This statistic shows the share of economic sectors in the gross domestic product (GDP) in Namibia from 2013 to 2023. In 2023, the share of agriculture in Namibia's gross domestic product was 7.72 percent, industry contributed approximately 30.02 percent and the services sector contributed about 53.4 percent.

The statistic shows the distribution of employment in Namibia by economic sector from 2013 to 2023. In 2023, 21.49 percent of the employees in Namibia were active in the agricultural sector, 16.28 percent in industry and 62.23 percent in the service sector.

Graph and download economic data for Geographical Outreach: Key Indicators Commercial Bank Branches Per 1000 Km2 for Namibia (NAMFCBODCKNUM) from 2004 to 2023 about Namibia, branches, banks, and depository institutions.

Here's the adapted article for Namibia:

Techsalerator’s Import/Export Trade Data for Namibia offers a thorough overview of international trade involving Namibian companies. This dataset provides a detailed analysis of trade transactions, documenting and categorizing imports and exports across various industries within Namibia.

To access Techsalerator’s Import/Export Trade Data for Namibia, please contact us at info@techsalerator.com or visit Techsalerator Contact with your specific requirements. We will provide a customized quote based on your needs, with delivery available within 24 hours. Ongoing access options can also be discussed.

Techsalerator's Import/Export Trade Data for Namibia integrates information from customs reports, trade agreements, and shipping records, offering businesses, investors, and trade analysts a comprehensive understanding of Namibia’s trade landscape.

Key Data Fields

• Company Name: Identifies the companies involved in trade transactions, useful for locating potential partners or competitors and tracking industry-specific trade patterns.
• Trade Volume: Details the quantity or value of goods traded, providing insights into the scale and economic impact of trade activities.
• Product Category: Specifies the types of goods traded, such as raw materials or finished products, helping to understand market demand and supply chain dynamics.
• Import/Export Country: Identifies the countries of origin or destination for traded goods, offering insights into regional trade relationships and market access.
• Transaction Date: Records the date of transactions, revealing seasonal trends and shifts in trade dynamics over time.

Top Trade Trends in Namibia

• Mining Sector Dominance: Namibia's economy is significantly driven by its mining sector, especially diamonds, uranium, and copper. These minerals are key exports and heavily influence the country's trade balance.
• Agricultural Exports: Namibia is seeing growth in agricultural exports, such as beef and fish, driven by international demand and efforts to boost the agricultural sector's contribution to trade.
• Increasing Manufacturing: The Namibian government’s focus on industrialization is gradually reshaping the export profile, with increasing exports of manufactured goods like processed foods and textiles.
• Regional Trade Integration: Namibia is part of the Southern African Development Community (SADC), which enhances regional trade relations and impacts trade policies and practices.
• Diversification Efforts: Namibia is working on diversifying its trade partners and products, exploring new markets and products beyond its traditional focus on mining and agriculture.

Notable Companies in Namibian Trade Data

• Namdeb Diamond Corporation: A joint venture between the Namibian government and De Beers, dominating the diamond mining sector and driving Namibia’s export of precious stones.
• Swakopmund Salt Refiners: A leading exporter of salt, reflecting Namibia’s growing role in the global mineral market.
• Namibia Breweries Limited: A major player in the beverage industry, exporting beer and contributing to Namibia’s trade in processed goods.
• Ohorongo Cement: A key manufacturer and exporter of cement, playing a significant role in Namibia’s construction sector and export economy.
• Fishcor: The Namibian Fishing Corporation, involved in the export of fish and seafood products, reflecting the country’s strength in marine resources.

Accessing Techsalerator’s Data

To access Techsalerator’s Import/Export Trade Data for Namibia, please reach out to us at info@techsalerator.com with your specific requirements. We will provide a tailored quote based on the number of data fields and records required, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields:

• Company Name
• Trade Volume
• Product Category
• Import/Export Country
• Transaction Date
• Shipping Details
• Customs Codes
• Trade Value

For detailed insights into Namibia’s import and export activities and trends, Techsalerator’s dataset is an essential resource for making informed and strategic decisions.

