Abstract

To ensure the centrality of refugees’ voices in discussions about their future, as well as to inform evidence-based inter-agency responses in support of host Governments, UNHCR is leading the regular implementation of intentions surveys with refugees from Ukraine, collecting primary data on their profiles, their current situation and intentions, and the factors influencing their decision-making.

The first, second and third regional intentions surveys were completed and the reports published in July 2022 (https://data.unhcr.org/en/documents/details/94176), September 2022 (https://data.unhcr.org/en/documents/details/95767) and February 2023 (https://data.unhcr.org/en/documents/details/99072). This data was collected during the fourth round, conducted between April and May 2023. The survey covered refugees hosted in countries in Europe.

A mixed methodological approach was used, combining two data collection modes. Around 3,850 refugee households were interviewed either through a phone-based survey, web-based survey or face-to-face interview. The data include a mix of Fresh refugee households (i.e. not included in previous rounds) and Panel households (i.e. those included in at least one of the previous rounds). All surveys used a harmonized questionnaire.

This data is an anonymous version of the original data collected and used for the primary analysis.

Geographic coverage

Europe

Analysis unit

Households

Universe

Refugees from Ukraine

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample includes households and individuals who completed this round as well as previous rounds (two and/or three) of the study (sample_type='Panel') and those who only participated in this round (sample_type = 'Fresh'). See more details in the report.

Mode of data collection

Other [oth]

Abstract

The 2023 Multi-Sector Needs Assessment (MSNA) in Slovakia presents findings from a regional interagency multi-sectoral assessment conducted with Ukrainian refugees in Slovakia from July to August 2023. The assessment, carried out by SHC and IOM, aimed to capture the needs of and access to basic services for refugees, identify service gaps, and understand refugees' priorities for the coming year to inform response planning. Using a structured questionnaire, the assessment surveyed purposively selected households of refugees from Ukraine, stratified by geographic area and accommodation type. Key topics included health, protection, food security, education, livelihoods, gender-based violence, mental health, cash assistance, and legal needs. As a key source of information for response planning, the 2023 MSNA provides insights into the experiences and priority needs of Ukrainian refugees in Slovakia.

Geographic coverage

Country

Analysis unit

Household

Universe

Households fleeing Ukraine: The assessment aimed to evaluate the profiles and urgent needs of these households as part of a regional exercise for the Ukraine Situation.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2023 Multi-Sector Needs Assessment (MSNA) in Slovakia utilized a simple random sampling method to survey 1,000 households (comprising both private accommodations and collective sites). 80% of the sample was drawn from households in private accommodations, and 20% from collective sites. The sample was stratified by geographic area and accommodation type, using data from the cash registration database and considering district-level refugee population density. This approach ensures that each household had an equal probability of selection, providing representative results of the refugee population's needs across Slovakia.

Mode of data collection

Face-to-face [f2f]

Research instrument

Income, food consumption, expenditures, assets, community relations, wellbeing, resilience, mental health, health, accommodation, protection, and education

Abstract

Starting in February 2022, an increasing number of refugees and third-country nationals (TCNs) entering Poland was registered as a result of the war in Ukraine. As of July 2022, over 4.3 million arrivals have been reported by the Polish authorities from Ukraine. To ensure that reponse actors have the necessary evidence base to effectively respond to the needs of Ukrainian refugee households in Poland, UNHCR and REACH carried out this joint Multi-Sectoral Needs Assessment (MSNA) targeting the population displaced due to the war in Ukraine and currently residing in Poland. Due to lack of complete data on location and profile of refugees residing in Poland, PESEL registration data (the national identification number used in Poland) was used as a proxy indicator for sampling for non-probability quota sampling for refugees residing in the host community. The sample includea two distinct population groups: refugees living in host community, outside of the collective sites (CSs), and refugees residing in CSs. Refugees living outside of CSs cover a variety of accommodation types, including private accommodation, being hosted by family, friends, or by Polish families, among others. This dataset is the anonymous version of the original dataset.

Geographic coverage

All voivodeship in Poland

Analysis unit

Households

Universe

tbc

Kind of data

Sample survey data [ssd]

Sampling procedure

Two approaches have been taken: a non-probability quota sampling for refugees residing in host community; and purposive sampling for refugees in collective sites.

Mode of data collection

Face-to-face [f2f]

Abstract

It is increasingly recognised that the majority of the world's refugees reside not in camps, but dispersed amongst the community in the countries where they have sought asylum. This is the case for Syrian refugees in Jordan, of which 84% live outside official refugee camps in urban and rural areas across the country. Understanding the needs, vulnerabilities and capacities of this dispersed refugee population is vital to ensuring their protection and access to services. The purpose of this dataset is to examine the situation of Syrian refugees living outside camps in Jordan, based on data collected through UNHCR's Home Visits programme. Under this programme, interviews are conducted with every refugee household registering with UNHCR outside camps. This provides an unparalleled source of information about the situation of Syrian refugees in non-camp settings.

