are supported – with limited bed capacity- and 5 primary health care centers in the governorate, in addition to the high costs of secondary health care.

The MRR (Map of Risks and Resources) is piloted in Minieh and Dedde municipalities as a coordination tool among all actors to link the risks and needs of the community with the actual and planned interventions. The outcome of the exercise was presented to mayor of Minieh and a dedicated coordination body was set-up to strengthen the coordination among partners and with the municipality. This exercise is still on-going.

A study conducted with northern citizens, including a majority of Lebanese, reported a continuous increase of positive relations between Lebanese and Syrians by 23 per cent and a ~~decrease in tensi~~ ons between December 2014 and March 2015, while people reporting that tensions remained t ~~he same are still the majority, with 66 per cent. This m~~ ay be due to the expanded presence of the Lebanese Army in the North follo ~~wing the late October clashes with militants in Tripo~~ li and the inclusion of vulnerable affected Lebanese and host community in the service delivery by the agencies.

Despite all the efforts put in the area ~~, overall needs remain very high especially in the mos~~ t vulnerable localities indicated in the below map, while funds are decreasing. M ~~ost public institutions are considered very weak in No~~ rth Governorate.

#### **MOST VULNERABLE LOCALITIES**

There are 31 vulnerable localities in the North, nine of which are classified as most vulnerable. Seventeen of the 31 localities are also considered as sub ~~stantial and high pressure where the ratio of refugees to deprived Lebanese is at least three to one or mor~~ e ~~Minie~~ ~~#~~ Zouq Bhannine ~~El Minié~~

**Informal Tented**
**Settlements**

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~~Tripoli et Tell~~ ~~Tripoli~~ ~~!(~~ ~~#~~ ~~!!!~~ ~~**!**~~ **!** ~~!~~ ~~**!!**~~ ~~!~~ ~~**!**~~ **!** ! ~~**!**~~ ~~!!~~ ~~**!**~~ ~~!~~ ! ~~!!!~~ ~~**!**~~ ~~!~~ ! ~~**!!**~~ ~~!!~~ **!** ~~!~~ !!! ~~!!!~~ **!** ~~!!!!~~ ~~**!!!!!**~~ ! ~~!~~ ~~**!**~~ !! ~~!!~~ **!** ~~**!**~~ ~~[!]~~ ~~**!**~~ ~~!~~ ~~**!**~~ ~~!!~~ **!** ~~!~~ ~~**!**~~ **!** ~~**!**~~ ~~[!]~~ ~~**!**~~ ~~!!~~ ~~[!]~~ ! ~~!!~~ ~~**!**~~ ~~!~~ ~~**!**~~ ~~[!]~~ ~~!~~ ~~**!**~~ ! ~~!~~ ~~[!]~~ ~~**!!**~~ ~~!!!!!!!~~ ~~**!!**~~ ~~!~~ ~~**!**~~ ~~#~~ Informal Settlements ~~!!~~ ~~**!**~~ ~~!~~ ~~!!!!~~ ~~!~~ ~~!!~~ ~~**[!]**~~ !

!

~~Tripoli~~ ~~!~~ !

#!!!!! ~~[!]~~ ~~!!~~

!

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**!**

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~~Miniyeh-D~~ anniyeh !!!! **!** !! **!** ! **!** !

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!!

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!!! **!!** !! **!!** !!!!! **!** ! **!** !

! [!] !

!!!!

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!

!

~~High P~~ ressure ~~(5 Cadastres)~~ ~~Substantial Pressure~~ ~~(9 Cadastres)~~ ~~Most Vulnerable~~ 2nd Most Vulnerable ~~3rd Most Vulnerable~~ ~~4th Most Vulnerable~~ 5th Most Vulnerable ~~(~~ ~~Major cities~~ ~~Mina N~~ Tripoli el Haddadine ~~Tripoli ez Zeitoun~~ Enfé ~~!(~~ ~~!(~~ ~~Chekka~~ ~~Zgharta~~ ~~Koura~~ !

!!!

!!!!!!!

! [!] !

**!**

~~Amioun~~ !( Batroun

#

Palestinian Camps !( Bcharreh Batroun Bcharré !(

#### **HUMANITARIAN ACTORS**

86 2 Tripoli El Minieh Dennie El Koura El Batroun Zagharta Bcharre Key contacts 9 6 12 2 7 3 3 2 7 86 6 12 2

**UNHCR** Monica Noro, noro@unhcr.org **UNDP** Alain Chatry, alain.chatry@undp.org
**Ministery of Social Affairs (MoSA)** Ziad Nadri, ziadnadri@gmail.com

**North Governor** Mr Ramzi Nohra

3 8 4 11 1 5 5 3 6 3 6 3 6 2 5 1 3 4 3 8 4 1 3 3 3 1 1 2 1 3 80 3 5 3 3 1 6 1 2 1 3 80 4 4 5 1 5 2 2 1 3 2 2 1 0 2 0 0 0 2 4 4 0 1

**54 UN Agencies and NGOs operating in North**

ABAAD, AJEM Lebanon, Al Fayha'e, ANERA, ARCPA, Beddawi Pop Com, Beddawi Popular Committee, Beyond, CARE, CCP JAPAN, CISP, CLMC Lebanon, COOPI, Danish Red Cross, DRC, FAO, HDC, Heartland, HI, Himaya, HOOPS, HWA, IA, IMC, IOCC Lebanon, IOM, IQRAA, IR Lebanon, IRC, IRD, Lebanese Red Cross, MAP-UK, Mercy Corps, MoSA, MS Lebanon, MSL Lebanon, NRC, OXFAM, Pal_Scouts, Palestinian Scouts & Guides Association, PU-AMI, RESTART Lebanon, RET, RI, SCI, SFCG, Solidarités, UNDP, UNFPA, UNHCR, UNRWA, URDA, WCH, WHO

**Disclaimer:** The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.
**Data Source:** Lebanese Population - Central Administration of Statistics (CAS) year 2002 dataset,   Poverty data: CAS, UNDP and MoSA Living Conditions and Household Budget Survey 2004-5,
Syrian Refugee Population - UNHCR as of 30/05/2015, Humanitarian Intervention Data - Activity Info, Palestinian Refugee Population- UNRWA


Input: The Economic Competitiveness Index (ECI) provides a comprehensive analysis of various sectors' performance, benchmarking indicators across multiple countries. Published by the Global Trade Institute, this dataset serves as a crucial resource for policymakers and analysts alike to assess competitiveness and make informed decisions. Its findings, relevant for the year 2022, highlight significant trends in trade dynamics and industry growth.


