{"doc_desc":{"title":"Namibia Household income and Expenditure Survey 2015\/16","idno":"NAM_NSA_2015\/16_NHIES_VO4","producers":[{"name":"Namibia Statistics Agency","abbr":"NSA","affiliation":"NSA","role":""}],"prod_date":"2018"},"study_desc":{"title_statement":{"idno":"NAM_NSA_2015\/16_NHIES_VO4","title":"Namibia Household Income and Expenditure Survey","sub_title":"2015\/16","alternate_title":"NHIES 2015\/16","translated_title":"In to English"},"authoring_entity":[{"name":"Namibia Statistics Agency","affiliation":"National Planning  Commision"}],"production_statement":{"copyright":"Namibia Statistics Agency","funding_agencies":[{"name":"Government Republic of Namibia","abbr":"GRN","role":"Funding "},{"name":"The  World Bank","abbr":"WB","role":"Techinical suport"},{"name":"United States Agency for International Delopment","abbr":"USAID","role":"Funding "},{"name":"United States Census Bureau","abbr":"USCB","role":"Technical suport"}]},"distribution_statement":{"distributors":[{"name":"Namibia Statistics Agency","abbr":"NSA","affiliation":"NSA","uri":""}],"contact":[{"name":"Namibia Statistics Agency","affiliation":"National Planning  Commision","email":"+264614313200","uri":"www.nsa.org.na"}]},"series_statement":{"series_name":"Income\/Expenditure\/Household Survey [hh\/ies]","series_info":"The Namibia Household Income and Expenditure Survey (NHIES) 2015\/2016 edition is the fourth of its kind to be executed in Namibia and the first to be carried out by the Namibia Statistics Agency (NSA) as per its first Strategic plan for the period of 2012\/2013 to 2016\/2017."},"version_statement":{"version":"NHIES 2015\/2016","version_date":"2018-03-14"},"study_info":{"keywords":[{"keyword":"Proportion of households cooking without electricity or gas","vocab":"","uri":""},{"keyword":"Proportion of households with no toilet\/use bush","vocab":"","uri":""},{"keyword":"Proportion of households that own a radio","vocab":"","uri":""},{"keyword":"Average annual per capita consumption (N$)","vocab":"","uri":""},{"keyword":"Proportion of households that are \u201cpoor\u201d or \u201cseverely poor\u201d","vocab":"","uri":""},{"keyword":"Poor households (incl. severely poor) -","vocab":"","uri":""},{"keyword":"Severely poor households","vocab":"","uri":""},{"keyword":"GINI-coefficient","vocab":"","uri":""}],"topics":[{"topic":"Population size","vocab":"","uri":""},{"topic":"Income and Expenditure","vocab":"","uri":""},{"topic":"Education","vocab":"","uri":""},{"topic":"Dwelling characteristics","vocab":"","uri":""},{"topic":"Anthropometric measurement of children less than 5 years","vocab":"","uri":""},{"topic":"Durable assets","vocab":"","uri":""},{"topic":"Annual Labour Force","vocab":"","uri":""},{"topic":"Main source of income","vocab":"","uri":""},{"topic":"Housing and utiliies","vocab":"","uri":""},{"topic":"Distance to services","vocab":"","uri":""},{"topic":"Ownership and access to assets","vocab":"","uri":""},{"topic":"Annual consumption and income","vocab":"","uri":""},{"topic":"Distribution of annual consumption","vocab":"","uri":""}],"abstract":"The Namibia Household Income and Expenditure Survey (NHIES) 2015\/2016 edition is the fourth of its kind to be executed in Namibia and the first to be carried out by the Namibia Statistics Agency (NSA) as per its first Strategic plan for the period of 2012\/2013 to 2016\/2017. \n\nThe NHIES is a household based survey, designed to collect data on income and expenditure patterns of households and the sole source of information on income and expenditure in the country. Therefore, institutions did not form part of this survey. Data from the NHIES is used to compute poverty indicators at household and individual levels. The survey also serves as a statistical framework for compiling the national basket items for the compilation of price indices used in the calculation of inflation. It also forms the basis for updating prices or rebasing of national accounts. \n\nThe implementation of NHIES 2015\/16 was financed by the Government of the Republic of Namibia through the Ministry of Economic Planning sectoral budget. Technical support in the area of data processing, for example, the development of data entry and listing applications was provided by experts from the United States Census Bureau through funding by USAID. In addition, experts from the World Bank (WB) provided technical expertise for during data analysis and sampling.\n\nThe main objective of the Namibia Household Income and Expenditure Survey (NHIES 2015\/2016) is to provide data to measure  the levels of living of the population of Namibian, for example,  using actual patterns of consumption and income, as well as a range of other socio-economic indicators. Statistical information from this  survey will inform planning and policy making processes  at national, regional and  international levels in particular the implementation of  Fifth National Development Plan, SADC agenda,  AU Agenda 2063 and Sustainable Development Goals (SDGs). The NHIES was designed to provide policy makers with reliable, up to date and quality  statistics at national, regional levels as well as rural urban disaggregated statistics for planning and decision making purposes.\n A representative sample of 10368 households from 864 primary sampling units (PSUs) was selected for the survey. Data was collected  over a twelve months period consisting of twenty two  survey rounds.