Geographic coverage

Urban areas at National Coverage

Analysis unit

Household and individual

Kind of data

Sample survey data [ssd]

Sampling procedure

This study is not based on random sampling. The Home Visits survey is an ongoing assessment which aims to interview every refugee household registered with UNHCR outside camps. The survey went through many different versions which included major changes in variables and sections content, for this reason it is not possible to fully compare the different versions with each other. Whenever possible, though, the various dataset versions have been harmonized so that variables containing the same kind of information were renamed with the same name. You can see all the versions available in the Microdata Library in the “Related studies” tab.

Mode of data collection

Face-to-face [f2f]

Abstract

The socio-economic desk score dataset includes the socio-economic scores of the households that have taken the 2020 Vulnerability Assessment of Syrian Refugees (VASyR) assessment. The desk score is a Proxy Means Test (PMT) score, available for all population, that predicts the economic vulnerability of households. The dataset includes the desk scores of the case numbers since 2016. In Lebanon, the desk score is revised annually and used by Lebanon Crisis Response Plan (LCRP) cash actors for the identification and selection of beneficiaries for multi-purpose cash assistance.

Geographic coverage

National coverage

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

This dataset includes the socio economic score history of all the households that have taken the 2020 Vulnerability Assessment of Syrian Refugees (VASyR 2020) assessment, available on the UNHCR Microdata Library (survey ID number: UNHCR_LBN_2020_VASYR_v2.1). It is possible to link each score record to the VASyR 2020 dataset using the case number provided.

For more info about the VASyR 2020 sampling please refer to the dataset page: https://microdata.unhcr.org/index.php/catalog/286

Mode of data collection

Other [oth]

Abstract

The assistance dataset includes the assistance history of the households that have taken the 2020 Vulnerability Assessment of Syrian Refugees (VASyR) assessment. The dataset is extracted from Refugees Assistance Information System (RAIS) which is an online Inter-Agency web application used by Lebanon Crisis Response Plan (LCRP) partners in Lebanon for tracking and reporting assistance provided to persons of concern to UNHCR.

Geographic coverage

National coverage

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

This dataset includes the assistance history of all the households that have taken the 2020 Vulnerability Assessment of Syrian Refugees (VASyR 2020) assessment, available on the UNHCR Microdata Library (survey ID number: UNHCR_LBN_2020_VASYR_v2.1). It is possible to link each assistance record to the VASyR 2020 dataset using the case number provided.

For more info about the VASyR 2020 sampling please refer to the dataset page: https://microdata.unhcr.org/index.php/catalog/286

Mode of data collection

Other [oth]

Abstract

The World Bank in collaboration with the Kenya National Bureau of Statistics and the University of California, Berkeley are conducting the Kenya COVID-19 Rapid Response Phone Survey to track the socioeconomic impacts of the COVID-19 pandemic, the recovery from it as well as other shocks to provide timely data to inform policy. This dataset contains information from eight waves of the COVID-19 RRPS, which is part of a panel survey that targets Kenyan nationals and started in May 2020. The same households were interviewed every two months for five survey rounds, in the first year of data collection and every four months thereafter, with interviews conducted using Computer Assisted Telephone Interviewing (CATI) techniques.

The data set contains information from two samples of Kenyan households. The first sample is a randomly drawn subset of all households that were part of the 2015/16 Kenya Integrated Household Budget Survey (KIHBS) Computer-Assisted Personal Interviewing (CAPI) pilot and provided a phone number. The second was obtained through the Random Digit Dialing method, by which active phone numbers created from the 2020 Numbering Frame produced by the Kenya Communications Authority are randomly selected. The samples cover urban and rural areas and are designed to be representative of the population of Kenya using cell phones. Waves 1-7 of this survey include information on household background, service access, employment, food security, income loss, transfers, health, and COVID-19 knowledge and vaccinations. Wave 8 focused on how households were exposed to shocks, in particular adverse weather shocks and the increase in the price of food and fuel, but also included parts of the previous modules on household background, service access, employment, food security, income loss, and subjective wellbeing.

The data is uploaded in three files. The first is the hh file, which contains household level information. The ‘hhid’, uniquely identifies all household. The second is the adult level file, which contains data at the level of adult household members. Each adult in a household is uniquely identified by the ‘adult_id’. The third file is the child level file, available only for waves 3-7, which contains information for every child in the household. Each child in a household is uniquely identified by the ‘child_id’.