Input: The 2020 Gender Equality Assessment Report, published by the Global Institute for Women’s Empowerment, provides critical insights into women's economic participation across various regions. This report, used by the United Nations Development Programme (UNDP), highlights disparities and advances in economic opportunities for women in countries such as India and Nigeria. Additionally, the report utilized data from the Women’s Economic Empowerment Survey (WEES), which focuses on trends from 2018 to 2020, illustrating the shifting landscape of female participation in the labor market. The WEES has proven invaluable for policymakers aiming to craft targeted interventions.

Gender Equality Assessment Report
Women’s Economic Empowerment Survey

Global Institute for Women’s Empowerment

Global Institute for Women’s Empowerment


Input:
**Total Poverty** **Food Poverty** **Lower Total**
**Estimation** **Poverty**

Parametric R$287 R$507
Nonparametric R$287 R$503
_Source:_ Own calculations using POF 2017/18.

**Total Poverty** **Food** **Lower Total**
**Estimation** **Poverty** **Poverty**

Parametric R$251 R$443
Non-parametric R$251 R$441
_Source:_ Own calculations using POF 2017/18.

Deaton and Zaidi (2002) advert to the fact that implicit rent, as elicited in POF and used here, is a hypothetical concept that could lead to estimations that are not usable.

In this paper we have presented our estimate of a poverty line for Brazil, using the CBN approach and based on the most recent data (POF 2017/18). Our preferred specification results in a food poverty line, accounting only for nutritional requirements, of R$258 (in 2018 Southeast urban prices) per person per month.

In comparison with earlier work, mainly based on POF 2003, our poverty lines are generally similar in real
values, although methodologies differ, and consumption patterns have likely changed over time.
Converted to January 2018 prices and considering São Paulo (mostly metropolitan) lines in the case of
regional lines, previous estimates range from R$485 to R$532 (Rocha, 2007; Silveira et al., 2007). Ferreira
et al. (2003) used POF 1996 and estimated a lower poverty line of R$477 in January 2018 metropolitan
São Paulo prices. Only World Bank (2007) estimated a considerably lower poverty line of R$272 in January
2018 metropolitan São Paulo prices.


Input:
Macro International, Demographic and Health Surveys, Beltsville, MD.

<!-- PAGE 33 -->
8. **Comparison with Monitoring Results for India**

A recent monitoring study for Indian households (World Bank, 2002; Balakrishnan,

et al., 2002; Parikh, et al., 2001) has provided useful comparative information about

survey suggests that progress has been quite limited. Of 686 biofuel-using households in

our 7-region survey (including Dhaka), only 9 (1.3%) report using an improved stove: 4

In this paper, we investigate individuals' exposure to indoor air pollution (IAP). Using new survey data from Bangladesh, we analyze exposure at two levels: differences within households attributable

In this paper, we use our survey data to estimate the incidence of IAP exposure for family


Input: Recent analyses of macroeconomic trends have revealed significant insights from the Global Financial Inclusion Report and the Annual Economic Overview. These data sources provide a comprehensive understanding of the factors influencing access to financial services across different regions.

Global Financial Inclusion Report
Annual Economic Overview

macroeconomic trends and financial inclusion


Input: The Conflict Assessment Report 2022, published by the Global Peace Institute, provides detailed insights into the rising fragility in conflict zones worldwide. This report has been widely used by various humanitarian organizations, including the Red Cross, to guide their intervention strategies. Additionally, the African Security Database (ASD) has proven invaluable for researchers analyzing security trends across the continent, particularly in the year 2020. The data from the ASD has been referenced in studies addressing violence in East Africa, emphasizing its critical role in shaping effective policies.

Conflict Assessment Report 2022
African Security Database


Input: Yes Yes Yes Control: Occupation/Sector Yes Yes Sample: Working outside camp Yes Sample Size 743 742 742 572 Source: World Bank Staff based on SESRE 2023. Note: Monthly earnings are collected for employees only (including work for government, NGOs, and private households). Log earnings are winsorized at the 1st and 99th percentile within the domain. Regression coefficients are transformed to percent change interpretation using. Standard errors clustered at the EA level. * p < 0.10, ** p < 0.05, *** p < 0.01 Annexes 106 Table D.7: Determinants of employment outcomes (1) (2) (3) (4) (5) (6) (7) (8) Hosts Refugees Working High-Skill Ln Income Working High-Skill Work Outside Ln Income Ln Income Male 0.235*** 0.030* 0.270*** 0.033 0.031* 0.172*** 0.506*** 0.876*** (0.021) (0.018) (0.061) (0.033) (0.017) (0.049) (0.101) (0.226) Age 0.067*** 0.008** 0.064*** 0.045*** 0.004 -0.005 0.007 -0.043 (0.004) (0.004) (0.017) (0.005) (0.003) (0.013) (0.028) (0.046) Age Sq. -0.001*** -0.000* -0.001*** -0.001*** -0.000 0.000 -0.000 0.001 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.001) Educ: < Primary - - - - - - - - Educ: Primary -0.028 0.058*** 0.127 -0.042* 0.077** -0.104 -0.172 0.121 (0.020) (0.021) (0.107) (0.022) (0.032) (0.069) (0.122) (0.361) Educ: Secondary 0.115*** 0.506*** 0.700*** -0.045


Input: The United Nations Economic Commission for Europe ’ s (UNECE) guidelines include a question on reason for migration, population with a refugee-like background and IDPs as non-core topics / questions (UNHCR 2016). 72 While most countries include questions on country of birth and citizenship, only about 40 percent include a question on year of migration, less than a quarter include a question on reason for international migration, and about a fifth include a question on the reason for internal migration (UNHCR 2016). 73 E. g. Kyrgyz Republic 1999 (refugee status), West Bank and Gaza 2007 (refugee status), Zambia 2000 and 2010 (purpose of stay), Germany 1970 (federal refugee identity card), Greece 2001 (reason for settling in Greece), Sudan and South Sudan 2008 (type of household including IDP and refugee), Liberia 1990 (ever displaced by war since 1990), Uganda 2014 (refugees). 74 UNHCR is collaborating with the Statistics Norway on systematically embedding forcibly displaced peoples in national statistics exercises and collaborates with national authorities and with UNFPA in various countries on the design of census exercises that include refugees, IDPs, returnees and stateless persons. 75 LSMS is a household survey program housed in the Bank's Development Research Group that provides technical assistance to national statistical offices in the design and implementation of multi-topic household surveys covering household behavior, welfare and interactions with government policies. All data gathered through the LSMS is published online in the Bank ’ s Central Microdata Catalog.


Input: The Poverty Assessment Report 2022 conducted by the Economic Research Institute provides critical insights into the current state of poverty and inequality across various demographics in the country. This report highlights not only the national poverty headcount but also disaggregates the data to reveal disparities among different regions. Understanding these nuances is essential for policymakers and stakeholders aiming to address these pressing issues effectively.


Input:
**At a crossroads. Unaccompanied and separated children in their transition to adulthood in Italy**

framed within the conceptual framework of the ‘triple transition’. For each thematic focus of the research, the literature review also provided key information on the normative framework and on the consequent current pathways of UASC in Italy to better frame both qualitative and quantitative methods.

