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The RERS was conducted in Nigeria, Somalia, South Sudan and Yemen, where food shortage from a prolonged drought brought large portions of the populations to the brink of famine. These conditions urged a rapid humanitarian short-term response but also requires a developmental intervention to restore assets and create resilience for future shocks. The RERS collects data to inform the developmental response.","coll_dates":[{"start":"2017-08-30","end":"2017-10-02","cycle":""}],"nation":[{"name":"Somalia","abbreviation":"SOM"},{"name":"South Sudan","abbreviation":"SSD"},{"name":"Yemen, Rep.","abbreviation":"YEM"}],"geog_coverage":"For the Somali population, pre-war regions declared to be in Emergency or worse are surveyed. This comprises of the regions Bakool, Bay, Bari, Galguduud, Gedo, Hiran, Lower Shabelle, Mudug, Nugaal, Sanaag, Sool, Toghdeer and Woqooyi Galbeed.\n\nIn South Sudan, former states declared to be in Emergency or worse are surveyed. This comprises of Central Equatoria, Jonglei, Nothern Bahr-el-Gazal, Unity, Upper Nile and Western Bahr-el-Gazal.\n\nIn Yemen, the survey covers all governorates, stratified into Emergency and non-emergency strata. Governorates classified as \u2018Emergency\u2019 are Abyan, Al Bayda, Hajjah, Lahj, Sa\u2019ada, Sana\u2019a, Shabwah and Taizz. Non-\u2018Emergency\u2019 governorates are Aden, Al Dhale\u2019e, Al Hudaydah, Al Mahwit, Amanat Al Asimah, Amran, Dhamar, Hadramaut, Ibb, Marib and Raymah.","analysis_unit":"- Households","universe":"Households with active phone connections and charged phones in 13 (pre-war) regions classified to be under \u2018Emergency\u2019.","data_kind":"Sample survey data [ssd]","notes":"The scope of the RERS includes:\n\n-  Household Information\n\n-  Education\n\n-  Main Income Source for Household\n\n-  Main Employment of Household\n\n-  Assets\n\n-  Food and Market Access\n\n-  Vulnerability Measure: Coping Strategies Index\n\n-  Water Access and Quality\n\n-  Health"},"method":{"data_collection":{"sampling_procedure":"SOMALIA\n\n-  Population targeted: Households with active phone connections and charged phones in 13 (pre-war) regions classified to be under \u2018Emergency\u2019 phase as per the IPC. \n\n-  Sample structure: 2600 households, stratified by region.  A random sample was drawn for each strata based on a sampling frame of phone numbers that responded to a mass text message sent for this purpose.\n\nSOUTH SUDAN\n\n-  Population targeted: Households with active phone connections and charged phones in 6 (pre-war) states classified to be under \u2018Emergency\u2019 phase as per the IPC.\n\n-  Sample structure: 1200 households, stratified by state.  A random sample was drawn for each of the strata using random digit dialing.\n\nYEMEN\n\n-  Population targeted: Households with active phone connections and charged phones across all (21) governorates in the country and the capital City, Sana\u2019a.\n\n-  Sample structure: 1800 households, stratified by governorate (the capital Sana\u2019a is a separate strata in itself). A random sample -was drawn from each governorate and the capital Sana\u2019a, using random digit dialing.\n\nThe sample size of these strata is low and would yield large confidence intervals for the estimates. 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This index has been used as a measure of household vulnerability, which is correlated against other variables to understand the profiles of households that are most vulnerable.\n\nAll questionnaires and modules are provided as Related Materials.","coll_situation":"Data collection was implemented over the phone, separately for each country through call-centers.","weight":"The sampling weight w is calculated for each strata as follows:\n\nw = N\/n,\n\nwhere N is the population in the strata, and n is the number of interviews completed in the strata.\n  \nNote that the strata are defined slightly differently among the countries, as detailed in Sampling Procedure above. For Yemen, the governorate-level strata are used to calculate the weights."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Before being granted access to the dataset, all users have to formally agree: \n\n1. 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No attempt will be made to produce links among datasets provided by the World Bank Microdata Library, or among data from the World Bank Microdata Library and other datasets that could identify individuals or organizations. \n\n5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the World Bank Microdata Library will cite the source of data in accordance with the Citation Requirement provided with each dataset.","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"schematype":"survey","tags":[{"tag":"DOI"}],"data_files":[{"file_id":"F1","file_name":"assets_CleanOutput","description":"Final cleaned data (Assets)","case_count":8671,"var_count":27,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F2","file_name":"hh_CleanOutput","description":"Final cleaned data (Household 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