Labour Force Survey 2008
Namibia, 2008
Created on
Apr 25, 2019
Last modified
Apr 25, 2019
Page views
21
Identification
Survey ID Number
NAM_2008_LFS_v01_M
Title
Labour Force Survey 2008
Country
| Name | Country code |
|---|---|
| Namibia | NAM |
Study type
Labor Force Survey [hh/lfs]
Abstract
The Namibia Labour Force Survey 2008 provides basic data required for policy making at national and regional levels as well as for different sectors.
The two main objectives for the survey were:
• To measure the extent of available and unused labour time and human resources for the purpose of macro-economic monitoring and human resources development planning.
• To measure the relationship between employment and other socio-economic characteristics for purposes of formulating and monitoring employment policies and programmes, income generating and monitoring schemes, vocational training and other similar programmes.
More specifi cally, the survey was designed to provide:
a) Basic information on the size and structure of the country’s work force.
b) Basic elements for measuring the labour supply as well as its input and the extent to which the available human resources are utilized in the production process of the economy.
c) A prospective basis for projections of the economically active population and its components for socio-economic planning.
d) A basis for research in many areas ranging from testing labour market segmentation theories to formulating demographic models.
e) To the public, information on the employment situation of the country. When properly disaggregated by geographic area, the data may provide information on the situation in local markets especially on the number of persons available in specifi c occupational categories.
f) To the business community, useful indicators on the future course of the economy.
g) Basic information on the size of the informal economy.
The two main objectives for the survey were:
• To measure the extent of available and unused labour time and human resources for the purpose of macro-economic monitoring and human resources development planning.
• To measure the relationship between employment and other socio-economic characteristics for purposes of formulating and monitoring employment policies and programmes, income generating and monitoring schemes, vocational training and other similar programmes.
More specifi cally, the survey was designed to provide:
a) Basic information on the size and structure of the country’s work force.
b) Basic elements for measuring the labour supply as well as its input and the extent to which the available human resources are utilized in the production process of the economy.
c) A prospective basis for projections of the economically active population and its components for socio-economic planning.
d) A basis for research in many areas ranging from testing labour market segmentation theories to formulating demographic models.
e) To the public, information on the employment situation of the country. When properly disaggregated by geographic area, the data may provide information on the situation in local markets especially on the number of persons available in specifi c occupational categories.
f) To the business community, useful indicators on the future course of the economy.
g) Basic information on the size of the informal economy.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Household
- Individual
- Individual
Scope
Notes
The 2008 Namibia Labour Force Survey covered the following topics:
- Demographic characteristics: age, sex, marital status, nationality, relationship to household head
- Main labour related characteristics: employment, unemployment, underemployment, hours of work, employment in informal sector, informal employment, absence from work
- Other labour related characteristics: industry, occupation, status in employment, institutional sector (public/private), size of establishment, full time/part time status, permanency of the job, type of workplace, duration of employment, existence of more than one job, characteristics of the second job(s), previous working experience, characteristics of the last job, methods of looking for work, reasons for not being in the labour force
- Demographic characteristics: age, sex, marital status, nationality, relationship to household head
- Main labour related characteristics: employment, unemployment, underemployment, hours of work, employment in informal sector, informal employment, absence from work
- Other labour related characteristics: industry, occupation, status in employment, institutional sector (public/private), size of establishment, full time/part time status, permanency of the job, type of workplace, duration of employment, existence of more than one job, characteristics of the second job(s), previous working experience, characteristics of the last job, methods of looking for work, reasons for not being in the labour force
Coverage
Geographic Coverage
National
Universe
Whole population excluding the following groups: Persons living in institutions such as hospitals, hostels, barracks and prisons.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Ministry of Labour and Social Welfare (MLSW) | Government of Republic of Namibia |
| Central Bureau of Statistics (CBS) | National Planning Commission, Government of Republic of Namibia |
Sampling
Sampling Procedure
Sample design
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 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 Master Sample Frame and stratification
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 stratifi ed 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 stratifi ed 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.
Sample size and the master sample
Sample size was determined in order to make reliable estimates at the National urban/ rural and region level. This requirement was satisfied by the Master Sample, which is designed by the CBS to be used for number of surveys and hence was used for this survey also. This is actually the first stage sample, which consists of 239 PSUs. The number of households per PSU was fixed at 25. Additions to the number of sample households within the PSU would not add much to the improvement of the precision but would only increase the cost. The final sample consisted of 5,975 households in 239 PSUs.
Sample allocation
The PSUs were first allocated to the major domains of estimation (regions) proportional to their population sizes (Number of households). Then further allocation was carried out for separate strata within the major domains.
Note: See Chapter 2 (in final survey report) for the details of the sample design.
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 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 Master Sample Frame and stratification
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 stratifi ed 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 stratifi ed 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.
Sample size and the master sample
Sample size was determined in order to make reliable estimates at the National urban/ rural and region level. This requirement was satisfied by the Master Sample, which is designed by the CBS to be used for number of surveys and hence was used for this survey also. This is actually the first stage sample, which consists of 239 PSUs. The number of households per PSU was fixed at 25. Additions to the number of sample households within the PSU would not add much to the improvement of the precision but would only increase the cost. The final sample consisted of 5,975 households in 239 PSUs.
Sample allocation
The PSUs were first allocated to the major domains of estimation (regions) proportional to their population sizes (Number of households). Then further allocation was carried out for separate strata within the major domains.
Note: See Chapter 2 (in final survey report) for the details of the sample design.
