Namibia Intercensal Demographic Survey 2016
Namibia, 2016
Namibia Statistics Agency
Last modified
January 15, 2019
Page views
10180
Documentation in PDF
Study website
Interactive tools
Identification
Title
Namibia Intercensal Demographic Survey 2016
Subtitle
NIDS
Translated title
No translation use for NIDS, the official language used was English
Countries
| Name | Abbreviation |
|---|---|
| Namibia | NAM |
idno
NIDS2016-V01
Study notes
The Namibia Intercensal Demographic Survey (NIDS) of 2016 is the first of its kind to be conducted by Namibia Statistics Agency since its establishment in April 2012, while the fisrt and second were conducted by the central Bureau of Statistics (1996 & 2006). It is a sample survey taken between the censuses, the 2011 census and the proposed 2021 census with the main objective of providing updated information on Demographic, socio-economics and housing characteristics of the population. The survey collected information from persons in households and their housing units. The NIDS coverage was limited to persons in private households excluding those in institutions.
The survey is intended to support evidence based planning and decision making in Namibia. The survey information at a national level, will provide crucial information for development planning and programme implementation. While at the international level, the information will be used to monitor progress towards Namibia's achievement of international targets, particularly the Sustainable Development Goals (SDGs).
The population characteristics include spatial distribution, age and sex composition, marital status, education, literacy, orphan hood and disability. The household and housing conditions include household size, housing amenities, ownership and the quality of housing.
The sample design was a stratified two-stage cluster sample, where the first stage units were the PSUs and the second stage units were the households.
The data processing methodology that was used is the Computer Assisted Personal Interview method (CAPI)
The survey is intended to support evidence based planning and decision making in Namibia. The survey information at a national level, will provide crucial information for development planning and programme implementation. While at the international level, the information will be used to monitor progress towards Namibia's achievement of international targets, particularly the Sustainable Development Goals (SDGs).
The population characteristics include spatial distribution, age and sex composition, marital status, education, literacy, orphan hood and disability. The household and housing conditions include household size, housing amenities, ownership and the quality of housing.
The sample design was a stratified two-stage cluster sample, where the first stage units were the PSUs and the second stage units were the households.
The data processing methodology that was used is the Computer Assisted Personal Interview method (CAPI)
Kind of data
Sample survey data [ssd]
Unit of analysis
Individual/Household; National; Urban,Rural and regions
Version
Version
NIDS2016-V1
Version date
2017-08-14
Version notes
This is version 1.
Scope
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| Collected information on individual household members | Person/individual characteristics | www.nsa.org.na |
| Collected information of household and housing characteristics | Household and housing characteristics | www.nsa.org.na |
Keywords
| keyword | URI |
|---|---|
| All interviews must relate to SRN. The reference night was the night of 30 October 2016. | |
| A private household is defined as one or more persons, related or unrelated, who live together in one (or part of one) or more than one dwelling unit and have common catering arrangements and answerable to the same head of household. A person who lives alone and caters for himself/herself forms a one-person household. | |
| Refers to all people who were actually present in the household on the survey reference night, including visitors, employees on night shift and resident domestic servants and their families. | |
| A de-facto method enumerates all persons found within the borders of a particular country at a particular point in time (i.e. SRN). For example every person is enumerated at a place or household where he/she spent the SRN. This is the approach that has been adopted for 2016 NIDS. |
Coverage
Geographic coverage
Information is at National, Urban, Rural and Regional levels.
Unit of analysis
Individual/Household; National; Urban,Rural and regions
Universe
Namibian private households and it's household members. Iinstitutions (institutional population) were excluded from this survey. However, private households within institutions were covered.
Producers and sponsors
Producer(s)
| Name | Affiliation | Role |
|---|---|---|
| Namibia Statistics Agency | Ministry of Economic Planning and National Planning Commission | Producers of statistics |
Funding agencies
| Name | Abbreviation | Role |
|---|---|---|
| Government of the Republic of Namibia | GRN | Finacial Assistance |
| United Nation Population Fund | UNFPA | Finacial Assistance |
Other acknowledgement(s)
| Name | Affiliation | Role | |
|---|---|---|---|
| Namibia Statistics Agency | Contributed to make NIDS as well as the production of survey report a success | ||
| Stakeholders (ministries and research institutions) | Contributed by making inputs on the types of information to collect data on |
Sampling
Sampling procedure
The sample design was a stratified two-stage cluster sample, where the first stage units were the PSUs and the second stage units were the households. Sample sizes were determined to give reliable estimates of the population characteristics at the regional level (i.e. lowest domain of estimation). A total of 12480 households constituted the sample from all 14 regions and from a sample of 624 PSUs.
