Rapid Emergency Response Survey 2017, Pilot Project
Somalia, South Sudan, Yemen, Rep., 2017
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Reference ID
WLD_2017_RERS_v01_M
Producer(s)
Utz Pape
Collection(s)
Metadata
Created on
Jan 15, 2019
Last modified
May 24, 2021
Page views
17710
Downloads
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Identification
Survey ID Number
WLD_2017_RERS_v01_M
Title
Rapid Emergency Response Survey 2017, Pilot Project
Subtitle
Pilot Project
Country/Economy
| Name | Country code |
|---|---|
| Somalia | SOM |
| South Sudan | SSD |
| Yemen, Rep. | YEM |
Study type
Socio-Economic/Monitoring Survey [hh/sems]
Abstract
The Rapid Emergency Response Survey (RERS) 2017 is a pilot project that developed a rapid, low cost methodology using phone interviews to identify critical developmental binding constraints to inform a developmental response to populations in crisis. 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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Households
Version
Version Description
- v01: Cleaned, anonymous dataset for Somali regions, South Sudan and Yemen
Scope
Notes
The scope of the RERS includes:
- Household Information
- Education
- Main Income Source for Household
- Main Employment of Household
- Assets
- Food and Market Access
- Vulnerability Measure: Coping Strategies Index
- Water Access and Quality
- Health
- Household Information
- Education
- Main Income Source for Household
- Main Employment of Household
- Assets
- Food and Market Access
- Vulnerability Measure: Coping Strategies Index
- Water Access and Quality
- Health
Coverage
Geographic 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.
In 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.
In Yemen, the survey covers all governorates, stratified into Emergency and non-emergency strata. Governorates classified as ‘Emergency’ are Abyan, Al Bayda, Hajjah, Lahj, Sa’ada, Sana’a, Shabwah and Taizz. Non-‘Emergency’ governorates are Aden, Al Dhale’e, Al Hudaydah, Al Mahwit, Amanat Al Asimah, Amran, Dhamar, Hadramaut, Ibb, Marib and Raymah.
In 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.
In Yemen, the survey covers all governorates, stratified into Emergency and non-emergency strata. Governorates classified as ‘Emergency’ are Abyan, Al Bayda, Hajjah, Lahj, Sa’ada, Sana’a, Shabwah and Taizz. Non-‘Emergency’ governorates are Aden, Al Dhale’e, Al Hudaydah, Al Mahwit, Amanat Al Asimah, Amran, Dhamar, Hadramaut, Ibb, Marib and Raymah.
Universe
Households with active phone connections and charged phones in 13 (pre-war) regions classified to be under ‘Emergency’.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Utz Pape | World Bank, Poverty and Equity Global Practice |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| State and Peacebuilding Fund | SPF |
Sampling
Sampling Procedure
SOMALIA
- Population targeted: Households with active phone connections and charged phones in 13 (pre-war) regions classified to be under ‘Emergency’ phase as per the IPC.
- 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.
SOUTH SUDAN
- Population targeted: Households with active phone connections and charged phones in 6 (pre-war) states classified to be under ‘Emergency’ phase as per the IPC.
- Sample structure: 1200 households, stratified by state. A random sample was drawn for each of the strata using random digit dialing.
YEMEN
- Population targeted: Households with active phone connections and charged phones across all (21) governorates in the country and the capital City, Sana’a.
- Sample structure: 1800 households, stratified by governorate (the capital Sana’a is a separate strata in itself). A random sample -was drawn from each governorate and the capital Sana’a, using random digit dialing.
The sample size of these strata is low and would yield large confidence intervals for the estimates. Thus, for analysis the strata can be grouped into 'analytical strata' as follows:
1. Governorates in emergency or worse as per the IPC.
2. Governorates not in emergency as per IPC.
3. Capital city of Sana’a.
- Population targeted: Households with active phone connections and charged phones in 13 (pre-war) regions classified to be under ‘Emergency’ phase as per the IPC.
- 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.
SOUTH SUDAN
- Population targeted: Households with active phone connections and charged phones in 6 (pre-war) states classified to be under ‘Emergency’ phase as per the IPC.
- Sample structure: 1200 households, stratified by state. A random sample was drawn for each of the strata using random digit dialing.
YEMEN
- Population targeted: Households with active phone connections and charged phones across all (21) governorates in the country and the capital City, Sana’a.
- Sample structure: 1800 households, stratified by governorate (the capital Sana’a is a separate strata in itself). A random sample -was drawn from each governorate and the capital Sana’a, using random digit dialing.
The sample size of these strata is low and would yield large confidence intervals for the estimates. Thus, for analysis the strata can be grouped into 'analytical strata' as follows:
1. Governorates in emergency or worse as per the IPC.
2. Governorates not in emergency as per IPC.
3. Capital city of Sana’a.
Deviations from the Sample Design
In Yemen, three governorates, Al Jawf, Al Maharah and Socotra, could not be reached over the phone, thus they were dropped and the share of planned interviews was evenly spread among other governorates.
Weighting
The sampling weight w is calculated for each strata as follows:
w = N/n,
where N is the population in the strata, and n is the number of interviews completed in the strata.
Note 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.
w = N/n,
where N is the population in the strata, and n is the number of interviews completed in the strata.
Note 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 Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2017-08-30 | 2017-10-02 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Data Collection Notes
Data collection was implemented over the phone, separately for each country through call-centers.
Questionnaires
Questionnaires
The questionnaire covers modules on income, employment, schooling, market and food access, water and health. Many questions explore changes in these areas over the previous 1 to 12 months, to understand the impacts of the current food security crisis. The questionnaire also includes the Coping Strategies Index (CSI), which measures severity of food insecurity. 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.
All questionnaires and modules are provided as Related Materials.
All questionnaires and modules are provided as Related Materials.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Utz Pape | World Bank | upape@worldbank.org |
Confidentiality
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor.
Access conditions
The dataset has been anonymized and is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the World Bank Microdata Library.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the World Bank Microdata Library.
4. 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.
5. 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.
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the World Bank Microdata Library.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the World Bank Microdata Library.
4. 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.
5. 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.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example,
Utz Pape, World Bank. Rapid Emergency Response Survey (RERS) 2017. Ref. WLD_2017_RERS_v01_M, Dataset downloaded from [url] on [date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example,
Utz Pape, World Bank. Rapid Emergency Response Survey (RERS) 2017. Ref. WLD_2017_RERS_v01_M, Dataset downloaded from [url] on [date].
Disclaimer and copyrights
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.
Metadata production
DDI Document ID
DDI_WLD_2017_RERS_v02_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the DDI |
DDI Document version
DDI Document - Version 02 - (05/24/21)
This version is identical to DDI_WLD_2017_RERS_v01_M_WB but country field has been updated to capture all the countries covered by survey.
v01 (December 2018)
This version is identical to DDI_WLD_2017_RERS_v01_M_WB but country field has been updated to capture all the countries covered by survey.
v01 (December 2018)