Labor Force Survey, LFS 2013-2014
Yemen, 2013 - 2014
Economic Research Forum, ILO Regional Office for Arab States, Central Statistical Organization
Identification
Survey ID Number
YEM_LFS_2013_HD_V1
Title
Labor Force Survey, LFS 2013-2014
Country
| Name | Country code |
|---|---|
| Yemen | YEM |
Study type
Labor Force Survey [hh/lfs]
Series Information
The Labour Force Survey (LFS) 2013-2014 is the second such survey that has been carried out in the last 15 years in Yemen. Similar to the first survey in 1999, the LFS 2013-2014 was conducted by the Central Statistical Organization with assistance from the International Labour Office.
Abstract
THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL STATISTICAL ORGANIZATION OF YEMEN (CSO)
The primary objective of LFS 2013-2014 was to provide current data on the employment and unemployment situation at national and governorate level using the preliminary version of the new standards concerning statistics of work, employment and labour underutilization on adopted by the 19th International Conference of Labour Statisticians (Geneva, October 2013).
---> The survey was then designed to meet five main measurement objectives as follows:
1- To provide current data on the number of employed, unemployed, and underemployed, and their demographic and social characteristics, including the size of women's participation in economic activity with a view to future policies in expanding their participation in the labour market.
2- To collect data on qualifications of the labour force and participation in training programmes of the youth population and other data requirements for improving the performance of employers through knowledge on the levels of skill available to them.
3- To measure the volume and characteristics of labour migration of Yemenis outside the country.
4- To provide information on the amount of wages and employment-related income in different occupations, branches of economic activity and sectors of employment.
5- To collect appropriate data for evaluating the microfinance projects funded through the Social Fund for Development.
Given the extent and diversity of data requirements, the survey was designed to spread over a one-year period, built around the five objectives of the survey. The core labour force survey was conducted throughout the four quarters of the survey period and incorporated the measurement of income from employment along the conventional items of data collection. Data on qualifications and participation in training was collected on the third quarter and on labour migration on the second quarter of the survey programme. Data collection on microfinance was undertaken as a separate survey over the four quarters.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
1- Household/family.
2- Individual/person.
2- Individual/person.
Version
Version Description
V1: A cleaned and a harmonized version of the survey dataset, produced by the Economic Research Forum for dissemination.
Production
Date
2017-09
Version Notes
All documentation available for the original survey provided by the Statistical Agency, and for the harmonized datasets produced by the Economic Research Forum, are published, along with a copy of all occupations and economic activities used during the harmonization process.
However, as far as the datasets are concerned, the Economic Research Forum produces and releases only the harmonized versions in both SPSS and STATA formats.
However, as far as the datasets are concerned, the Economic Research Forum produces and releases only the harmonized versions in both SPSS and STATA formats.
Scope
Notes
Household: Includes geographical characteristics, household composition, LFS classification of household members, head's and spouse's characteristics, dwelling characteristics and ownership of durables.
Individual: Includes demographics, nationality and immigration, education, current labor status, main job, secondary job and last held job characteristics, wages and incomes, unemployment characteristics and inactivity reason(s).
Individual: Includes demographics, nationality and immigration, education, current labor status, main job, secondary job and last held job characteristics, wages and incomes, unemployment characteristics and inactivity reason(s).
Topics
| Topic | Vocabulary |
|---|---|
| Demographics | ERF |
| Education | ERF |
| Nationality and immigration | ERF |
| Labor Force | ERF |
| Employment | ERF |
| Unemployment | ERF |
| Wages and incomes | ERF |
Coverage
Geographic Coverage
Survey operations were carried out in all governorates except parts where recent events have disturbed the normal course of economic activity. In these circumstances, special procedures were used for compensation, either through the replacement of those areas with other areas having otherwise similar characteristics in the respective strata or through the adjustment of the sampling weights for missing values. There were 14 such cases, 5 each in quarters 1 and 4, and 2 each in quarters 2 and 3.
Universe
The labour force survey covered the civilian non-institutional settled population excluding certain areas with difficult access or low population densities, in particular, the nomad population, displaced populations who are homeless, population living in public housing (boarding, hotels, prisons, hospitals, etc.), individuals enlisted in the Armed Forces, who are residing permanently within camps and do not spend most days of the year with their families. Similarly, for marine crews and expatriates outside the country and other categories of persons in remote islands.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Economic Research Forum | |
| ILO Regional Office for Arab States | Lebanon |
| Central Statistical Organization | Yemen |
Producers
| Name |
|---|
| The Ministry of Social Affairs and Labour |
Sampling
Sampling Procedure
THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL STATISTICAL ORGANIZATION OF YEMEN (CSO)
The sample design of the labour force survey of Yemen 2013-2014 is a two-stage stratified sample of enumeration areas in the first stage of sampling and a fixed number of sample households at the second stage of sampling. The resulting sample is spread evenly over the four quarters of the survey period.
Accordingly, the Central Statistics Organization (CSO) has drawn a stratified sample of census enumeration areas recomposed as primary sampling units (PSUs). Sample selection has been made with probability proportional to the number of households as determined in the 2004 population on census. In the second stage of sampling, after relisting of the sample enumeration areas, a fixed number of households (16 sample households) are drawn as clusters with equal probability from each sample enumeration area. The strata consist of the urban and rural areas of the 21 governorates in Yemen.