\n\nAfter data processing, 10090 out of 10368 sampled households were used for analysis..","time_periods":[{"start":"2015-03-27","end":"2016-03-21","cycle":"22 survey rounds "}],"coll_dates":[{"start":"2015-03-27","end":"2016-03-21","cycle":"22 Survey rounds"}],"nation":[{"name":"Namibia","abbreviation":"NAM"}],"geog_coverage":"The survey was national and covered  representative samples from all 14 regions to\nallow for regional, and urban and rural disaggregation at regional and national levels. \n\nDue to financial constraints the survey was not able to collect data at levels lower than\nregions, although it was desirable to do so. \n\nThe NHIES is a household based exercise which excludes institutional population such as those living in army barracks, prisons, hospitals, hostels and the\nlikes. However, private households in those institutions if selected were covered in the survey.","analysis_unit":"Unit of analysis in the survey is private households and individuals.","universe":"The survey was national and covered representative samples from all 14 regions to\nallow for regional, and urban and rural disaggregation at regional and national levels. \n\nDue to financial constraints the survey was not able to collect data at levels lower than\nregions, although it was desirable to do so. \n\nThe NHIES is a household based exercise which excludes institutional population such as those living in army barracks, prisons, hospitals, hostels and the\nlike. However, private households in those institutions if selected were covered in the survey.","data_kind":"Sample survey data [ssd]","notes":"Access to Services \nEducation\nHousing and utilities \nDemographic characteristics \nHealth \nMain source of income \nDistribution of annual consumption"},"method":{"data_collection":{"time_method":"The data collection  started on 27 April 2015 to 21 March 2016","data_collectors":[{"name":"Namibia Statistics Agency","abbr":"NSA","role":"","affiliation":"Mimnistry of Economic Planning and National planning Commision"}],"sampling_procedure":"The design of the NHIES 2015\/2016 differs in comparison to previous NHIES undertakings. One such variation appears in the reduction of the number of households selected from the sampled primary sampling units (PSUs). This was done to increase the geographical coverage and by so doing increase the precision level of survey estimates. \n16 Namibia Household Income and Expenditure Survey (NHIES) 2015\/2016 Report\n\n Survey Methodology\nThe number of households to be covered in each PSU have been reduced from 20 in previous NHIES to 12. This procedure increased the total number of PSUs sampled, from 500 in previous NHIES to 864 while keeping the overall sample households fixed. Similarly, the collection period of food transactions such as tobacco, beverage and food items in the households has also been reduced from 28 days in previous NHIES to 7 days.\nThis new survey methodology was adopted to increase the precision of indicators without significant impact on costs as well as to reduce the time interviewers spend in households thereby reducing the burden of response fatigue.\n\nTarget population and the survey population\n The target population for the NHIES 2015\/2016 was the non-institutional population residing in private households in Namibia. The Institutional population were out of scope for NHIES 2015\/2016, however private households found within institutions were included in the target population. In addition, people who were homeless or those who usually reside in those private households, but were in hospital, prison and school hostels during the time of data collection were not eligible for NHIES 2015\/2016. Table 2.1 below presents the list of institutional population, which were excluded, from the NHIES 2015\/2016.\n\nSampling frame \nThe primary sampling frame used for this survey is a list of Primary sampling Units (PSUs) based on the 2011 Population and Housing Census Enumeration Areas (EAs). A PSU can be one EA, part of an EA or more than one EA. A secondary sampling frame for each of the selected PSUs was created for the purpose of selecting the sample households through a listing procedure.\n\nThe sampling design \nThe sample design for the survey was a stratified two-stage cluster sample, where the first stage units were geographical areas designated as the Primary Sampling Units (PSUs) and the second stage units were the households. The up-to-date list of households in the selected PSU were prepared during the listing stage of fieldwork, and 12 households were systematically selected in each PSUs. \n\nThe primary sample frame was stratified first by region followed by urban and rural areas within region. The Urban\/rural strata were further stratified implicitly by constituencies. \nThe rural strata were also further stratified implicitly taking into consideration the proclaimed villages, settlements within the rural strata. Once this step was carried out the remaining PSUs in rural strata were implicitly stratified into communal and commercial farming areas. The PSUs within each of these areas were also geographically arranged.\n\nThe households in the secondary frame constitute a list of all households for each selected PSU were listed generally following a geographic order. Additional information was collected from the PSUs in the commercial farming areas for the purpose of carrying out further stratification before selecting sample households.