The duration of data collection and sample size for each completed wave was: Wave 1: May 14 to July 7, 2020; 4,061 Kenyan households Wave 2: July 16 to September 18, 2020; 4,492 Kenyan households Wave 3: September 28 to December 2, 2020; 4,979 Kenyan households Wave 4: January 15 to March 25, 2021; 4,892 Kenyan households Wave 5: March 29 to June 13, 2021; 5,854 Kenyan households Wave 6: July 14 to November 3, 2021; 5,765 Kenyan households Wave 7: November 15, 2021, to March 31, 2022; 5,633 Kenyan households Wave 8: May 31 to July 8, 2022: 4,550 Kenyan households

The same questionnaire is also administered to refugees in Kenya, with the data available in the UNHCR microdata library: https://microdata.unhcr.org/index.php/catalog/296/

Geographic coverage

National coverage covering rural and urban areas

Analysis unit

Household, Individual

Sampling procedure

The COVID-19 RRPS with Kenyan households has two samples. The first sample consists of households that were part of the 2015/16 KIHBS CAPI pilot and provided a phone number. The 2015/16 KIHBS CAPI pilot is representative at the national level stratified by county and place of residence (urban and rural areas). At least one valid phone number was obtained for 9,007 households and all of them were included in the COVID-19 RRPS sample. The target respondent was the primary male or female household member from the 2015/16 KIHBS CAPI pilot. The second sample consists of households selected using the Random Digit Dialing method. A list of random mobile phone numbers was created using a random number generator from the 2020 Numbering Frame produced by the Kenya Communications Authority. The initial sampling frame therefore consisted of 92,999,970 randomly ordered phone numbers assigned to three networks: Safaricom, Airtel and Telkom. An introductory text message was sent to 5,000 randomly selected numbers to determine if numbers were in operation. Out of these, 4,075 were found to be active and formed the final sampling frame. There was no stratification and individuals that were called were asked about the households they live in. Until wave 7 sampled households that were not reached in earlier waves were also contacted along with households that were interviewed before. In wave 8 only households that had previously participated in the survey were contacted for interview. The “wave” variable represents in which wave the households were interviewed in.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was administered in English and is provided as a resource in pdf format. Additionally, questionnaires for each wave are also provided in Excel format coded for SCTO. The same questionnaire is also administered to refugees in Kenya, with the data available in the UNHCR microdata library: https://microdata.unhcr.org/index.php/catalog/296/

Abstract

The 2024 Socio-Economic Insights Survey (SEIS) in Romania is a comprehensive regional assessment conducted from May to July 2024, focusing on the needs of refugees in Romania, particularly those from Ukraine. This multi-sectoral survey aims to capture key data on refugees' socio-economic integration, access to national systems, and their priorities for the coming year, providing valuable insights to inform the 2025 Refugee Response Plan (RRP). The survey employs a stratified random sampling method and involves face-to-face and online interviews with refugees, covering topics such as health, education, protection, food security, and livelihoods. The collected data is anonymized and cleaned for use in policy planning and intervention development. The findings highlight gaps in services and provide crucial information on the changing trends in refugees’ needs, contributing to a more targeted and effective response to refugee challenges in Romania.

Geographic coverage

Romania

Analysis unit

Household

Universe

Ukrainian refugee households in Romania

Kind of data

Sample survey data [ssd]

Sampling procedure

Probability: Stratified random sampling. The sampling frame was constructed using deduplicated databases (Cash and CRI Assistance Lists) with 15,100 households. One strata was added based on the county distribution of Ukrainian households under temporary protection, respecting the UNHCR geographical distribution.

Mode of data collection

Face-to-face interview

Research instrument

Key topics covered include protection, gender-based violence, mental health, socio-economic status, health, accommodation, food security, education, social cohesion, and access to humanitarian aid.

Abstract

This UNHCR dataset, developed in partnership with Ipsos SA, provides an in-depth analysis of the intentions and circumstances of Ukrainian refugees in Austria, based on data collected from January to March 2023. The survey, which includes responses from 553 households representing over 1,500 refugees, offers a detailed look at the socio-economic status, decision-making processes, and future plans of these individuals. Gathered via an online questionnaire distributed through social media and messaging apps, the data is carefully anonymized, ensuring privacy while maintaining a representative demographic profile in line with the latest Austrian government statistics. This dataset is a valuable asset in the Microdata Library, offering crucial insights for stakeholders engaged in refugee support and policy-making in Austria.

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling for this survey employed a non-probability, respondent-assisted approach, reaching 553 refugee households in Austria through an online questionnaire disseminated via social media and messaging platforms.

Mode of data collection

Face-to-face [f2f]

Research instrument

Income, food consumption, expenditures, assets, community relations, wellbeing, resilience, mental health, health, accommodation, protection, and education

Abstract

It is increasingly recognised that the majority of the world's refugees reside not in camps, but dispersed amongst the community in the countries where they have sought asylum. This is the case for Syrian refugees in Jordan, of which 84% live outside official refugee camps in urban and rural areas across the country. Understanding the needs, vulnerabilities and capacities of this dispersed refugee population is vital to ensuring their protection and access to services. The purpose of this dataset is to examine the situation of Syrian refugees living outside camps in Jordan, based on data collected through UNHCR's Home Visits programme. Under this programme, interviews are conducted with every refugee household registering with UNHCR outside camps. This provides an unparalleled source of information about the situation of Syrian refugees in non-camp settings.