Response rate
98.1%
Weighting
Population figures were estimated by applying calibrated weight while the household figures were estimated by applying the design weights.
The design/base weight
Design weights were calculated based on the probabilities of selection at each stage. The first stage weights were calculated using the sample selection information from the sampling frame and the second stage weights were calculated based on the sample selection information of the household listing.
Weight Calibration
Weight calibration is a post survey weight adjustment method that is used when auxiliary information related to the population of interest is available. This auxiliary information generally is in the form of population totals for various categories of the unit of interest e.g. age groups, sex of respondents etc. Assuming the auxiliary information is true and correct, this information can be used to benchmark the survey estimates to sum up to these known population totals (within each categories) but more importantly, will improve the quality of the survey estimates. Weight calibration is generally applied as a final step in the development of the survey weights at the person level. The weight calibration was achieved using a GREGWT macro implemented in the Statistical Analysis Software (SAS) package.
The design/base weight
Design weights were calculated based on the probabilities of selection at each stage. The first stage weights were calculated using the sample selection information from the sampling frame and the second stage weights were calculated based on the sample selection information of the household listing.
Weight Calibration
Weight calibration is a post survey weight adjustment method that is used when auxiliary information related to the population of interest is available. This auxiliary information generally is in the form of population totals for various categories of the unit of interest e.g. age groups, sex of respondents etc. Assuming the auxiliary information is true and correct, this information can be used to benchmark the survey estimates to sum up to these known population totals (within each categories) but more importantly, will improve the quality of the survey estimates. Weight calibration is generally applied as a final step in the development of the survey weights at the person level. The weight calibration was achieved using a GREGWT macro implemented in the Statistical Analysis Software (SAS) package.
Data Collection
Dates of collection
| Start | End | Cycle |
|---|---|---|
| 2016-10-17 | 2016-11-11 |
Time period(s)
| Start | End | Cycle |
|---|---|---|
| 2016-10-17 | 2016-11-11 |
Mode of data collection
Face to face interviews using Computer Assisted Persosnal Interviews (CAPI).
Data collection supervision
The main survey consisted of field teams operating within a region under the regional supervisor a position held by the NSA Regional Statisticians (RS).
Each regional supervisor was supported by an IT technician who provided IT support to the regional field team. There were in total 15 IT technicians employed during the survey field work period, 14 for the regions and one IT technician based at the NSA head office to oversee data transmission and management.
The IT Technicians worked closely with Regional supervisors and also assisted them with administrative issues and field logistics.
The field teams consisted of a team supervisor and two interviewers. Field personnel were recruited from their own areas since they needed to be familiar with the local terrain/locality and to facilitate interviews in local languages. In Total 491 field staffs were deployed for the fieldwork for a period of approximately one month (30 days). The work plan was designed to include the first two weeks for listing of private households within the selected PSUs and the last two weeks to administer the questionnaire to the sampled 20 private households per PSU.
Field visits were made by staff from the head office to oversee the data collection process (interviews), feedback were given to the enumerators through the team supervisors.
With regard to ensuring the quality of the data, edits checks were built in CAPI to verify the data that is being entered by enumerators.
Each regional supervisor was supported by an IT technician who provided IT support to the regional field team. There were in total 15 IT technicians employed during the survey field work period, 14 for the regions and one IT technician based at the NSA head office to oversee data transmission and management.
The IT Technicians worked closely with Regional supervisors and also assisted them with administrative issues and field logistics.
The field teams consisted of a team supervisor and two interviewers. Field personnel were recruited from their own areas since they needed to be familiar with the local terrain/locality and to facilitate interviews in local languages. In Total 491 field staffs were deployed for the fieldwork for a period of approximately one month (30 days). The work plan was designed to include the first two weeks for listing of private households within the selected PSUs and the last two weeks to administer the questionnaire to the sampled 20 private households per PSU.
Field visits were made by staff from the head office to oversee the data collection process (interviews), feedback were given to the enumerators through the team supervisors.
With regard to ensuring the quality of the data, edits checks were built in CAPI to verify the data that is being entered by enumerators.