\n\nSample selection \nThe first stage sample of PSUs was selected from the sampling frame using the probability proportional to size (PPS) sampling together with systematic sampling procedure. Once the PSUs were selected a listing operation was carried out to prepare a fresh list of households then 12 households were selected from the list of households (implicitly stratified) using a systematic sampling procedure. Selection of the sample households were carried out using a CSPro based sampling application.\n\nSubstitution of non-responding households\n The survey was divided into four quarters and each quarter was further divided into survey rounds. During each survey round, some selected households did not respond to the survey as a result of non-contacts and\/or refusals. If one household did not respond in a PSU this case was accepted as non-response. On the other hand if two or more non-responding households were encountered, then such households were replaced with households from a fresh selection in the same PSU.  The replacement households were randomly selected using the CSPro based sampling application, designed to consider households with similar characteristics to the original selected households.\n\nThe NHIES sample distribution\n The overall sample size was calculated to give reliable estimates of different characteristics at regional level as the lowest domain of estimation. The estimates of the characteristics for all other domains above the regional level will have better precision than the regions.  The total sample size was 10368 households. A sample of 12 households were selected within each selected PSU from a freshly prepared list of households just before the interview. The total number of sampled PSUs was 864.\n\nThe survey needed to cover seasonal variations in different characteristics and therefore was carried out throughout the year. The survey year consists of four quarters, divided into survey rounds, which were 24 in total. Each survey round was made up of 15 days that a household was required to participate in the survey. The 864 PSUs were randomly allocated to the 24 survey rounds so that the sample selected for each round yield a representative sample at national level. Some adjustments were done when the allocated PSUs were drawn from the same stratum. Hence each survey round covered 36 PSUs that consisted of 432 households.\n\nSample Realization \nThe data collection process was followed by the verification of the number of households and PSUs received against the actual sample. This was then followed by structural editing process to ensure completeness of information and once this exercise was completed, the household file and person file was made available for weighting. The household file received had 10090 records, while the individual file had 41581 records, which were used for the weights calculation.","coll_mode":["Face-to-face interviews [f2f]"],"research_instrument":"Two Forms (questionnaires) were used to record information on consumption and income using a face-to-face interview method. Form I recorded demographic information and transactions of infrequent nature like purchases of durable goods as well as other information from other modules while Form II or daily record book (DRB) was used to capture information of daily transactions such as buying of bread, presents given to members of households and gifts given outside the household, etc. during the survey round. Households were shown how to record daily transactions. However, where there were no literate persons in the households, interviewers visited them on daily basis in order to help with daily DRB recordings.","sources":[{"name":"","origin":"","characteristics":""}],"coll_situation":"1. Each interviewing team comprised of 2  interviewers and 1 team supervisor. \n2. Interviews were conducted primarily in English.\n3.The evaluation of the pilot survey was done.\n4.There were 9 x Information Technology Field Technicians (ITFT) who provided IT support to the regions. Two (2) ITFTs were allocated to each region except for the Zambezi region.","act_min":"The issue of data quality is critical to the production of official statistics because it enhances the credibility of data and the institution that produces them. Therefore, NSA places data quality at the core of its statistical work across and data collection activities including this survey, to increase data use. Great efforts were made to check and ensure that collected data were relevant, reliable, accurate and timely. \nTherefore, to achieve these attributes, consultation with key stakeholders were carried out, use of sound survey approach and sampling methodology, provision of adequate training, well developed questionnaires and training manuals including \"Data quality assurance manual\", capturing data with Tablets with in-built editing rules and regular field visits by the monitoring teams routinely were carried out or as the need arise. The monitoring teams consisted mainly of national supervisors were dispatched to regions at the beginning of each quarter to ensure that field work commenced as planned. Monitoring teams also conducted control interviews in the same households, which had been covered by the interviewers and sat in some interviews to observe how interviewers conducted the interviews. Furthermore, monitoring was also done on a daily basis from the head office through submission of daily monitoring reports from Regional Statisticians. The division for Quality Assurance took several field trips to undertake quality audits during field work and evaluate whether