Abstract

The survey was conducted in Namibia in June 2006. Data from 329 establishments were analyzed.

The Enterprise Surveys are applied to a representative sample of firms in the non-agricultural economy. The sample is consistently defined in all countries and includes the entire manufacturing sector, the services sector, and the transportation and construction sectors. Public utilities, government services, health care, and financial services sectors are not included in the sample. Enterprise Surveys collect a wide array of qualitative and quantitative information through face-to-face interviews with firm managers and owners regarding the business environment in their countries and the productivity of their firms. The topics covered in Enterprise Surveys include the obstacles to doing business, infrastructure, finance, labor, corruption and regulation, law and order, innovation and technology, trade, and firm productivity.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for countries participating in the Enterprise Surveys is stratified by industry, firm size, and geographic region.

For stratification by industry, the main manufacturing sectors in each country in terms of value added, number of firms, and contribution to employment are selected. The retail trade sector is also included in all countries as a representative of the services sector, and depending on the size of the economy, the information technology (IT) sector is included. The rest of the universe is included in a residual stratum. In Namibia, Manufacturing sector included 106 firms, Retail sector - 110 companies and Other sectors (Residual) - 113 businesses.

Size stratification is defined the following way: small establishments (5 to 19 employees), medium establishments (20 to 99 employees), and large establishments (more than 99 employees).

Regional stratification includes the main economic regions in each country. In Namibia, Walvis Bay and Windhoek were surveyed.

Through this methodology, estimates for the different stratification levels can be calculated on a separate basis while at the same time inferences can be made for the economy as a whole, weighting individual observations by corresponding sample weights. Sample sizes for each stratification level are defined ensuring a minimum precision level of 7.5% with 95% confidence intervals for estimates with population proportions.

For more technical details on the sampling strategy, please review "Sampling Methodology" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module; - Core Questionnaire + Retail Module; - Core Questionnaire.

Most of the questions in all three questionnaires are the same.

The "Core Questionnaire" is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the "Core Questionnaire + Manufacturing Module" and the "Core Questionnaire + Retail Module." The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, informality, business-government relations, conflict resolution and legal environment, innovation and technology, and performance measures. The questionnaires also assess respondents’ opinions on what are the obstacles to firm growth and performance.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Namibia or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank's team that works in Namibia, greater insight into how the Bank's work is perceived. This is one tool the World Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Namibia. The World Bank commissioned an independent firm to oversee the logistics of this effort in Namibia.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Namibia perceive the Bank; - Obtain systematic feedback from stakeholders in Namibia regarding: · Their views regarding the general environment in Namibia; · Their overall attitudes toward the World Bank in Namibia; · Overall impressions of the World Bank's effectiveness and results, knowledge work and activities, and communication and information sharing in Namibia; and · Perceptions of the World Bank's future role in Namibia. - Use data to help inform Namibia country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Namibia

Kind of data

Sample survey data [ssd]

Sampling procedure

In April and May 2013, 314 stakeholders of the World Bank in Namibia were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President or Prime Minister; the office of a Minister; the office of a Parliamentarian; employees of a ministry, ministerial department, or implementation agency; consultants/contractors working on World Bank-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff; bilateral agencies; multilateral agencies; private sector organizations/firms; private foundations; the financial sector/private banks; NGOs; community-based organizations (CBOs); the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; and the judiciary branch.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues Facing Namibia: Respondents were asked to indicate whether Namibia is headed in the right direction, what they thought were the top three most important development priorities, and which areas would contribute most to reducing poverty and generating economic growth in Namibia.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank's effectiveness in Namibia, Bank staff preparedness to help Namibia solve its development challenges, the extent to which the Bank should seek to influence the global development agenda, their agreement with various statements regarding the Bank's work, and the extent to which the Bank is an effective development partner. Respondents were also asked to indicate the sectoral areas on which it would be most productive for the Bank to focus its resources, the Bank's greatest values and greatest weaknesses in its work, the most effective instruments in helping to reduce poverty in Namibia, with which stakeholder groups the Bank should collaborate more, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results in Namibia, the extent to which the Bank meets Namibia's needs for knowledge services and financial instruments, and the Bank's level of effectiveness across thirty-two development areas, such as economic growth.