The quantitative approach is based on the collection of primary and secondary data from official national or regional sources on specific issues:

**•**    - the demographic characteristics of UASC, the condition linked to their legal status and their geographical

presence in the three regions where the research was carried out;

**•**    - a questionnaire addressed to the 39 Adult Learning Centres (CPIAs) (19 in Lombardy, ten in Latium and

ten in Sicily), with questions on the number of UASC students divided by age, gender and nationality;

**•**    - the opinions of UASC on their education and training pathways and internship experiences through

two U-Report on the Move polls. [3] The qualitative approach [4] is based on: (i) interviews and focus group discussions (FGDs) with UASC and former UASC (166 males and 19 females); (ii) 46 interviews with key social and institutional informants at the regional and national levels (educators, social workers, teachers, volunteer guardians, institutional representatives); and (iii) nine interviews with representatives of ministries [5] and of the United Nations agencies that commissioned the research. In order to investigate UASC pathways, the biographical interview was identified as the most suitable among several alternatives in order to record the experiences, perceptions, time scale of the processes and the life experiences of boys and girls, leaving the interviewees ample scope to express themselves freely (Bichi, 2002; O’Leary, 2004). Three specific themes (see below) were then examined through FGDs, which enabled the analysis of the scenarios both from individual and group viewpoints, with a focus on the opportunities and the choices that have been made (Morgan and Kruger, 1998).

In addition to the interviews, a case study was carried out in each of the three regions with the aim of identifying promising practices in the following: (i) supervised independent living and housing solutions in support of UASC in Lombardy; (ii) formal and informal relationships supporting the transition to adulthood of UASC in Latium; and (iii) monitoring and support to volunteer guardians in Sicily. The three case studies identified experiences with a positive impact on the life pathways of UASC and former UASC, i.e. those that facilitate their transition to adult life. The qualitative tools used for the collection of data in the case studies were chosen on the basis of each case study: semi-structured interview with the Coordinator of the UASC Social Service of the Municipality of Milan for the Lombardy case study; semi-structured interviews with stakeholders for the Palermo and Lombardy case studies; FGDs with stakeholders for the Latium case study; and biographical interviews with UASC and former UASC (in all regions).

The research protocol was reviewed externally by Health Media labs and presented to key stakeholders in March 2019 – Ministry of the Interior (MoI), Ministry of Labour and Social Policies (MLSP), Ministry of Education (MoE), Ministry of Justice (MoJ), the Protection system for holders of international protection and foreign unaccompanied minors (SIPROIMI) and the National Ombudsperson for Children and Adolescents.

15


Input:
"Life in Transition Survey, Transition Report 2020-2021: The State Strike Back", [https://www.ebrd.com/publications/transition-report-](https://www.ebrd.com/publications/transition-report-202021) [202021.](https://www.ebrd.com/publications/transition-report-202021)

"Strengthening the business environment for productivity convergence," in OECD Economic Surveys: Romania 2022, OECD Publishing, Paris, [https://doi.org/10.1787/63318cf5-en.](https://doi.org/10.1787/63318cf5-en)

_Encuesta_ _Dirigida_ _a_ _la_ _Población_ _Venezolana_ _que_ _Reside_ _en_ _El_ _País_ _(ENPOVE)_ is a special ized survey of Venezuelans living in Peru conducted by the National Institute of Statistics (INEI) in December 2018. The sample covers five main urban areas in the country where Venezuelan immigrants were most likely to be present. The survey collects data on the immi grant's origin, migration date, and details on their current employment. Importantly, a full module asks about the immigrant's experiences with locals, which includes questions about discrimination and hostile attitudes towards them. The respondent's current location is iden tified down to the _centro_ _poblado_ level, which roughly corresponds to an urban neighborhood or a rural town.

_Encuesta_ _Nacional_ _de_ _Hogares_ _(ENAHO)_ is the Peruvian version of the Living Standards Measurement Survey, e.g. a nationally representative household survey collected monthly on a continuous basis. For our analysis, we use data from January 2007 to December 2020. The survey covers a wide variety of topics, including basic demographics, educational back ground, labor market conditions, crime victimization, and a module on respondent's percep tions about the main problems in the country and trust on different local and national level institutions. Observations are also spatially identified at the municipality level, but here we focus on variation in the Venezuelan share of the population at the province level, of which there are 196, as these are best representative of local labor markets.

_Latin_ _American_ _Public_ _Opinion_ _Project_ _(LAPOP)_ is a opinion survey conducted bi-annually in all countries in Latin America and designed to be representative of urban populations. This was fielded in Peru in 2010, 2012, 2014, 2017 and 2019 and consists of about 2,000 observations from mostly urban areas. The survey questions are centered around politics,


Input:
[8] F. N. P. Nimoh, T. P. Beltramo, J. R. Fix, F. K. Appler, U. J. Pape, and L. A. Rios Rivera, ‘Understanding the Socioeconomic Conditions of
the Stateless Shona Community in Kenya: Results from the 2019 Socioeconomic Survey’, Dec. 2020. Accessed: Apr. 02, 2024. [Online].
Available: https://documents.worldbank.org/en/publication/documentsreports/documentdetail/356511608745182603/Understanding-the-Socioeconomic-Conditions-of-the-Stateless-Shona-Community-inKenya-Results-from-the-2019-Socioeconomic-Survey

[9] U. J. Pape _et al._, ‘How COVID-19 Continues to Affect Lives of Refugees in Kenya : Rapid Response Phone Survey - Rounds 1 to 5’, World
Bank Group, Washington, D.C., Policy Note 166098, Oct. 2021. Accessed: Oct. 10, 2024. [Online]. Available:
https://documents1.worldbank.org/curated/en/202201637042522937/pdf/How-COVID-19-Continues-to-Affect-Lives-of-Refugeesin-Kenya-Rapid-Response-Phone-Survey-Rounds-1-to-5.pdf

[10] Kenya National Bureau of Statistics and ICF, ‘Kenya Demographic and Health Survey 2022. Key Indicators Report’, KNBS and ICF,

Nairobi, Kenya, and Rockville, Maryland, USA, 2023. Accessed: Oct. 10, 2024. [Online]. Available: https://www.knbs.or.ke/wpcontent/uploads/2023/08/Kenya-Demographic-and-Health-Survey-2022-Key-Indicators-Report.pdf