Geographic coverage

Urban areas at National Coverage

Analysis unit

Household and individual

Kind of data

Sample survey data [ssd]

Sampling procedure

This study is not based on random sampling. The Home Visits survey is an ongoing assessment which aims to interview every refugee household registered with UNHCR outside camps. The survey went through many different versions which included major changes in variables and sections content, for this reason it is not possible to fully compare the different versions with each other. Whenever possible, though, the various dataset versions have been harmonized so that variables containing the same kind of information were renamed with the same name. You can see all the versions available in the Microdata Library in the “Related studies” tab.

Mode of data collection

Face-to-face [f2f]

Abstract

The Forced Displacement Survey (FDS) is UNHCR’s new flagship household survey programme designed to standardize, streamline, and build on the existing UNHCR survey landscape to produce high-quality and timely data on people forced to flee. The FDS is comparable across countries over time and aligned with international statistical standards. And it has the purpose of providing actionable evidence to inform the government’s operational and policy-related data needs, as well as its humanitarian and development partners.

As a multi-topic survey, the FDS collected household and individual level data on the socioeconomic characteristics and living conditions of targeted populations. Data was collected through face-to-face household interviews, where up to four household members aged 15 and above were interviewed: (1) the head of the household or a household member who was knowledgeable about the household; (2) a randomly selected household member who provided information about individual life experiences; (3) the caregiver of a randomly selected child under five years of age; and (4) a randomly selected woman who gave birth in the last two years.

South Sudan was the 1st pilot country where FDS has been implement. South Sudan hosted refugees since its independence in 2011, despite facing multiple social challenges and internal conflicts. By April 2024 South Sudan hosted 450,000 refugees, mostly from Sudan, Burundi, the Central African Republic, and other countries.

The FDS in South Sudan collected data on a nationally representative sample of registered refugees and on a sample of the national population living in proximity of refugees located in the north of South Sudan. Data collection occurred between April and December 2023. The final realized sample of the FDS in South Sudan was composed of around 3,000 households, all located in rural areas. Among them, 68 per cent are refugee households and 32 per cent belong to host communities.

Analysis unit

Household and individual

Kind of data

Sample survey data [ssd]

Sampling procedure

FDS survey features up to 4 distinct interviews and aims to represent their respective populations: •Refugee households, •Adults aged 15 and over, •Children under the age of 5 and •Women who gave birth within 2 years prior to the interview. The microdata features weights to correctly represent these populations.

The sampling design identified 5 distinctive sampling strata: •Refugees in Pariang county •Refugees in Mabane county •Refugees in Central Equatoria, West Equatoria and Jonglei •Hosts in Pariang county •Hosts in Mabane county

The main sampling principle assumed equal sample size for each identified stratum. Due to late changes in the survey design oversampling of refugees in Pariang and Mabane county was introduced in order to achieve more analytical power at the levels below the identified strata.

Mode of data collection

Computer Assisted Personal Interview [capi]

To strengthen and promote an evidence-based protection response, UNHCR and its partners implemented a protection profiling and monitoring exercise in Europe starting in May 2022 to regularly collect and analyze data about the profiles, protection risks, and needs of refugees from Ukraine and monitor changes over time. The exercise covered the following countries that received refugees from Ukraine: Belarus, Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Republic of Moldova, Poland, Romania and Slovakia.

The protection profiling and monitoring involved household-level interviews conducted at border crossing points, reception and transit centres, collective sites, and assistance points in major cities using a structured questionnaire. Trained enumerators from UNHCR and partners collected data digitally using the Kobo Toolbox. While respondents were randomly selected to reduce bias, the sample is considered a non-probability sample and results should be considered indicative, meaning they cannot be extrapolated to the population of refugees from Ukraine. The result reflects the refugees' situation at the time of data collection.

The first round of data collection took place between May and Nov 2022. The focus of the first round was general profiling of Ukraine refugees and their needs, as well as key issues during the intial phase of the crisis such as family separation, etc.

In October 2022, a new questionnaire was rolled out, shifting towards exploring longer-term issues in host countries such as access to health care, education, etc. The second round took place between Oct 2022 and 15 Feb 2023. overlapping slightly with the first round, however the datasets are not comparable due to the change in the questionnaire. The third round employed the same questionnaire as the second, and took place between 16 Feb and 30 Jun 2023.

This dataset is the anonymous version of the data that was collected during the third round. It includes 21,340 household interviews. Data from the following countries are new to this round: Czechia, Estonia, Latvia, and Lithuania.