D. The World Bank's Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult Bank knowledge work and activities, the areas on which the Bank should focus its knowledge work and activities, and to rate the effectiveness and quality of the Bank's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as working with the World Bank increasing Namibia's institutional capacity.

F. The Future Role of the World Bank in Namibia: Respondents were asked to rate how significant a role the Bank should play in Namibia's development in the near future and to indicate what the Bank should do to make itself of greater value in Namibia. Respondents were also given a list of priorities from the National Development Plan IV and asked to indicate which would benefit from the World Bank playing a leading role, which should receive little support from the Bank, and which should be left for the Government to manage.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the Bank, their Internet access, and their usage and evaluation of the Bank's websites and Development Information Centre. Respondents were asked about their awareness of the Bank's Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank's Open Data policy. Respondents were also asked about their level of agreement that they know how to find information from the Bank and that the Bank is responsive to information requests.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in Namibia, and their geographic location.

Response rate

A total of 90 stakeholders participated in the country survey (29% response rate).

Namibia NA: Net Official Flows from UN Agencies: IAEA data was reported at 0.180 USD mn in 2016. This records a decrease from the previous number of 0.210 USD mn for 2015. Namibia NA: Net Official Flows from UN Agencies: IAEA data is updated yearly, averaging 0.360 USD mn from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 0.490 USD mn in 2008 and a record low of 0.180 USD mn in 2016. Namibia NA: Net Official Flows from UN Agencies: IAEA data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Namibia – Table NA.World Bank: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor).). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), , United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), Wolrd Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), and International Labour Organization (ILO). Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;

Abstract

The survey was conducted in Namibia between April 2014 and February 2015 as part of Enterprise Surveys roll-out, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

In Namibia, data from 580 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. The establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was selected using stratified random sampling. Two levels of stratification were used in this country: industry and region. The size was not available in the sampling frame for most contacts.

Industry stratification was designed in the way that follows: the universe was stratified into manufacturing industries and two service sectors (retail and other services).

Regional stratification was defined in three regions: Windhoek/Okahandja, Walvis Bay/Swakopmund and Oshakati/Ondangwa/Ongwediva.

For the Namibia ES, a sample frame was built using data compiled from local and municipal business registries. The target sample size was 600 establishments. Establishments with undefined size were included as part of the sample frame in order to ensure a representative sample. Size information collected during the survey process can then be used to categorize these firms.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of interviews per contacted establishments was 0.26. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.12

Abstract

Namibia conducted its fifth post-Independence national labor force survey in 2008. This survey, known as the Namibia Labor Force Survey 2008 (LFS 2008), provides a wealth of information on the state of labor force in the country that is by far superior in scope and quality to any that has been available previously, in particular that it incorporated a detailed module on Informal sector and Informal employment.

The 2008 Namibia Labor Force Survey was conducted to generate all the necessary information that would provide Government with the statistical data for analysis of employment, unemployment and underemployment and hence assist in formulating well-conceived policies designed to achieve full employment and promote socio-economic development in general. The report provides a wide range of information on population size and composition, employment and unemployment and other socio-economic characteristics of the workforce.

The findings of the survey provide important statistical base for strategic policy formulation. Apart from informing the public about the state of employment in Namibia, the survey results and in particular the unemployment rate should provide a basis for the evaluation and analysis of the macro-economic policies of the country. The results will also be essential in the design and evaluation of overall government policies aimed at promoting and creating employment.

Geographic coverage

The survey was conducted nation-wide and covered all thirteen regions.

Analysis unit

• Individuals
• Households

Universe

Whole population excluding the following groups: Persons living in institutions such as hospitals, hostels, barracks and prisons.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two-stage probability 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 first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within the PSU, which was compiled just before the interviews for the survey.