Questionnaires
The NID questionnaire had the following sections:
Section A: Identification section of the household
Section B: Information on all members of the household
Section C: Child Protection, for all persons aged 0 - 18 years
Section D: Early Childhood Development for children aged 0 to 5 years and Literacy and Education for persons aged 6 years and above
Section E: Labour Force for all household members that are aged 8 years and above
Section F: Fertility information for all women aged 8 - 54 years
Section G: Mortality/Deaths in the household in the last 12 month
Section H: Housing Characteristics for each household
Section A: Identification section of the household
Section B: Information on all members of the household
Section C: Child Protection, for all persons aged 0 - 18 years
Section D: Early Childhood Development for children aged 0 to 5 years and Literacy and Education for persons aged 6 years and above
Section E: Labour Force for all household members that are aged 8 years and above
Section F: Fertility information for all women aged 8 - 54 years
Section G: Mortality/Deaths in the household in the last 12 month
Section H: Housing Characteristics for each household
Data collector(s)
| Name | Abbreviation | Affiliation |
|---|---|---|
| Namibia Statistics Agency | NSA | Ministry of Economic Planning and National Planning Commission |
Data Processing
Data editing
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's 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.
Numerous batch programs were developed to run through the data to sort and fix inconsistencies. Main programs developed were:
1. Case specific edits program - this program allows to implement edits which are specific to a case (household), these edits are provided by subject matter after checking/ investigating each household.
2. General edits program - this program fix any data inconsistency found during the run. Standardize data program - removes deleted persons and ensure that the head of household is on the first row for each household. In the end, only valid person lines are remaining in the data file.
3. Recode variables program - this program recode variable values from the notes (Other specify) to different values based on the input from subject matter (SM). An excel sheet is provided to SM to put the correct value for each case and variable for recoding, then program convert the excel sheet to CSpro data file and implements the changes.
4. Add weight program - the weight is also applied through the CSpro post data processing program. Sampling team design weight (both individual and household) based on the completeness of survey interviews by PSU. Once the weight is applied to the dataset Data Processing (DP) runs the final Merge flatten program, which convert and flatten the multi select answers into more human readable data.
5. The final step is to drop the person identification information such as the person name from the dataset, this is done via an Anonymize data program.
Numerous batch programs were developed to run through the data to sort and fix inconsistencies. Main programs developed were:
1. Case specific edits program - this program allows to implement edits which are specific to a case (household), these edits are provided by subject matter after checking/ investigating each household.
2. General edits program - this program fix any data inconsistency found during the run. Standardize data program - removes deleted persons and ensure that the head of household is on the first row for each household. In the end, only valid person lines are remaining in the data file.
3. Recode variables program - this program recode variable values from the notes (Other specify) to different values based on the input from subject matter (SM). An excel sheet is provided to SM to put the correct value for each case and variable for recoding, then program convert the excel sheet to CSpro data file and implements the changes.
4. Add weight program - the weight is also applied through the CSpro post data processing program. Sampling team design weight (both individual and household) based on the completeness of survey interviews by PSU. Once the weight is applied to the dataset Data Processing (DP) runs the final Merge flatten program, which convert and flatten the multi select answers into more human readable data.
5. The final step is to drop the person identification information such as the person name from the dataset, this is done via an Anonymize data program.
Data access
Access authorities
| Name | Affiliation | URI | |
|---|---|---|---|
| Namibia Statistics Agency | Ministry of Economic Planning and National Planning Commission | info@nsa.org.na | www.nsa.org.na |
Access conditions
The dataset 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 Namibia Statistics Agency. 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 Namibia Statistics Agency.
4. No attempt will be made to produce links among datasets provided by the Namibia Statistics Agency, or among data from the Namibia Statistics Agency 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 Namibia Statistics Agency will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the Namibia Statistics Agency.
The original collector of the data, the Namibia Statistics Agency, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
1. 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. 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 Namibia Statistics Agency.
4. No attempt will be made to produce links among datasets provided by the Namibia Statistics Agency, or among data from the Namibia Statistics Agency 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 Namibia Statistics Agency will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the Namibia Statistics Agency.
The original collector of the data, the Namibia Statistics Agency, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Citation requirements
Namibia Statistics Agency. Namibia 2016 Intercensal Demographic Survey [dataset]. Version 1.0, Windhoek: Namibia Statistics Agency [producer and distributor], September 2017.
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.
Copyrights
Copyright, NSA 2017
contacts
Contact(s)
| Name | Affiliation | URI | |
|---|---|---|---|
| Namibia Statistics Agency | Ministry of Economic Planning and National Planning Commission | info@nsa.org.na | www.nsa.org.na |