The data from the first round is also available on the Microdata Library as a separate dataset for each country where the exercise took place.

The 2023 Multi-Sector Needs Assessment (MSNA) in Czechia presents findings from a regional interagency multi-sectoral assessment conducted with Ukrainian refugees. The assessment, carried out by SHC and IOM, aimed to evaluate refugee households' access to basic services, identify service gaps, and understand priorities for the coming year to inform response planning. Using a structured questionnaire, the assessment surveyed purposively selected households, stratified by geographic area and accommodation type. Key topics included health, protection, food security, education, livelihoods, gender-based violence, mental health, cash assistance, and legal needs. The MSNA 2023 provides key insights into the needs and experiences of Ukrainian refugees in Czechia, shaping the 2024 Refugee Response Plan. The dataset has been anonymized for publication under Licensed Use on UNHCR's Microdata Library.

Abstract

Between February and March 2021, UNHCR and WFP undertook an assessment of refugees from South Sudan in the sites of Biringi (Ituri province), Bele and Meri (Haut Uélé province) in the Democratic Republic of the Congo (DRC). The objective of the assessment was to update the basic knowledge on the humanitarian needs of the whole South Sudanese refugee population in these sites to inform programmatic decisions and assess the relevance of a harmonized humanitarian targetting strategy based on level of vulnerability.

The assessment was carried out jointly by UNHCR and WFP. All refugee households in all sites were interviewed, consisting of 8,630 households. This dataset represents an anonymous version of the original dataset. A 20% random sample of the original dataset was drawn as part of the anonymization. The sample was stratified by site (Mele, Beri and Biringi). The variable survey_weight provide the final weights.

Geographic coverage

Biringi (Ituri province), Bele and Meri (Haut Uélé province) refugee camps.

Analysis unit

Households

Universe

Refugees from South Sudan living in sites of Biringi (Ituri province), Bele and Meri (Haut Uélé province) refugee camps.

Kind of data

Sample survey data [ssd]

Sampling procedure

The original dataset was a full enumeration. The anonymous data published on the Microdata Library is a stratified random sample of the original dataset, stratified by camp (camp).

Mode of data collection

Face-to-face [f2f]

Abstract

Between June and September 2021, a group of internally displaced persons (IDPs) were evicted from pastoral sites in Batangafo, Ouham prefecture, Central African Republic. They eventually settled in Bambari, Ouaka prefecture. UNHCR in partnership with ACTED, IOM, INTERSOS and PARET undertook a study of the intentions of the IDPs to return to their place of origin. The study took place from 8 to 13 September, and included all 1,670 IDP households or 8,134 individuals living in Bambari. This data is an anonymous version of the original data. A 20% sample of the original data, representing 335 households or 1,659 individuals, was drawn before the data were anonymized for public distribution.

Geographic coverage

Bambari, Ouaka, Central African Republic

Analysis unit

Household

Universe

all IDPs living in Bambari

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey was a complete enumeration. The anonymous version published on the Microdata Library is a 20% sample of original data, stratified by prefecture of origin (origine_prefecture).

Mode of data collection

Face-to-face [f2f]

Abstract

In January 2021, the United Nations High Commissioner for Refugees (UNHCR) and the World Food Programme (WFP) undertook an assessment of refugees from Burundi in the Lusenda and Mulongwe refugee camps in South Kivu, Democratic Republic of the Congo (DRC). The objective of the assessment was to assess the relevance of UNHCR and WFP's targeting in the context of Burundian refugees and possibly develop a targeting strategy harmonized as much as possible with other refugee populations in DRC.

A secondary objective was to introduce barcodes linked to unique identifiers used in registration. This vulnerability assessment was conducted through an exhaustive inventory of all refugee households living in the Lusenda and Mulongwe camps (South Kivu) as well as those living outside the camps and who went to the interview locations in the camps. The survey targeted Burundian refugee households assisted by WFP and UNHCR. The data collected during the survey are quantitative and were supplemented by qualitative data collected in February 2021 in the camps of Lusenda and Mulongwe through four focus group discussions per camp for a total of eight focus groups. All refugee households in Lusenda and Mulongwe camps as well as those living outside the camp, were interviewed with a core set of questions (see variable TypeEnquete, response Ciblage). In addition, 7% of households, randomly selected, participated in a more detailed interview (see variable TypeEnquete, response Exhaustive). A total of 7,873 households were selected.

This dataset represents an anonymous version of the original dataset. A sample of the original dataset was drawn as part of the anonymization. The sample was stratified by camp (Lusenda or Muolongwe) and the type of survey (Ciblage or Exhaustive). All respondents that were part of the Exhaustive survey were preserved, while a random sample of the respondents that were part of the Ciblage survey was taken. The variable strata defines which records correspond with which group, and survey_weight provide the final weights.