The national sampling frame, which is maintained by the Central Bureau of Statistics (CBS), is based on the enumeration areas (EAs) of the 2001 Population and Housing Census and the households within the EAs. One PSU could be an EA, Part of an EA or more than one EA. The frame was stratified first by regions and then by urban/rural areas within each region. PSUs in the urban areas were further stratified into the high, middle or low levels of living according to the geographical location and the level of housing. In the regions where these levels contain large number of PSUs separate strata were made, while in the other regions a combined list of PSUs ordered by the levels was made. In the rural areas large proclaimed settlements and villages were stratified separately while the others were combined with the communal area PSUs. Communal and commercial area PSUs were grouped separately and combined to form one list for the rural strata. After all the above groupings the PSUs were geographically ordered within the strata.

Mode of data collection

Face-to-face [f2f]

Research instrument

In general the sections of the questionnaire are as follows: Section A: Identification particulars of household Section B: Information on all members of household Section C: Education questions for those aged 6 years and above Section D: Employment and labor questions for persons 10 years and above during the last 7 days (currently economically active or Labor force) Section E: Employed for those who have worked the last 7 days or who had a job but did not work coded 1 in D1 or D2 Section F: Hours worked Section G: Unemployed Section H: Employees Section I: Employers, Own Account Workers Section J: Housing conditions Section K: Control Section

Cleaning operations

The editing and coding of the questionnaires were handled in the regional centers. This arrangement, proved to be efficient as many of the errors made by the interviewers were detected and corrected by them before the questionnaires left the regional centers. A further benefit was the improvement of the processing speed since this process ran parallel to the fieldwork.

Response rate

Of 5,975 households covered countrywide, 5,246 households responded. This gives an 87.8% response rate.

Sampling error estimates

An average is in effect a ratio of two estimates, an estimate of the total and an estimate of the total number of units (households, individuals, etc.). For more details on the sampling error estimation, see the Report on page 21.

Abstract

The Household Income and Expenditure Survey (NHIES) 2009 was a survey collecting data on income, consumption and expenditure patterns of households, in accordance with methodological principles of statistical enquiries, which were linked to demographic and socio-economic characteristics of households. A Household Income and expenditure Survey was the sole source of information on expenditure, consumption and income patterns of households, which was used to calculate poverty and income distribution indicators. It also served as a statistical infrastructure for the compilation of the national basket of goods used to measure changes in price levels. It was also used for updating the national accounts.

The main objective of the NHIES 2009-2010 was to comprehensively describe the levels of living of Namibians using actual patterns of consumption and income, as well as a range of other socio-economic indicators based on collected data. This survey was designed to inform policy making at the international, national and regional levels within the context of the Fourth National Development Plan, in support of monitoring and evaluation of Vision 2030 and the Millennium Development Goals (MDG's). The NHIES was designed to provide policy decision making with reliable estimates at regional levels as well as to meet rural - urban disaggregation requirements.

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

Every week of the four weeks period of a survey round all persons in the household were asked if they spent at least 4 nights of the week in the household. Any person who spent at least 4 nights in the household was taken as having spent the whole week in the household. To qualify as a household member a person must have stayed in the household for at least two weeks out of four weeks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The targeted population of NHIES 2009-2010 was the private households of Namibia. The population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in the survey. However, private households residing within institutional settings were covered. The sample design for the survey was a stratified two-stage probability 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 PSUs were based on the 2001 Census EAs and the list of PSUs serves as the national sample frame. The urban part of the sample frame was updated to include the changes that take place due to rural to urban migration and the new developments in housing. The sample frame is stratified first by region followed by urban and rural areas within region. In urban areas, further stratification is carried out by level of living which is based on geographic location and housing characteristics. The first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within each selected PSU, which was compiled just before the interviews.

PSUs were selected using probability proportional to size sampling coupled with the systematic sampling procedure where the size measure was the number of households within the PSU in the 2001 Population and Housing Census (PHC). The households were selected from the current list of households using systematic sampling procedure.

The sample size was designed to achieve reliable estimates at the region level and for urban and rural areas within each region. However, the actual sample sizes in urban or rural areas within some of the regions may not satisfy the expected precision levels for certain characteristics. The final sample consists of 10 660 households in 533 PSUs. The selected PSUs were randomly allocated to the 13 survey rounds.

