Between February and June 2016, World Bank in collaboration with South Sudan’s National Bureau of Statistics, funded by DfID, conducted the second wave of the High Frequency Survey South Sudan to monitor welfare and perceptions of citizens, revisiting urban households from Wave 1. This dataset contains information on security, economic conditions, education, employment, access to services, and perceptions. It also includes comprehensive information on assets and consumption, to allow estimation of poverty based on the Rapid Consumption methodology as detailed in Pape and Mistiaen (2014).
Kind of data
Sample survey data [ssd]
Unit of analysis
The survey was conducted using a CAPI mode (SurveyCTO sofware). Some questions refered to responses of earlier questions in their wordings. To allow that, the questions might have special characters in their wordings.
Question"Please confirm that your ID number is [qr_id]," where qr_id is another variable. Here the square brackets  are used so that instead of "qr_id," the value of qr_id as selected by the respondent, will appear within the wordings of this question in the tablet when the survey is administered.
The data tables were downloaded directly from the SurveyCTO platform. Each data table has variables "State", "ea", and "hh". These are the identifying variables for the households and are used to match the observations in the given datasets.
Seven of South Sudan's ten former states: Western Equatoria, Central Equatoria, Eastern Equatoria, Northern Bahr-El-Ghazl, Western Bahr-El-Ghazal, Warrap and Lakes state. The other three former states (Jonglei, Unity, and Upper Nile) could not be surveyed due to security concerns.
Unit of analysis
Producers and sponsors
Utz J. Pape
The World Bank
South Sudan's National Bureau of Statistics
Department for International Development
Wave 2 of the High Frequency South Sudan Survey revisited the urban households surveyed in Wave 1. In addition, Wave 2 surveyed five additional enumeration areas in each of the following three states: Northern Bahr el Ghazal, Lakes and Eastern Equatoria and added Warrap state to the sample. Thus, 15 urban enumeration areas were selected in total from each state. For the additional enumeration areas, the same sample design as for Wave 1 was followed after excluding already selected enumeration areas due to the revisit. The design employs a stratified clustered design. Within each of the 7 strata (7 states, urban) the primary sampling units are enumeration areas (EAs) that were drawn randomly proportional to size. Within EAs, a listing was conducted for the new enumeration areas introduced into the sample and 12 households were drawn randomly as unit of observation.
Deviations from sample design
Enumeration Areas (EA) were replaced if security rendered field work unfeasible. Replacements were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits to the household.
The sampling weight is the inverse probability of selection. The selection probability for a household can be decomposed into the selection probability of the EA and the selection probability of the household within the EA. The selection probability of an EA is calculated as the number of households within the EA divided by the number of households within the stratum multiplied by the number of selected EAs in the stratum estimated using the 2008 Census. The selection probability for a household within an EA is constant across households and is calculated as the number of households selected in the EA over the number of listed households in the EA. Sampling weights were then scaled to equal the number of households per strata using the Census 2008 data.
Dates of collection
Mode of data collection
Computer Assisted Personal Interview [capi]
The questionnaire was coded and administered using SurveyCTO.
See accompanying Stata do files, available under the related materials tab
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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.
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 scientic research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specic 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.
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
Utz J. Pape, World Bank. South Sudan High Frequency Survey 2016, Wave 2 (HFS-W2), Ref. SSD_2016_HFS-W2_v02_M. Datasets downloaded from [URL] on [date].
Disclaimer and copyrights
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.
Utz Johann Pape
The World Bank
Development Data Group
The World Bank
v02 (August 2017)
Metadata on all datasets included in DDI