field staff were following stipulated guidelines for data collection. The comprehensive and completeness of the data collection were also audited, and further control measures were introduced to improve data collection. All survey quality checks were guided by quality guidelines for data collection as prescribed in the Data Quality Assurance and Interviewer Manuals. \nFinally, it is worth mentioning that this edition of the NHIES was the first NHIES to make use of the computer assisted personal interview methodology, using the CSPro-based application in Tablets. This methodology was implemented with the aim of improving efficiency and thus data quality. \n\n\nThe main survey consisted of regional field teams managed by the Regional Supervisor (statistician). There were 9 x Information Technology Field Technicians (ITFT) who provided IT support to the regions. Two (2) ITFTs were allocated for each region except for the Zambezi region which was allocated one (1) ITFT because of its long distance from other regions. The ITFTs worked closely with the Regional Supervisors. Each field team consisted of a team supervisor and 2 interviewers. Each interviewer was responsible for 6 of the 12 selected households in each PSU. Field personnel were recruited from their own areas since they were familiar with the local terrain\/locality and to facilitate interviews in local languages. In total, 54 teams comprising of 162 field staff were in the field during first quarter of the data collection. This number was further reduced from quarter 2 to 4 to a total of 36 teams and 108 field staff.","weight":"A representative sample of private households was selected using the updated National\nsample frame and in accordance with a scientific procedure to partake in the survey in order\nto provide valid and reliable data and sample estimates. \n\nEach selected household had to participate in the interview for a period of two weeks known as a survey round after which a\nnew set of households or subsample was selected. \n\nWeighting is a process of accounting for the selection probabilities and non-response in a sample survey. The inverse of these selection probabilities adjusted for non-response is called the design (base) weight. For the calculation of income and consumption per capita aggregates, weights calibration was required to get the required population and households weights  for the calculation of per capita indicators. Assistance was sought from experts from the World Bank as there was no internal expertise to do weight calibration as required.\n\nA detailed weighting description is provided in the 2015\/16 NHIES Basic report.","cleaning_operations":"Data entry application was built with many consistency checks, skipping patterns and other validations such as maximum and minimum acceptance range per variable.  Supervisors were given minimum variables to check on a day-to-day basis, especially for other - specify (notes) variables. As a result, data consistency checks, coding and validation was done at field level. This minimized the time spent on post data cleaning, validation and editing process."},"method_notes":"The data processing methodology that was adopted for this study was the Computer Assisted Personal Interview method (CAPI). Data management tools to collect, transmit and store and clean (primary editing and recoding) survey data were designed and developed using CSPro 6.3.","analysis_info":{"response_rate":"After data processing, 10090 out of 10368 sampled households were successfully used for analysis, resulting in a 97.3 percent response rate which is highly satisfactory as exceeds the NSA target response rate of 80 percent for all data collection in the social statistics domain. The lowest response rate of 94.1% was observed in Khomas region.","sampling_error_estimates":"The sampling error of a particular statistics is measured in terms of the standard error of that statistics which is the square root of the variance. The standard error is the standard deviation of the statistics which measures the variability in the estimates around the expected value. The standard error given in this report were estimated using the Taylor series Linearization method in Stata 12.1 program."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"The NHIES 2015\/2016 was conducted under the provisions of the Statistics Act No.9 of 2011.","required":"yes","form_no":"","form_uri":""}],"contact":[{"name":"Namibia Statistics Agency","affiliation":"National Planning Commision","email":"www.na.org.na","uri":""}],"cit_req":"Namiba Statistics Agency,2018. Namibia Household Income and Expenditure Survey Report.  Namibia Statistics Agency, Windhoek.","conditions":"The datasets has been anonymized and is available as a Public Use Dataset, accessible to all. It is  accessible to all for statistical and research purposes only, under the following terms and conditions:\n1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Namibia Statistics Agency. \n2. 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. \n3. 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  Namibia Statistics Agency.  \n4. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the  Namibia Statistics Agency will cite the source of data in accordance with the Citation Requirement provided with each dataset.","disclaimer":"The Namibia Statistics Agency  bears no responsibility for use of the data or for interpretations or inferences based upon public uses."}}},"schematype":"survey"}