Weighting
Weighting
Sample weights were calculated based on the probabilities of selection at each stage. First stage weight was calculated using the sample selection information from the sampling frame. In the case of the second stage some households out of the selected 25 households in a PSU did not participate in the survey due to refusals or non-contact etc. Such non-responding households were not too large in number and there was no evidence to suggest that the excluded households were quite different from the responding ones. Hence it was assumed that the non-responding households were randomly distributed and the second stage weights were adjusted accordingly. The result of this adjustment was that the responding households were used instead of the selected 25 households in the calculation of the second stage weights. The final sample weight was the product of the first and the second stage weights. These final sample weights were incorporated into the database so that raising the sample data would be automatically carried out when the tables were produced.
Sample weights were calculated based on the probabilities of selection at each stage. First stage weight was calculated using the sample selection information from the sampling frame. In the case of the second stage some households out of the selected 25 households in a PSU did not participate in the survey due to refusals or non-contact etc. Such non-responding households were not too large in number and there was no evidence to suggest that the excluded households were quite different from the responding ones. Hence it was assumed that the non-responding households were randomly distributed and the second stage weights were adjusted accordingly. The result of this adjustment was that the responding households were used instead of the selected 25 households in the calculation of the second stage weights. The final sample weight was the product of the first and the second stage weights. These final sample weights were incorporated into the database so that raising the sample data would be automatically carried out when the tables were produced.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2008 | 2008 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Supervision was exercised at different levels. At the first level, the team supervisor was the immediate supervisor to the interviewers. At the next level was the regional supervisor who was in charge of all the fieldwork in the region and the editing and coding staff. Labour officers of the Ministry of Labour and Social Welfare (MLSW) were appointed as regional supervisors. Finally, the national supervisor who was appointed by the Ministry of Labour and Social Welfare was an overall supervisor for all activities within the allocated region.
A one-week training course was held in Windhoek for the team and regional supervisors. The training of interviewers and coders took place at five different centers at the same time to ensure uniformity. The team supervisors and the regional supervisors also assisted during the one-week training of interviewers.
A one-week training course was held in Windhoek for the team and regional supervisors. The training of interviewers and coders took place at five different centers at the same time to ensure uniformity. The team supervisors and the regional supervisors also assisted during the one-week training of interviewers.
Data Collection Notes
With 25 sample households in each PSU, it was decided to establish teams consisting of four interviewers and a supervisor to handle the workload. As a rule, five PSUs were allocated to each team. However, in cases where travel distances between and within PSUs were too large, only three or four PSUs were allocated to the team. In total 52 teams were established. There were thus 52 supervisors and 208 interviewers required.
Questionnaires
Questionnaires
The questionnaire was designed by the Technical Committee of the Ministry of Labour and Social Welfare in consultation with various users and producers of labour statistics. The questionnaire consists of the following sections:
Section A: Identification particulars of the household, including its geographical location
Section B: Information on all persons who were members of the household during the survey collection
Section C: Information on the education for those aged 6 years and above
Section D: Information on the current activities of the adult population 10 years and above
Section E: Information on employed household members (who have worked the last 7 days or who had a job but did not work)
Section F: Information on hours worked (who have worked the last 7 days or who had a job but did not work)
Section G: Information on unemployment (who have not worked during the last 7 days, had no job and were ready to work)
Section H: Employees
Section I: Employers, own account workers
Section J: Housing conditions
Section K: Control information
Section A: Identification particulars of the household, including its geographical location
Section B: Information on all persons who were members of the household during the survey collection
Section C: Information on the education for those aged 6 years and above
Section D: Information on the current activities of the adult population 10 years and above
Section E: Information on employed household members (who have worked the last 7 days or who had a job but did not work)
Section F: Information on hours worked (who have worked the last 7 days or who had a job but did not work)
Section G: Information on unemployment (who have not worked during the last 7 days, had no job and were ready to work)
Section H: Employees
Section I: Employers, own account workers
Section J: Housing conditions
Section K: Control information
Data Processing
Data Editing
Manual processing was done in the field. Therefore the information from the field was ready for data capture. Around 20 data entry operators were recruited and worked in different shifts for about two months. The data entry operators were temporary staff. The Census and Survey Processing System (CSPro) software, a US Census Bureau product, was used for data capture. SPSS software was used for data cleaning, tabulation and analysis together with other packages such as the Microsoft Excel.
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.
Substantial coding inconsistencies were nevertheless detected in the analysis stage. Since these mainly concerned the occupation and industry of employed persons, it was possible to correct them using the answers provided to related questions. The inconsistencies were primarily due to the insufficient time allocated for the training of coders, and perhaps also to inadequate time for coding itself.
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.
Substantial coding inconsistencies were nevertheless detected in the analysis stage. Since these mainly concerned the occupation and industry of employed persons, it was possible to correct them using the answers provided to related questions. The inconsistencies were primarily due to the insufficient time allocated for the training of coders, and perhaps also to inadequate time for coding itself.
Access policy
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:
Namibia Ministry of Labour and Social Welfare (MLSW). Namibia Labour Force Survey 2008. Ref. NAM_2008_LFS_v01_M. Dataset downloaded from [source] 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:
Namibia Ministry of Labour and Social Welfare (MLSW). Namibia Labour Force Survey 2008. Ref. NAM_2008_LFS_v01_M. Dataset downloaded from [source] 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_NAM_2008_LFS_v01_M_WB
Producers
| Name | Abbreviation | Role |
|---|---|---|
| World Bank, Development Economics Data Group | DECDG | Documentation of the study |
Date of Metadata Production
2013-03-13
DDI Document version
Version 01 (March 2013)