Geographic coverage

Lusenda and Mulongwe refugee camps in South Kivu.

Analysis unit

Households

Universe

Refugees from Burundi living in Lusenda and Mulongwe refugee camps in South Kivu

Kind of data

Sample survey data [ssd]

Sampling procedure

The original dataset was a full enumeration for a core set of questions related to demographics, livelihoods and assets (TypeEnquete ciblage). A random sample of households were selected to answer an additional set of supplementary questions relating to their livelihoods, food consumption and coping strategies (TypeEnquete exhaustive). The anonymous data published on the Microdata Library is a stratified random sample of the original dataset. Data is stratified by by site (Lusenda and Mulongwe) and further more into the group of households that was asked only the base questions (ciblage) and the group of households that was asked the base questions and additional supplementary questions (exhaustive).

Mode of data collection

Face-to-face [f2f]

Abstract

Since the onset of the Syrian crisis, the humanitarian community has increasingly relied on cash-based assistance provided from donor contributions and implemented by aid partners under the Lebanon Crisis Response Plan to support the affected population. In November 2017, the World Food Programme (WFP) joined the United Nations High Commissioner for Refugees (UNHCR) and non-governmental organisations (NGO) in the delivery of multi-purpose cash (MPC) to assist the most economically vulnerable Syrian refugee households to meet their basic needs.

This study aims to measure the short-term (12 months or less) and long-term (more than 12 months) causal impact of the $173.50 and $175 MPC assistance provided by WFP and UNHCR respectively, over and above the $27 per person per month assistance, as well as the impact of discontinuation from MPC on the well-being of Syrian refugees. This report presents the causal impact on multiple dimensions of well-being, namely household expenditures, food security, housing, water, sanitation and hygiene (WASH), education, employment, health and decision-making.

The key take-away messages from the study are: 1. The impact of MPC materialised across most dimensions of well-being in the long-term, indicating the importance of households' access to a longer duration of MPC. 2. The benefits of MPC fade for many indicators within 4 to 10 months after discontinuation, and households' well-being returned to pre-assistance levels for most indicators, and dropped slightly below the pre-assistance baseline for others. 3. The findings would suggest that there are benefits to instituting longer cash cycles and/or linking MPC to other services through a 'cash plus' approach to expand and extend the positive impact of cash on beneficiary households and ensure sustainable impact.

A total of 11,457 households were visited and used in this analysis, which constitutes one of the largest samples among impact evaluations conducted in Lebanon to date.

Analysis unit

Household and individual.

Kind of data

Sample survey data [ssd]

Sampling procedure

A total of 11,457 households were visited and used in this analysis, which constitutes one of the largest samples among impact evaluations conducted in Lebanon to date. The impact evaluation used a quasi-experimental fuzzy regression discontinuity design, which enables estimation of the causal impact of MPC after different enrolment periods in the programme (rather than producing simple correlations). For this purpose, a multi-sectoral household survey was collected across three regions in Lebanon (Bekaa, North, and Mount Lebanon), where 85 per cent of Syrian refugees and 94 per cent of MPC beneficiaries live, over three waves of data collection held in July/ August 2018, February/March 2019, and July/August 2019. The multiple rounds of data collection allowed for the measurement of effects that materialise at different points in time and enabled the validation of the detected impact. Furthermore, collecting data in the summer and winter made it possible to account for seasonal variations, and accessing administrative data from UNHCR on other assistance programmes targeting the population of interest made it possible to append this information and distinguish between the effect of MPC and other programmes. WFP and UNHCR cash assistance beneficiaries are selected based on a proxy means testing formula that constructs a vulnerability score for each household based on a set of socio-demographic characteristics from the UNHCR database. This score predicts the per capita expenditure level of households and is used to rank them from most to least vulnerable. All households with a score below the SMEB are eligible for MPC. However, due to budgetary constraints, only about 29 per cent of eligible households currently receive the MPC package. WFP follows a bottom-up approach by including in the programme households starting from the lowest scores and moving up the scores until the allocated funding is fully disbursed. UNHCR employs a geographical bottomup targeting approach by including the most vulnerable households in each geographic region until it reaches the regions allocated proportion given its budget constraints. Accordingly, the point at which the funding is fully disbursed creates an artificial cut-off line. This creates a quasi-natural experiment where households on either side of the cut-off are plausibly similar along observable and unobservable characteristics. As a result, the argument is that the only difference is the receipt of MPC. Thus, any differences in outcomes between households are attributable to the amount of cash assistance received, which allows for measuring the causal impact of the MPC. Notably, because the annual recalibration of the targeting formula that determines a households eligibility for MPC occurred prior to the collection of wave 2 data, this uniquely positioned the study to measure the impact of discontinuation on affected household.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire included the following sections: demographics, education, employment, health, food, housing, economic situation, accountability.

