KEN_1998_ILFS_v01_M
Integrated Labour Force Survey 1998-1999
Second Round
Name | Country code |
---|---|
Kenya | KEN |
Labor Force Survey [hh/lfs]
The 1998/99 Integrated Labour Force Survey (ILFS) was the first of its kind to integrate three related surveys (labour force, informal sector and child labour modular surveys) into a single cost-effective survey. It was conducted over the whole country on the household-based NASSEP III sample frame, and covered 11,049 households giving a response rate of 86.2 per cent. As such, the survey collected a wide range of representative information that can be used in the design, implementation, monitoring and evaluation of various policies and programmes. In particular, it provides indicators such as school enrolments rates, housing conditions, access to amenities and facilities, income and expenditures, unemployment rates, and income and expenditure levels which should provide invaluable inputs into the monitoring and evaluation of the economic reforms and poverty reduction programmes that are being implemented by the Government.
The key objectives of the survey were to update data on the labour force, determine the size and output of the informal sector, and estimate the extent of child labour. A rich data bank has been created as a by-product of data processing exercise, which can be used to carry out further analysis of the information collected by the survey.
In designing and implementing the survey, CBS worked closely with other stakeholders through the Inter-Ministerial Steering Committee (IMSC) that was formed to provide overall guidance on the implementation of the survey. The committee was composed of representatives from Ministry of Labour and Human Resource Development, Ministry of Education Science and Technology, and the Macro Planning and Human Resources and Social Services departments in the Ministry of Finance and Planning. A Technical Working Group (TWG) was formed as the survey's secretariat that undertook day-to-day activities on the implementation of the survey.
Also, the wealth of data collected by the 1998/99 ILFS should be used for in-depth analysis, especially on the informal sector module data.
Sample survey data [ssd]
Household, Individual
The Kenya Integrated Labour Survey covered the following topics:
Topic | Vocabulary |
---|---|
Labor & Social Protection | World Bank |
Children & Youth | World Bank |
National coverage
The survey covered all de jure household members, all persons above 5 years
Name | Affiliation |
---|---|
Kenya National Bureau of Statistics | Ministry of State for Planning National Development and Vision 2030 |
Name | Role |
---|---|
International Labour Organisation | Financial support |
Name | Role |
---|---|
International Programme for Elimination of Child Labour | Technical and financial assistance during the design stage |
United Nations Development Fund | Funded the data collection phase |
The World Bank | Funded the data processing and report writing phases |
The sample for the 1998/99 Integrated Labour Force Survey (ILFS) was drawn from the NASSEP III master sample frame, which was developed from the population count of the 1989 Population and Housing Census. The frame covered all the districts (excluding Turkana, Marsabit, and Samburu) that were in existence during its inception in 1989. The master sample frame, which is a two stage stratified cluster design, is multi-purpose for household-based surveys.
In the design of NASSEP III, the Enumeration Areas (EAs) of the 1989 population census were the Primary Sampling Units (PSUs). The PSUs were selected using the Probability Proportional to Size (PPS) method, and were then segmented into smaller units of about 100 households, constituting one Measure of Size (MOS). One segment from each PSU was selected randomly for the creation of a "cluster". The frame was further categorised into urban and rural sub-strata. The urban component comprised 329 clusters (of which 209 are operational) spread over 63 urban centres, with population 10,000 and over, including all district headquarters with the exception of Marsabit, Mararal and Lodwar towns. The rural component of the frame had a total of 952 clusters (of which 930 are operational) spread over 34 districts as constituted in 1989, but excluded Turkana, Marsabit, Samburu and the North Eastern districts of Wajir, Garissa and Mandera. In creating the rural component of the frame, each of the 34 districts covered was treated as a stratum. The allocation of the PSUs to the rural districts was done proportionately to the population size. The allocation of the clusters to the districts varied between 12 and 36 clusters, with sparsely populated districts assigned fewer clusters than densely populated districts.
Sample Size Determination
The child labour phenomenon was used in determining the appropriate sample size, so as to increase the chances of capturing working children in sampled households since the child labour incidence is a rare event. First, it was estimated that children aged 5-17 years constituted 37.0 percent of the listings of 1996, and also in the December 1998 population projections. Also, the proportion of working children falling in this age interval was estimated to lie between 15 percent and 19 percent (using the results of the 1989 Population and Housing Census). Using a margin of error of 5 percent and a confidence level of 95 percent with an adjustment for the design effect of 2.0, a sample size of 54,000 persons was estimated for the survey. Working with average household size of 4.2 persons, the sample size translated into 12,814 households, which were selected by a systematic selection of every tenth household in each cluster. Where the calculated number fell below 10 households, a minimum of 10 households was taken in all such cases. The resultant sample size was observed to be sufficient to provide national and provincial estimates.
The survey, as stated earlier, covered 1,109 clusters out of the 1,139 selected clusters, giving 97.4 percent response rate. The remaining 30 clusters constituting 2.6 per cent were not covered, mainly due to inaccessibility caused by flooding and insecurity prevailing in these clusters.
The survey, as stated earlier, covered 1,109 clusters out of the 1,139 selected clusters, giving 97.4 percent response rate. The remaining 30 clusters constituting 2.6 per cent were not covered, mainly due to inaccessibility caused by flooding and insecurity prevailing in these clusters.