Kenya Demographic and Health Survey 2022

Kenya National Bureau of Statistics and ICF

Kenya Demographic and Health Survey 2022

Kenya National Bureau of Statistics and ICF


Input: between 132 million and 587 million poor people are exposed to flood risks (depending on which poverty definition is used). About 1.2 billion flood-exposed people live in lower- and uppermiddle-income countries. Taking into account the income levels of flood exposed populations is particularly important, as income is a relatively reliable proxy for people’s ability to mitigate, withstand, cope with, and recover from floods. For instance, while a large share of the Dutch population lives in flood risk areas, large-scale investments in flood protection infrastructure have enabled them to mitigate risks. Similarly, flood exposed populations in Canada or Japan are more likely to have access to rapid government support systems in post-disaster situations compared to people in Malawi or Bangladesh. Thus, action to strengthen disaster prevention and recovery capacity is most urgently needed in the hotspots where poverty and flood exposure coincide. References Braese, J., S. De Vries Robbe, J. Rentschler, Jun. (2020). Coastal Development between Opportunity and Disaster Risk: A Multisectoral Risk Assessment for Vietnam. Policy Research Working Paper; No. 9352. World Bank, Washington Bright, E. A., Rose, A. N. & Urban, M. L. _Landscan 2015 High-Resolution Global Population Data Set_ . (Oak Ridge National Laboratory (ORNL), Oak Ridge, TN,

Landscan 2015 High-Resolution Global Population Data Set

Oak Ridge National Laboratory (ORNL)
World Bank

Landscan 2015 High-Resolution Global Population Data Set

Landscan 2015 High-Resolution Global Population Data Set


Input: The Digital Technology Adoption Survey (DTAS) conducted by Tech Innovations Inc. provides crucial insights into the technology usage patterns among small and medium enterprises (SMEs) in Southeast Asia. This dataset, collected in 2022, is vital for understanding the barriers and facilitators of digital transformation in this region.

digital development and technology adoption


Input: The Food Security Assessment Report 2022 provides critical insights into the agricultural trends in Sub-Saharan Africa. This report, published by the International Food Policy Research Institute (IFPRI), highlights the increasing challenges faced by farmers in the region due to climate change and economic instability.

International Food Policy Research Institute

International Food Policy Research Institute

International Food Policy Research Institute

agriculture, food security, and nutrition


Input: The Food Security Assessment Report 2022, published by the Global Agriculture Initiative, provides extensive insights into rural nutrition levels across several countries. This dataset has been instrumental for various organizations, including the International Food Policy Research Institute (IFPRI), which utilized the findings to support their analysis of agricultural policies in the region. Additionally, the report highlights trends in food access during the 2020–2022 period, shedding light on the challenges faced in countries like Mozambique and Ethiopia. Overall, this collaborative effort underscores the importance of reliable data in shaping effective food security strategies.

Food Security Assessment Report 2022
Food Security Assessment Report

International Food Policy Research Institute

International Food Policy Research Institute

International Food Policy Research Institute


Input: The 2022 Global Refugee Status Report (GRSR) provides comprehensive insights into the patterns of forced displacement across various countries. Published by the International Organization for Migration (IOM), this report covers data from 2010 to 2022, emphasizing trends and challenges faced by refugees in regions like the Middle East and North Africa. While the report is utilized by numerous NGOs for advocacy and policy development, it is essential to approach its findings critically, recognizing the limitations of data collection in conflict zones. The GRSR serves as a vital resource for understanding the evolving landscape of migration and displacement amid ongoing global challenges.

International Organization for Migration

International Organization for Migration


Input: The Regional Learning Achievement Survey (RLAS) conducted in 2022 provides critical insights into student performance metrics across Southeast Asia. Designed to assess learning outcomes in mathematics and reading, the survey data is pivotal for educational policy reforms in the region. Meanwhile, the National Enrollment Data (NED) for 2021 highlights trends in school enrollment rates across various countries, emphasizing the disparities in access to education. Both datasets serve as valuable resources for researchers and policymakers alike, although they differ in their geographical scope and objectives. Source: elaboration based on RLAS and NED datasets.

Regional Learning Achievement Survey
National Enrollment Data

education, learning achievement, and school enrollment


Input: The recent analysis of urban expansion in Southeast Asia heavily relies on data from the Land Use Change Assessment Report 2022 (LUCA 2022). This comprehensive dataset provides insights into land cover changes across various regions, particularly in countries like Vietnam and Thailand. Researchers at the Asian Development Bank have utilized this valuable resource to evaluate the impacts of rapid urbanization on environmental sustainability. The LUCA 2022 dataset not only covers the year 2022 but also includes historical data spanning back to 2010, facilitating a deeper understanding of long-term trends in land use.

geospatial analysis, remote sensing, and land use mapping


Input: The Climate Change Adaptation Report 2022 (CCAR) provides vital insights into the impact of climate change on agricultural practices across various regions. This report, published by the Global Environmental Agency, highlights adaptation strategies utilized in Africa during the period 2015–2022. Furthermore, the Biodiversity Assessment Database 2021 (BAD) aggregates comprehensive data on species distribution and ecosystem health, with a particular focus on Southeast Asia. This database serves as a crucial tool for researchers and policymakers working towards sustainable development in the region.

Climate Change Adaptation Report 2022
Biodiversity Assessment Database 2021


Input: The 2022 Energy Access Report, published by the Global Energy Agency, provides critical insights into the progress made in expanding electricity access in developing nations. This comprehensive report analyzes data collected from various regions and highlights the challenges that persist in achieving universal energy access.


Input:
treatment distance of 50 km, we no longer see a significant effect. In panel Ab, the results are

replicated using a spatial lag model, meaning that we allow for nonlinear effects with distance.

In reality, it seems like the electricity rate is much higher before a mine (dashed line) than with

an active mine (the blue line). However, when the results are decomposed by migrant status in

panel Ac of figure A1 (Annex) we find that migrants are driving the lower electricity rate. In

fact, among nonmigrants, the electricity rate is higher 0–10 km from an active mine, although

it is slightly lower 10–20 km away. [14]

**6.3 Distributional effects on wealth and inequality**

Table 9 presents the effects of mining on asset wealth and on asset wealth inequality. Wealth

data are available in the form of a wealth index, but only for the two last DHS surveys.

Following Fenske (2015) and Flatø and Kotsadam (2014), we calculate inequality by means of

a Gini coefficient (recoding the wealth variable to be positive only, and using the command

13 It is also possible that mining companies compete with households for electricity if supply cannot be increased
in the short run.

---
[14] In panels Ba, Bb, and Bc of Appendix figure A1, we analyze access to radio. We learn that access to

Fenske (2015) and Flatø and Kotsadam (2014)

Fenske (2015) and Flatø and Kotsadam (2014)


Input: The Urban Mobility Assessment Report 2022, published by the Transport Research Agency, provides critical insights into transportation usage patterns across urban areas. In particular, the report has been invaluable for city planners in Jakarta, who have leveraged its findings to improve public transport systems and reduce congestion. The agency also produced the Infrastructure Development Index (IDI), which tracks nationwide infrastructure conditions over a ten-year period from 2015 to 2025. This index has been instrumental for the Indonesian Ministry of Transportation as they formulate strategic initiatives to enhance connectivity throughout the country. Furthermore, the Global Urban Survey (GUS) released by the International Urban Development Institute (IUDI) in 2021, highlights key challenges faced by urban environments worldwide. Local governments have cited the GUS data to advocate for sustainable urban development policies.