Sampling deviation

All the expected sample of 533 PSUs was covered. However, a number of originally selected PSUs had to be substituted by new ones due to the following reasons.

Urban areas: Movement of people for resettlement in informal settlement areas from one place to another caused a selected PSU to be empty of households.

Rural areas: In addition to Caprivi region (where one constituency is generally flooded every year) Ohangwena and Oshana regions were badly affected from an unusual flood situation. Although this situation was generally addressed by interchanging the PSUs between survey rounds still some PSUs were under water close to the end of the survey period.

There were five empty PSUs in the urban areas of Hardap (1), Karas (3) and Omaheke (1) regions. Since these PSUs were found in the low strata within the urban areas of the relevant regions the substituting PSUs were selected from the same strata. The PSUs under water were also five in rural areas of Caprivi (1), Ohangwena (2) and Oshana (2) regions. Wherever possible the substituting PSUs were selected from the same constituency where the original PSU was selected. If not, the selection was carried out from the rural stratum of the particular region.

One sampled PSU in urban area of Khomas region (Windhoek city) had grown so large that it had to be split into 7 PSUs. This was incorporated into the geographical information system (GIS) and one PSU out of the seven was selected for the survey. In one PSU in Erongo region only fourteen households were listed and one in Omusati region listed only eleven households. All these households were interviewed and no additional selection was done to cover for the loss in sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The instruments for data collection were as in the previous survey the questionnaires and manuals. Form I questionnaire collected demographic and socio-economic information of household members, such as: sex, age, education, employment status among others. It also collected information on household possessions like animals, land, housing, household goods, utilities, household income and expenditure, etc.

Form II or the Daily Record Book is a diary for recording daily household transactions. A book was administered to each sample household each week for four consecutive weeks (survey round). Households were asked to record transactions, item by item, for all expenditures and receipts, including incomes and gifts received or given out. Own produce items were also recorded. Prices of items from different outlets were also collected in both rural and urban areas. The price collection was needed to supplement information from areas where price collection for consumer price indices (CPI) does not currently take place.

Cleaning operations

The data capturing process was undertaken in the following ways: Form 1 was scanned, interpreted and verified using the “Scan”, “Interpret” & “Verify” modules of the Eyes & Hands software respectively. Some basic checks were carried out to ensure that each PSU was valid and every household was unique. Invalid characters were removed. The scanned and verified data was converted into text files using the “Transfer” module of the Eyes & Hands. Finally, the data was transferred to a SQL database for further processing, using the “TranScan” application. The Daily Record Books (DRB or form 2) were manually entered after the scanned data had been transferred to the SQL database. The reason was to ensure that all DRBs were linked to the correct Form 1, i.e. each household's Form 1 was linked to the corresponding Daily Record Book. In total, 10 645 questionnaires (Form 1), comprising around 500 questions each, were scanned and close to one million transactions from the Form 2 (DRBs) were manually captured.

Response rate

Household response rate: Total number of responding households and non-responding households and the reason for non-response are shown below. Non-contacts and incomplete forms, which were rejected due to a lot of missing data in the questionnaire, at 3.4 and 4.0 percent, respectively, formed the largest part of non-response. At the regional level Erongo, Khomas, and Kunene reported the lowest response rate and Caprivi and Kavango the highest.

Data appraisal

To be able to compare with the previous survey in 2003/2004 and to follow up the development of the country, methodology and definitions were kept the same. Comparisons between the surveys can be found in the different chapters in this report. Experiences from the previous survey gave valuable input to this one and the data collection was improved to avoid earlier experienced errors. Also, some additional questions in the questionnaire helped to confirm the accuracy of reported data. During the data cleaning process it turned out, that some households had difficulty to separate their household consumption from their business consumption when recording their daily transactions in DRB. This was in particular applicable for the guest farms, the number of which has shown a big increase during the past five years. All households with extreme high consumption were examined manually and business transactions were recorded and separated from private consumption.