Abstract

To monitor the rapidly changing economic landscape due to COVID-19, the National Institute of Statistics of Djibouti (INSD), with the technical assistance from the World Bank, conducted a second wave of the COVID phone survey from September 20 to October 18, 2020. Like the first wave fielded in July, this wave drew from a sampling frame consisting of households from the Ministry of Social Affairs and Solidarity’s social registry that reported telephone numbers. The sample, consisting of 1,460 complete interviews, combined a panel of households interviewed during the first wave, to which a replacement sample was added to compensate for attrition.

Geographic coverage

Urban areas only. The survey is representative of the bottom 80 percent of the consumption distribution (thus the top 20 percent are excluded). It is representative by poverty status and by three domains of Balbala, rest of Djibouti city and urban areas outside Djibouti city.

Analysis unit

• Household
• Individual

Universe

The survey covers households that reported telephone numbers, are included in the social registry data collected by the Ministry of Social Affairs and Solidarity (MASS) and have been interviewed after 2017. Refugees are excluded from this first round.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy allows for disaggregation by poverty status4 and by three survey domains, being Balbala (476 households), rest of Djibouti City (487 households) and urban areas outside Djibouti City (497 households). See "Box 1. Sampling strategy and sampling weights in wave 2" of the survey report provided as Related Documents.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire is adapted from the template questionnaire prepared by the Poverty and Equity GP to measure the impact of COVID-19 on household welfare. It was designed in French and dispensed in local language (Afar, Arabe, Somali, Français or other). The questionnaire includes the following sections: - Household Roster - Knowledge and Behavior Regarding the COVID-19 - Employment - Household's Income - Needs - Access - Safety Nets

Cleaning operations

The CsPro CATI data entry application helped to enforce skip and range patterns during data collection. Standard consistency checks (like age differences between parents and children and unicity of household heads) were carried out at the time of the data collection. Because the entry application was strictly system-controlled, complete cases including missing items were avoided. The various checks resulted in a limited need for secondary data editing, which eventually entailed two main steps from the WB team. First, duplicated names of household members, who were otherwise distinct, were corrected by adding a suffix “bis” to the names. Second, after analysis of text responses mentioned in the residual “other” categories, a few items codes were adjusted (not exceeding 10 in any category).

Response rate

The response rate stands at 85 percent nationally and the results are representative of the country’s urban population except for the top wealth quintile (richest 20 percent). For more information, please see Table 2.1 of the survey report provided as Related Documents.

Abstract

The World Bank and UNHCR in collaboration with the Kenya National Bureau of Statistics and the University of California, Berkeley are conducting the Kenya COVID-19 Rapid Response Phone Survey to track the socioeconomic impacts of the COVID-19 pandemic, the recovery from it as well as other shocks to provide timely data to inform a targeted response. This dataset contains information from eight waves of the COVID-19 RRPS, which is part of a panel survey that targets refugee household and started in May 2020. The same households were interviewed every two months for five survey rounds, in the first year of data collection, and every four months thereafter, with interviews conducted using Computer Assisted Telephone Interviewing (CATI) techniques. The sample aims to be representative of the refugee and stateless population in Kenya. It comprises five strata: Kakuma refugee camp, Kalobeyei settlement, Dadaab refugee camp, urban refugees, and Shona stateless. Waves 1-7 of this survey include information on household background, service access, employment, food security, income loss, transfers, health, and COVID-19 knowledge. Wave 8 focused on how households were exposed to shocks, in particular adverse weather shocks and the increase in the price of food and fuel, but also included parts of the previous modules on household background, service access, employment, food security, income loss, and subjective wellbeing. The data is uploaded in three files. The first is the hh file, which contains household level information. The 'hhid', uniquely identifies all household. The second is the adult level file, which contains data at the level of adult household members. Each adult in a household is uniquely identified by the 'adult_id'. The third file is the child level file, available only for waves 3-7, which contains information for every child in the household. Each child in a household is uniquely identified by the 'child_id'. The duration of data collection and sample size for each completed wave was: Wave 1: May 14 to July 7, 2020; 1,328 refugee households Wave 2: July 16 to September 18, 2020; 1,699 refugee households Wave 3: September 28 to December 2, 2020; 1,487 refugee households Wave 4: January 15 to March 25, 2021; 1,376 refugee households Wave 5: March 29 to June 13, 2021; 1,562 refugee households Wave 6: July 14 to November 3, 2021; 1,407 refugee households Wave 7: November 15, 2021, to March 31, 2022; 1,281 refugee households Wave 8: May 31 to July 8, 2022: 1,355 refugee households The same questionnaire is also administered to nationals in Kenya, with the data available in the WB microdata library: https://microdata.worldbank.org/index.php/catalog/3774