Urban Mobility Assessment Report 2022
Infrastructure Development Index
Global Urban Survey

International Urban Development Institute

International Urban Development Institute

urban infrastructure and transportation planning


Input: The recent study on urban household water access in Sub-Saharan Africa utilized the Urban Water Access Assessment Report 2022 conducted by the Global Water Institute. This dataset, which provides a comprehensive view of water availability, was then cited by UNICEF in their ongoing efforts to improve sanitation conditions in the region. Furthermore, the analysis draws on the results from the Hygiene Practices Survey (HPS) published by WaterAid, which covers data from 2021. This survey has been instrumental in shaping the hygiene education programs implemented in countries like Kenya and Ghana.

Urban Water Access Assessment Report 2022

Urban Water Access Assessment Report 2022

Urban Water Access Assessment Report 2022

Urban Water Access Assessment Report 2022

Urban Water Access Assessment Report 2022


Input: The recently published Food Security Assessment Report 2022 by the Global Agriculture Organization provides vital insights into agricultural productivity and food access across various regions. This dataset, which covers the year 2022, is utilized by several NGOs, including Food Aid International, to analyze the impact of food shortages in Sub-Saharan Africa. In addition, the Agricultural Trends Database (ATD), created by the International Food Institute, offers comprehensive data on crop yields and is frequently referenced in studies conducted by regional agricultural ministries throughout the 2019–2023 period.

Food Security Assessment Report 2022
Agricultural Trends Database

Global Agriculture Organization
Food Aid International
International Food Institute


Input: The recent findings on gender disparities in the labor market highlight the importance of comprehensive data sources. The report from the Gender Equality Assessment provides crucial insights into the challenges women face in achieving economic empowerment. Understanding these dynamics is essential for policymakers aiming to create effective interventions to support women in the workforce.


Input: The recent Agricultural Baseline Survey 2023 has provided valuable insights into rural practices and food security challenges faced by farmers in Ethiopia. This dataset, published by the Food and Agriculture Organization (FAO), is essential for understanding the current agricultural landscape and informing policy decisions.


Input: The Global Land Use Mapping Database (GLUMD) provides essential insights for geospatial analysis and remote sensing applications. Published by the GeoSpatial Research Institute, the database offers comprehensive data that assists policymakers in making informed decisions about land use and environmental management.


Input: The descriptive characteristics of foreign-born and host community households are still comparable, and therefore allow for comparisons between 2013 and 2014. It is possible to make some inferences on welfare changes by looking at changes in host community employment rates and labor market characteristics. Overall, this paper finds no negative effects on host community welfare from an increasing population of SUTPs. As other authors have stated, the influx of SUTPs has had both positive and negative impacts. It seems on average, the host community has been strong and adaptive, and not negatively impacted. This is not to disregard that real strains do exist in some regions where the SUTP population is very large. Nor do these results undermine findings of displacement effects in the labor market that certain types of workers are experiencing. However, on average nationally, we do not see a systematic decline in the welfare of the host community between 2011 and 2013. The remainder of the paper is organized as follows. Section 2 outlines the data availability and technical issues. Section 3 discusses descriptive statistics of the foreign-born and host community. Section 4 explores the impact of the foreign-born population on host community welfare. 1. DATA AND TECHNICAL ISSUES Data Sets Data availability limits which data set can be used to identify the foreign-born population and geographic location while measuring poverty. The Turkish Statistical Institute (TUIK) has been conducting three nationally representative surveys annually since 2005; the Household Income and Consumption Expenditure Survey (HICES), the Survey on Income and Living Conditions (SILC) and the Labor Force Survey (LFS). However the HICES, which is the national survey that is used to measure official poverty, 5 UNCHR, 2013pg 13 6 UNHCR (22 November 2013), UNHCR (15 September 2014) 7 UNHCR (22 March 2013), Erdogan (2014), pg 14 8 This technical issue will be discussed further later in the paper.


Input: The Water Quality Assessment Report 2022 provides critical insights into the levels of contaminants found in drinking water across various regions. This report, produced by the Global Water Institute, serves as a key resource for policymakers and health officials aiming to ensure safe drinking water standards.


Input:
future year by the counterpart observation in the CRU benchmark dataset (from the most

representative temperature/rainfall combination, derived from CRU data for 1980-2000).

departure: the benchmark series from the CRU data. This translation step is necessary


Input: Hosts Refugees Eritrean Somali South Sudanese Figure D.24: Household owns livestock Source: World Bank Staff based on SESRE 2023. 0 0.1 0.2 0.3 0.4 0.5 0.6 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.23: Household owns crops Source: World Bank Staff based on SESRE 2023. 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.25: Total value of livestock Source: World Bank Staff based on SESRE 2023. 0 5,000 10,000 15,000 20,000 25,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.26: Value per tropical livestock unit Source: World Bank Staff based on SESRE 2023. 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.27: Household has non-farm business Source: World Bank Staff based on SESRE 2023. Annexes 110 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.28: Value of productive assets in households with business Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 Percent 70 80 90 100 Hosts Refugees Hosts Refugees


Input: Furthermore, in some contexts, registration as an IDP can expire after a prescribed timeframe without regard to whether the person achieved a durable solution (e. g. after five years in Russia). The accuracy of IDP registers is greatly impacted by political considerations, particularly a government ’ s willingness to acknowledge internal displacement and to enable the humanitarian community to respond. Some countries may be reluctant to acknowledge the presence of IDPs, or may be inclined to understate numbers to demonstrate progress in military operations or limit assistance provided to IDPs. For example, in Kenya, registration of individuals displaced by the 2007 and 2008 post-election violence excluded ‘ integrated ’ IDPs, i. e. those who had sought refuge with host communities or rented accommodation in urban areas, as assistance was limited to registered IDPs. Alternatively, aggregate numbers of IDPs in particular countries may be inflated to suggest a deterioration of the situation or to maximize humanitarian assistance. Therefore, access to IDP areas and the willingness of IDPs to be counted may be largely dependent on government policies. These political considerations can lead to disagreements on the data, undermine cooperation and in some cases even lead to reduced humanitarian funding. Profiling of IDP situations Profiling of IDP situations is a collaborative process aimed at generating reliable data that can be broadly agreed upon. As a collaborative process, it can be a crucial tool for generating agreement on persistent questions such as who is recognized as internally displaced within a given context, what are the most prevalent vulnerabilities caused by displacement, and how do IDPs fare compared to host populations. In sought refuge with host communities or rented accommodation in urban areas, as assistance was limited to registered IDPs. 68 However, in many conflict-affected countries, governments lack the basic capacity to maintain Civil Registration and Vital Statistics (CRVS) systems including the registration of births and deaths in non-displacement situations, let alone the registration of IDPs displaced due to natural disasters or conflict. 69 IOM has introduced biometric registration systems in South Sudan, Sudan, DRC and Nigeria to circumvent these problems.