At household level, 11,049 out of 12,814 selected households participated in the survey, giving 86.2 percent response rate. The lowest response rate was recorded in Garissa district while the highest response rates were observed in Mandera and Embu districts. The rural component had a higher response rate of 87.5 percent, that is 9,111 respondents out of a total of 10,413 selected households. In the urban areas there was a response rate of 80.7 percent based on 1,938 households that responded from 2,401 selected households. Among the provinces, the lowest response rate was experienced in North Eastern where 74.6 percent while Eastern Province had the highest response rate of 92.7 percent.
As to the weighting procedures, weighting of the sample data was done because the selection process of the sample was not self-weighting; and in the accompanying computation process, adjustment was done for cluster and household non-response. In addition, the adjustments took into consideration both the listed populations in the clusters and population growth.
See Appendix I of the report for a complete description of weighting.
The ILFS questionnaire consisted of three modules with a total of thirteen forms:
(i) The labour force module consisting of forms LFS/I/98 through LFS/IV/98, which solicited labour force particulars;
(ii) The informal sector module consisting of forms LFS/V/98 through LFS/VII/98, which was used to solicit information on informal sector businesses, and
(iii) The child labour module consisting of forms LFS/VIII through LFS/XIII/98, by which information was collected on the child labour phenomenon.
Start | End |
---|---|
1998-12-21 | 1999-01-30 |
Name | Affiliation |
---|---|
Kenya National Bureau of Statistics | Ministry of State for Planning National Development and Vision 2030 |
Training for field staff was undertaken in two tiers: 6 days training of trainers, which was conducted at a central point; and a week's training of enumerators in 8 training venues spread over the country.
The fieldwork was undertaken in 21 consecutive days during the months of December 1998 and January 1999. About 250 enumerators who are permanent employees of CBS based in each of the surveyed districts collected the data. Fifty District Statistical Officers (DSOs) supervised data collection at district level. In addition, 32 district coordinators were constituted to coordinate the survey in each of the districts; while the 250 CBS field enumerators, who are permanent employees of CBS based in each of surveyed districts, manned the NASSEP clusters and collected the data.
The enumerators had a range of responsibilities, which included:
Locating the sampled households within the assigned clusters by use of cluster maps;
Establishing rapport with respondents to gain their consent to be interviewed;
Conducting personal interviews and recording answers using the questionnaire by following instructions given during their training and elaborated in the enumerators' reference manual;
Checking the completed questionnaires to ensure that all questions are asked and the responses are neatly and legibly recorded;
Returning to the respondents where necessary to clarify suspect entries and for appointments to finish uncompleted interviews;
Preparing debriefing notes for the supervisor on the problems encountered; and
Forwarding all completed questionnaires to the supervisor or the DSO.
The field staff in the districts where the survey was conducted undertook the initial editing of the questionnaires. The edited questionnaires were then forwarded to the CBS head office for further editing and processing using FoxPro 2.0 software. Thereafter the data were verified and validated up to the analysis stage to identify and correct invalid codes, duplicates, missing variables and other internal inconsistencies.
It is observed that estimates based on sample survey data are potentially subject to two types of errors, namely, sampling and non-sampling errors. The latter are not easy to control since they arise from factors external to the sample design, which include coding and data entry errors among others. Sampling errors are however controlled through the design of the sample and are measured by use of variances. In the ILFS, the stratified cluster design was used. This is a complex design and its variance estimates were based on the ultimate cluster method for variance estimation. The Cenvar program in the IMPS was used in the estimation of the variances of some selected variables. The standard error estimates in Appendix I were therefore obtained and reflect the situation of the data.
The variances of the parameters were either for the totals or ratios. (For the fomulae kindly check the report)
It is observed from the estimates of the variances that most of the estimates have consistently small standard errors, with the exception of categories with very few observations. Consequently, it was found that the coefficient of variation (CV) for most of the variable were in the neighbourhood of 10 percent or below with exception of North Eastern Province which had a very small sample in the survey, or categories of the population with rare occurrence such as people with university level education or ages exceeding 50 years in some provinces, which had very few observations.
The design effect in most cases was not high with the exception of the categories having small observations in the North Eastern Province. It is, therefore, observed that estimates based on the ILFS are fairly reliable and provide a good reflection of the employment situation and associated characteristics in the country.
Name | URL | |
---|---|---|
Director | http://www.knbs.co.ke | data@knbs.co.ke |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
---|---|
yes | Confidentiality of respondents is guaranteed by Articles ..... to ....... of the National Statistics Act of [date]. Before being granted access to the dataset, all users have to formally agree: 1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor. 2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. 3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor. |
The dataset has been anonymized and is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
The original collector of the data, the Kenya National Bureau of Statistics, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Use of the dataset must be acknowledged using a citation which would include:
Exemple:
Kenya National Bureau of Statistics. Integrated Labour Force Survey 1998-1999. Ref. KEN_1998_ILFS_v01_M. Dataset downloaded from [source] on [date].
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.
Name | Affiliation | URL | |
---|---|---|---|
Director | Kenya National Bureau of Statistics | director@knbs.co.ke | http://www.knbs.co.ke |
DDI_KEN_1998_ILFC_v02_M
Name | Affiliation | Role |
---|---|---|
Kenya National Bureau of Statistics | Ministry of Planning and National Development | Documentation of the study |
Accelerated Data Program | International Household Survey Network | Review of the metadata |
2013-05-31
Version 02 (October 2013). Edited version based on Version 1.1 (November 2008) DDI that was done by Kenya National Bureau of Statistics and reviewed by Accelerated Data Program, International Household Survey Network.