Geographic coverage

National coverage covering rural and urban areas

Analysis unit

Individual and Household

Universe

All persons of concern for UNHCR

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample aims to be representative of the refugee and stateless population in Kenya. It comprises five strata: Kakuma refugee camp, Kalobeyei settlement, Dadaab refugee camp, urban refugees, and Shona stateless, where sampling approaches differ across strata. For refugees in Kakuma and Kalobeyei, as well as for stateless people, recently conducted Socioeconomic Surveys (SES), were used as sampling frames. For the refugee population living in urban areas and the Dadaab camp, no such household survey data existed, and sampling frames were based on UNHCR's registration records (proGres), which include phone numbers. For Kakuma, Kalobeyei, Dadaab and urban refugees, a two-step sampling process was used. First, 1,000 individuals from each stratum were selected from the corresponding sampling frames. Each of these individuals received a text message to confirm that the registered phone was still active. In the second stage, implicitly stratifying by sex and age, the verified phone number lists were used to select the sample. Until wave 7 sampled households that were not reached in earlier waves were also contacted along with households that were interviewed before. In wave 8 only households that had previously participated in the survey were contacted for interview. The “wave” variable represents in which wave the households were interviewed in. For the stateless population, all the participants of the Shona socioeconomic survey (n=400) were included in the RRPS, because of limited sample size. The sampling frames for the refugee and Shona stateless communities are thus representative of households with active phone numbers registered with UNHCR.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire included 12 sections Section 1: Introduction Section 2: Household background Section 3: Travel patterns and interactions Section 4: Employment Section 5: Food security Section 6: Income Loss Section 7: Transfers Section 8: Subjective welfare (50% of sample) Section 9: Health Section 10: COVID Knowledge Section 11: Household and Social Relations (50% of sample) Section 12: Conclusion

Cleaning operations

Variable names were kept constant across survey waves. For questions that remained exactly the same across survey waves, data points for all waves can be found under one variable name. For questions where the phrasing changed (even in a minimal way) across waves, variable names were also changed to reflect the change in phrasing. Extended missing values are used to indicate why a value is missing for all variables. The following extended missing values are used in the dataset: · .a for 'Don't know' · .b for 'Refused to respond' · .c for 'Outliers set to missing' · .d for 'Inconsistency set to missing' (used for employment data as explained below) · .e for 'Field Skipped' (where an error in the survey tool caused the question to be missed) · .z for 'Not administered' (as the variable was not relevant to the observation) More detailed data on children was collected between waves 3 and 7, compared to waves 1, 2 and 8. In waves 1 and 2, data on children, e.g. on their learning activities, was collected for all children in a household with one question. Therefore, variables related to children are part of the 'hh' data for waves 1 and 2. Between waves 3 and 7, questions on children in the household were asked for specific children. Some questions covered all children, while others were only administered to one randomly selected child in the household. This approach allows to disaggregate data at the level of the child household members, and the data can be found in the 'child' data set. The household level weights can be used for analysis of the children's data. In wave 8, detailed information on children was dropped, as the questionnaire focused on other topics. The education status of household members, except for the respondent, was imputed for rounds 1 and 2. For rounds 1 and 2, only the education status of the respondent was elicited, while for later rounds the education status for each household member was asked. In order to evaluate outcomes by the household member's education status, information on education was imputed for waves 1 and 2, using the information provided for all household members in waves 3, 4, and 5. This resulted in additional information on the education status for household members in round 1 and 2, which was not yet available for earlier versions of this data. Some questions are not asked repeatedly across waves such that their values were imputed. For some questions, answers are not possible or unlikely to change within two months between survey waves such that households were not asked about them in all waves. The questions on assets owned before March 2020 were only asked to households when they are interviewed for the first time. The questions on the dwelling's wall and floor material as well as the household's connection to the power grid was not asked for all households in wave 2 and 3, where only new households and those who moved were covered by these questions. Questions on the main source of electricity in the households and types of assets owned were not asked in wave 8. The missing values those variables have when they were not asked, are imputed from the answers given in earlier waves. Improved quality insurance algorithms lead to minor revisions to wave 1 to 5 data. Based on additional data checks, the team has made minor refinements to wave 1 to 5 data. The identification of the household members that were the respondent or the household head was refined in the rare cases where it was not possible to interview the same respondent as in previous waves for a given household such that another adult was interviewed. For this reason, for about 2 percent of observations the household head status was assigned to an incorrect household member, which was corrected. For <1 percent of households the respondent did not appear in adult level dataset. For about 1 percent of observations in wave 5 the respondent appeared twice in the adult level dataset. Data from questions on COVID-19 vaccinations from wave 7 was dropped from the dataset. Due to significantly higher self-reported vaccination rates compared to official administrative records, data on vaccinations was deemed unreliable, most likely due to social desirability bias. Consequently, questions on vaccination status and questions using the vaccination data as a validation criterion were dropped from the datasets.