Input: 15 resulting in government forces recapturing rebel held territory, establishment of a rebel base or headquarters, rebel activity that is not battle related (e. g. presence or the killing of civilians), and territorial transfers. The dataset consists of 4, 145 battle events for the 1960 – 2004 period. In the present analysis, we use 2, 530 of these. The remaining events were dropped as they either were in countries not included in the analysis, or because information was missing for one of the key variables. Each conflict event is associated with geographic coordinates and a date of occurrence. This information allows for spatial and temporal modeling of conflict events. The dataset used in this article covers 14 countries in Central Africa. 6 of them had a conflict in the 1960 – 2004 period according to the Uppsala / PRIO Armed Conflict Dataset (Gleditsch et al., 2002): Angola, Burundi, Republic of Congo (Brazzaville), Democratic Republic of Congo (Zaire), Rwanda, and Uganda.


Input: The Digital Connectivity Assessment (DCA) provides insights into internet usage patterns across various demographics. Conducted by the Global Tech Foundation in 2022, this assessment highlights the disparities in digital access within different regions, particularly in Sub-Saharan Africa. The findings underscore the pressing need for targeted policies to enhance connectivity in underserved areas. The DCA is especially relevant as governments and organizations seek to leverage technology for development, assisting in the formulation of initiatives aimed at bridging the digital divide.


Input: The Climate Resilience Assessment Report 2022, published by the Global Environmental Institute (GEI), provides critical insights into regional vulnerabilities and adaptive capacities across various nations. In this report, the data focuses on South Asia, specifically highlighting the importance of addressing climate risks in Bangladesh. Meanwhile, the data from the Emergency Preparedness Survey (EPS) conducted by the International Disaster Management Organization (IDMO) is utilized by various stakeholders, including local governments and NGOs to develop comprehensive disaster response strategies. The EPS data, covering the period from 2019 to 2021, has proved invaluable for enhancing community resilience in affected areas.

Climate Resilience Assessment Report 2022

International Disaster Management Organization

Climate Resilience Assessment Report 2022

Climate Resilience Assessment Report 2022

Climate Resilience Assessment Report 2022

Climate Resilience Assessment Report 2022

International Disaster Management Organization


Input: The 2020 National Fertility and Demographic Assessment Report (NFDA 2020) provides comprehensive insights into fertility trends across various regions in the country. Conducted by the National Institute of Population Studies, the report analyzes data collected from urban and rural areas, highlighting significant disparities in fertility rates. While the report emphasizes the need for targeted policy interventions, it is also cited by various NGOs working in the field of reproductive health. The NFDA 2020 underscores how demographic changes can influence economic development over the coming years.

2020 National Fertility and Demographic Assessment Report

National Institute of Population Studies

2020 National Fertility and Demographic Assessment Report

2020 National Fertility and Demographic Assessment Report

2020 National Fertility and Demographic Assessment Report

demographics, fertility, and population growth


Input:
**The World Bank**
Balochistan Human Capital Investment Project (P166308)

(FMS), and an environmental and social safeguards specialist/officer. [47] The PMUs will be fully authorized
to implement the planned activities approved by the Project Steering Committee (PSC).

46. **A Project Coordination Committee (PCC) will be set up to coordinate project implementation**

**and a PSC will be set up to provide strategic guidance and oversight.** The PCC, co‐chaired by Secretaries
Health and Secondary Education, will meet quarterly. The PSC, chaired by the Additional Chief Secretary,
will meet biannually (see figure 2).

**Figure 2. Institutional and Implementation Arrangements**

**B. Results Monitoring and Evaluation Arrangements**

47. **Building on the results chain, the M&E framework identified indicators to track project**

**implementation progress and impact.** The PDO‐level health indicators are taken from the RMNCHN
indicators in the DHIS, while digitization and integration of various HMIS is an intermediate indicator. The
education indicators are taken from the EMIS. Where possible, relevant indicators will be disaggregated
by gender. Discussions with the GoB and the UNHCR have confirmed, however, that beneficiary data by
nationality will not be routinely collected or publicly released.

48. **The project M&E will leverage and strengthen existing routine information systems, and finance**

---
[47] During the early phase of implementation, the Governance and Policy Program (GPP) PMU will provide back‐up support.


Input: GoR has progressive laws and policies on forced displacement.** The World Bank, in consultation with the United Nations High Commissioner for Refugees (UNHCR), has confirmed that Rwanda’s refugee protection framework is adequate for the purposes of access to the Window for Host Communities and Refugees (WHR). [5] Rwanda is a signatory to the 1951 Refugee Convention and the Global Compact on Refugees (GCR). The 2014 _Law_ _Relating to Refugees_ complies with international law and entrenches the right to work and freedom of movement. At the policy level, Rwanda’s _Strategic Plan for Refugee Inclusion 2019-2024_ made commitments to: (a) provide all [1 Data is from April 30, 2025. There are also 14,936 asylum-seekers in Rwanda: see https://data.unhcr.org/en/country/rwa](https://data.unhcr.org/en/country/rwa) [2 Loschmann, C., Bilgili, O. & Siegel, M. (2019) “Considering the benefits of hosting refugees: evidence of refugee camps influencing local labour](https://link.springer.com/article/10.1186/s40176-018-0138-2) [market activity and economic welfare in Rwanda,” IZA Journal of Development & Migration, pp. 1-23.](https://link.springer.com/article/10.1186/s40176-018-0138-2) 3 The self-reliance survey is part of the “Enhancing Self-Reliance and Preparedness for Forced Displacement in the Great Lakes Region” activity [(P500793) and draws on the global Refugee Self-Reliance Initiative index (www.refugeeselfreliance.org).](http://www.refugeeselfreliance.org/) 4 Phase I of Jya Mbere was approved on April 30, 2019, and will close

global Refugee Self-Reliance Initiative index

United Nations High Commissioner for Refugees (UNHCR)

global Refugee Self-Reliance Initiative index

United Nations High Commissioner for Refugees (UNHCR)

global Refugee Self-Reliance Initiative index


Input:
Therefore, in addition we adopted another adapted calculation method which is based on travel paths simulations using OD pairs from the JICA travel survey.

The conventional approach calculates shortest paths between every possible pair of nodes within the network whereas the adapted approach simulates the travel trajectories based on the multimodal transportation model and accounts for public transport waiting times, road speed limits, and designated origin and destination pairs acquired from the JICA commuter travel survey.

**Acknowledgments:** We would like to thank GoMetro for leading the public transport mapping, and in
particular Bob Kabeya and Clayton Lane, as well as the enumerators that conducted these surveys. We thank
Shohei Nakamura, Takaaki Masaki and Mervy Ever Viboudoulou Vilpoux for their help in accessing
Kinshasa commuter and household surveys. We are grateful to Laurent Corroyer, Stephane Hallegatte and
Kirsten Homman for their inputs and feedback throughout this project. We are also grateful to Catalina
Ochoa for her review of an earlier draft of this paper and her thoughtful comments. This study was supported
by the Global Facility for Disaster Risk Reduction and Recovery (GFDRR).

These data sets were combined with travel survey data containing travelers' socioeconomic attributes and trip parameters, as well as a high-resolution flood maps.


Input:
**Electricity** **Capital** **GDP** **Consumption** **Stock** **Population** Median 3.84 3.65 3.45 1.44 Average 3.48 4.10 3.88 1.43 Standard Deviation 4.37 6.87 2.77 0.97 Skewness -1.58 1.56 0.81 0.11 Kurtosis 9.83 20.48 1.10 -0.33 _Sources: World Development Indicators, Penn World Tables Version 8, and author's calculations._

<!-- PAGE 19 -->
#### **VII. Hypothesis Testing**

We explore two basic questions. First, could night-time lights data serve as a good proxy for any of the
economic variables considered in this paper?

A new satellite is generating superior night-time lights data. The data are generated by the Suomi National Polar-orbiting Partnership (SNPP) satellite series operated by the NASA - NOAA Joint Polar Satellite System that was launched in late 2011.

observed in cross-section surveys - even when controlling for other observable characteristics -   cannot directly be interpreted as reflecting a change in attitudes over the life-cycle.


Input:
Night-time lights data are a beneficial by-product of a meteorological satellite program. The data are
collected by the United States Air Force Defense Meteorological Satellite Program (DMSP). DMSP
satellites have been circling the earth since the 1970s in a polar orbit that allows observations of every

1. Number of illuminated pixels with _DN_ >=6 within the borders of a country.
2. Average _DN_ within all illuminated pixels.
_Sources:_ NGDC v4, World Development Indicators for land area, and author's calculations.

Long-run patterns in _AoL_ and _R_ are consistent with some country circumstances. For example, as shown
in Table 1, a country with a rapidly expanding _AoL_ is more likely to be a country with a high urban
population growth rate. China, Indonesia, Malaysia, Vietnam, and Yemen are examples. A country with
shrinking _AoL_ could be in the early, painful stages of transition from a planned economy to a market
economy. Azerbaijan, Tajikistan and Ukraine are examples. Countries with growing average radiance, _R_,

Souknilanh et al (2015) find their night-light based _GDP_ estimates are improved when supplemented by ground cover data from a second satellite (MODIS).

16 Normally there is a quasi-fixed ratio of intermediates to gross output which slowly falls as productivity improves. Countries that import most of their intermediates will be subject to external shocks (trading partner demand, terms of trade) that disrupt this relationship. 17 From a sample of 166 countries in 2010, from the World Development Indicators.

[26] The result is the v.4 DMSP stable lights data set with between 20 and 100 observations per year per pixel depending upon circumstances (Baugh et al.

Defense Meteorological Satellite Program

Defense Meteorological Satellite Program


Input: The recent report on global forced displacement highlights findings from the Refugee Assessment Survey (RAS) conducted by the International Organization for Migration (IOM) in 2022. The data from this assessment indicates significant trends in migration patterns, which were further analyzed by the United Nations High Commissioner for Refugees (UNHCR). Additional insights were drawn from the Forced Migration Data Set (FMDS) published by the World Bank in 2021, showcasing the economic impact of refugee movements across various regions. Moreover, the FMDS has been employed by multiple non-governmental organizations (NGOs) to inform their policies and responses to the refugee crisis in sub-Saharan Africa.

Refugee Assessment Survey
Forced Migration Data Set

International Organization for Migration

United Nations High Commissioner for Refugees

International Organization for Migration

United Nations High Commissioner for Refugees


Input: The Domestic Revenue Mobilization Survey (DRMS) conducted in 2022 provides critical insights into revenue collection practices across various nations. This survey, which covers data from over 30 developing countries, is designed to assist policymakers in improving fiscal transparency and efficiency. Source: World Bank elaboration based on the DRMS. The findings highlight significant regional variations, particularly in Africa and Southeast Asia, and underscore the need for tailored strategies to enhance tax compliance in these regions.

public financial management and domestic revenue


Input:
## Secondary Data Review
# GENDER-BASED VIOLENCE – Mozambique: Cyclone Idai and Floods

APRIL 2019 difficult to access. As a result of the cyclone and floods, people in remote affected areas face challenges accessing district hospitals.

To ensure a private and protective environment, there is a need to refurbish the maternity wards, where the survivors are treated. Further, the administrative offices of the Women and Children’s Protection desk need to be rehabilitated, so a private and protective environment can be restored for women and girls to report confidentially.

**HIV:** It is estimated that almost 1.6 million people, including more than 90,000 children,
are infected with HIV in Mozambique. More than half of those infected are women, and
[15% of pregnant women aged 15–49 are HIV-positive (ODI, 2014). The prevalence rate](https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/9073.pdf) of HIV in the population aged 15-49 is 13.2% (15.4% in women and 10.1% in men).
Sofala has a higher rate (16.3%) than other affected districts [(DHS, 2015). Furthermore,](https://www.dhsprogram.com/pubs/pdf/AIS12/AIS12_SP.pdf) women and girls are particularly affected by the epidemic because they usually lack the
[power to refuse unsafe sex, choose their partners or influence sexual behavior (ODI 2014).](https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/9073.pdf)

**Sexual and Reproductive Health:** According to the latest estimation, about 438,000
women affected by the cyclone are of reproductive age (15-49). Among those, 64,000 women are estimated to be pregnant and more than 37,000 women in affected areas are estimated to give birth in the next three months. Among those giving birth, up to 9,600 may be at risk of complications during their pregnancy in the next three months.
They will they will need access to functioning health facilities and care (UNFPA, 4/2019).

**Shelter:** According to the Demographic Health Survey some 28% of people in Sofala did
not have electricity. A further 28.9% of people lived in a cement house, 36.9% in an earthen mud-house [(DHS, 2015).](https://www.dhsprogram.com/pubs/pdf/AIS12/AIS12_SP.pdf) According to the latest DTM there are currently over 13,600 people hosted in 24
[displacement sites in Beira (DTM R2, 4/2019). This includes five planned sites, the remainder](https://displacement.iom.int/reports/moçambique-—-ciclone-tropical-idai-inquérito-dos-locais-de-deslocamento-beira-dondo-e) are temporary transit sites including schools and public buildings. Site plans of the five accommodation centers suggest that currently up to 5–6 families are sharing one tent,
[and averagely 12m2 space is available per person (calculated based on CCCM site plans](https://www.humanitarianresponse.info/en/operations/mozambique/infographic/temporary-relocation-sites-layout) and
[DTM Round 2, 4/2019). The SPHERE standards prescribe a minimum of 30m2 for camp-like](https://displacement.iom.int/reports/moçambique-—-ciclone-tropical-idai-inquérito-dos-locais-de-deslocamento-beira-dondo-e) settlements. Overcrowding and inadequate privacy for women and girls are observed, which is a risk to GBV.
While the site plans are designed to follow minimum standards and provide suitable living conditions, many elements have contributed to increased vulnerabilities and overstretched capacity on site: ad-hoc relocation plans, lack of sensitization among surrounding communities, lack of communication to the population, and a lack of systematic allocation of tents (Protection Monitoring, 4/2019). It is also reported that more than half of the sites do not have adequate lighting in any common place; which is considered a major risk to GBV and can hamper the freedom of movement of women and girls [(DTM](https://displacement.iom.int/reports/moçambique-—-ciclone-tropical-idai-inquérito-dos-locais-de-deslocamento-beira-dondo-e)
[R2, 4/2019). The MRA in Dondo district shows that in more than half surveyed locations,](https://displacement.iom.int/reports/moçambique-—-ciclone-tropical-idai-inquérito-dos-locais-de-deslocamento-beira-dondo-e) people have been sleeping in open areas. In Buzi all but one location there were surveyed families who reported they were sleeping outside (MRA, 4/2019). Sleeping out in the open is unsafe and can increase the risk of GBV to women and girls.

**Documentation:** The affected population have lost most or all of their documents during
the cyclone. This include identity documentation and other vital certificates. An estimated 19% of people in Sofala already did not have birth certificates or registration in 2015
[(DHS 2015). The lack of mechanisms to facilitate attainment of these documents is likely to](https://dhsprogram.com/pubs/pdf/AIS12/AIS12.pdf) hinder access to services, including enrolment in schools and engagement in some livelihood activities (Protection cluster, 4/2019). A lack of basic needs, or possibility to engage in livelihood activities, will lead to faster depletion of coping mechanisms of the affected population. This means that negative coping mechanisms including those that pose a higher risk to GBV will be adopted faster. A lack of engagement in school for children also increases the risk of child labor and exploitation.

**Eviction** : Assessments in the displacement sites suggested that 11 (3 in Nhamatanga
[district and 8 in Beira district) out of 41 sites reported there is an eviction threat (DTM R2,](https://displacement.iom.int/reports/moçambique-—-ciclone-tropical-idai-inquérito-dos-locais-de-deslocamento-beira-dondo-e)
[4/2019). However the answer is perception-based and it is likely to indicate the lack of](https://displacement.iom.int/reports/moçambique-—-ciclone-tropical-idai-inquérito-dos-locais-de-deslocamento-beira-dondo-e) communication and sensitization to the displaced population. In multiple reports the importance for communities to get timely and clear information on relocation processes is emphasized (Protection cluster, 4/2019).

**Child Protection:** Over 28% of households in Mozambique have adopted children [(DHS](https://dhsprogram.com/pubs/pdf/AIS12/AIS12.pdf)
[2015).](https://dhsprogram.com/pubs/pdf/AIS12/AIS12.pdf) Almost 50% of young Mozambican women aged 20-24 years were married
[before the age of 18, while 14% were married before the age of 15 (CARE, 3/2019).](https://reliefweb.int/sites/reliefweb.int/files/resources/Regional-RGA-Cyclone-Idai-29032019.pdf) According to MRA in Dondo, among children under 14 years old, a total of 22.3% were orphan by father (13.2%), by mother (6%) or both parents (3%). The assessment further showed that in six affected districts, helping out the family by doing chores and other work are among the main reason children (both boys and girls) are not attending schools.
In about 10% of locations assessed, communities reported that they have noticed there are children disappearing (or being trafficked). In almost 40% of assessed locations communities reported having come across children who are forced to work to provide 5


Input: The Fertility and Population Growth Survey (FPGS), conducted in 2020, provides critical insights into demographic trends across various regions. This dataset, produced by the National Institute of Statistics, highlights key fertility indicators for countries such as Nigeria and Kenya. Notably, the FPGS has been instrumental in regional studies on population dynamics, often cited in research by organizations like UNICEF. Additionally, the 2021 Demographic Survey Assessment (DSA) focuses specifically on urban and rural population changes, covering data from all provinces of Mozambique. The DSA serves as a vital resource for policymakers and researchers, contributing to the understanding of demographic shifts during this period.

Fertility and Population Growth Survey
Demographic Survey Assessment


Input: The Urban Mobility Assessment Report 2022, published by the International Transportation Institute (ITI), provides critical insights into urban traffic patterns in major cities. This dataset is widely used by the Metropolitan Planning Organizations (MPOs) to inform their transportation strategies and improve infrastructure. The analysis presented in the report highlights trends from 2018 to 2022, emphasizing the growing need for sustainable urban transit solutions. Additionally, the Global Urban Infrastructure Database (GUIDE), maintained by the World Research Council, is another crucial resource utilized by city planners across several countries, including Brazil and Kenya, to analyze urban development metrics.

Urban Mobility Assessment Report 2022
Global Urban Infrastructure Database

International Transportation Institute
Metropolitan Planning Organizations
World Research Council


Input: The recent analysis of financial inclusion trends in Southeast Asia has leveraged data from the Southeast Asia Economic Monitoring Report 2022, published by the Asian Development Bank (ADB). This comprehensive report highlights critical indicators of economic performance and access to financial services across the region. Additionally, the World Bank has utilized the Financial Access Survey (FAS) data, which covers the years 2018-2021, to examine the correlation between economic growth and financial inclusion in countries like Indonesia and Thailand. Furthermore, the 2023 Microfinance Sector Assessment Report, produced by the International Finance Corporation (IFC), offers insights into the microfinance landscape, which has been cited by several NGOs working on poverty alleviation initiatives in the region.

Southeast Asia Economic Monitoring Report 2022

2023 Microfinance Sector Assessment Report

Asian Development Bank
World Bank
International Finance Corporation
NGOs

Southeast Asia Economic Monitoring Report 2022

Southeast Asia Economic Monitoring Report 2022

2023 Microfinance Sector Assessment Report

2023 Microfinance Sector Assessment Report

2023 Microfinance Sector Assessment Report

2023 Microfinance Sector Assessment Report

2023 Microfinance Sector Assessment Report


Input: The Education Access Survey (EAS) conducted by the Ministry of Education in 2022 provides critical insights into school enrollment patterns across the country. This dataset highlights significant trends in learning achievement among various demographics, informing policy decisions and resource allocation for future educational programs.