According to the sample design, urban areas are oversampled and rural areas under-sampled. This is because a relatively larger sample size is required in urban areas where heterogeneity is greater in comparison with rural areas. Also, because the cost of transportation and field operations is relatively greater in rural areas, it is more cost effective to under sample the rural areas relative to the less costly operations in urban areas. The differential sampling rates are then corrected through the sample weights so that the final results accurately reflect to the overall employment pattern.
The sample selection of the cluster of 16 households in each sample enumeration area was drawn after fresh listing of the totality of the households living in the sample enumeration area at the time of listing. This procedure updates the census information that dates back to 2004. The listing operations are carried out in each quarter before survey interviewing. The updated lists are send to CSO in Sana'a for data entry and sample selection of households for transmission to the survey team in each area. Instructions were given so that sample households that could not be found in the field or were absent or refused to be interview should not be substituted with other households as this procedure may introduce bias in the results. Instructions were also given that in cases where the minimum number of households in the sample enumeration areas was to be found to be less than the required 16 in each quarter, all households in the enumeration area should be taken in the sample.
The total sample size was determined on the basis of the requirement of producing national estimates of the unemployment rate with 1.5% margin of errors at the national level, assuming an overall non-response rate of 15%, and a design effect of 3. For the determination of the national sample size, the expected unemployment rate was set at 15% and the expected number of sample households to reach one person of working age, 15 years old and over, in the labour force was set at 0.6.
A more detailed description of the allocation of sample across governorates is provided in the report document available among external resources in English.
Response Rate
Among the 13,167 target sample households, some of 12,646 provided data for all members of the households and 16 for some but not all members. In addition, 323 eligible sample households could not be contacted due to temporary absence and 155 refused to participate in the survey. There were also 11 sample households who could not be contacted because the dwelling was found vacant or the address could not be found. Finally, there were 2 sample dwellings found destroyed and an additional 14 that could be interviewed for other reasons.
In total, there were 13,140 eligible households, among which 13,140 responded and 478 not responded, giving a non-response rate of 3.6%. The non-response rate was about the same in all quarters (4.4% in Q1, 3.3% .in Q2, 2.8% in Q3 and 4.0% in Q4).
Corrections for non-response errors were made by inflating the design weights for each quarter by the inverse of the response rate (one minus the non-response rate defined above) for each sample enumeration area as described earlier. This procedure assumes that non-respondent households within an enumeration area have similar characteristics as the responding households in those areas.
In total, there were 13,140 eligible households, among which 13,140 responded and 478 not responded, giving a non-response rate of 3.6%. The non-response rate was about the same in all quarters (4.4% in Q1, 3.3% .in Q2, 2.8% in Q3 and 4.0% in Q4).
Corrections for non-response errors were made by inflating the design weights for each quarter by the inverse of the response rate (one minus the non-response rate defined above) for each sample enumeration area as described earlier. This procedure assumes that non-respondent households within an enumeration area have similar characteristics as the responding households in those areas.
Weighting
The sampling weights were calculated on the basis of the sample design and response rates. The sample design determines the probability of selection of each unit that in principle is a known non-zero value between 0 and 1. The response rates were obtained from information on the cover page of the LFS questionnaire after visiting the sample household: completed interview, partially completed interview, absent, refusal, vacant/demolished, out-of-scope (shop, workshop, office, …) and other.
In mathematical terms, the extrapolation weights are given by:
Wk = Basic Weight / Response Rate
where the basic weight is the inverse of the probability of selection and the response rate in the proportion of completed and partially completed households interviewed in the total number of sample households selected.
For the calculation of the probability of selection, the number of households listed is obtained from the listing form and the number of sample households selected is the sample-take, the fixed number of sample households selected in each sample enumeration area, b=16. The number of sample households with completed and partially completed interviews is obtained from the cover page of the filled-in household questionnaire. The probability of selection of the sample enumeration area is proportional to size to the number of households in the sample enumeration area according to the sampling frame.
Finally, the extrapolation weights were adjusted to conform to known population projections. This process of adjustment is called calibration. Calibration means using calibrated weights such that the application of these weights to the auxiliary variables will give estimates exactly equal to the known population totals on those auxiliary variables. Here calibration was made on the sampling weights of all quarters except the first to conform to the projected population of the quarters based on the population estimate of the first quarter. This procedure was adopted because independent and reliable projection projections were not available.
For the calculation of annual estimates, the quarterly sampling weights were simply divided by four. This procedure is equivalent to calculating annual estimates by the simple arithmetic average of the quarterly estimates.
The results indicate that on average on each sample person represents about 1100 persons for quarterly estimates and about 277 persons for annual estimates. The standard deviations of the quarterly or annual weights are about equal the average weights, indicating significant variability among the sampling weights, whether quarterly or annual.
In mathematical terms, the extrapolation weights are given by:
Wk = Basic Weight / Response Rate
where the basic weight is the inverse of the probability of selection and the response rate in the proportion of completed and partially completed households interviewed in the total number of sample households selected.
For the calculation of the probability of selection, the number of households listed is obtained from the listing form and the number of sample households selected is the sample-take, the fixed number of sample households selected in each sample enumeration area, b=16. The number of sample households with completed and partially completed interviews is obtained from the cover page of the filled-in household questionnaire. The probability of selection of the sample enumeration area is proportional to size to the number of households in the sample enumeration area according to the sampling frame.
Finally, the extrapolation weights were adjusted to conform to known population projections. This process of adjustment is called calibration. Calibration means using calibrated weights such that the application of these weights to the auxiliary variables will give estimates exactly equal to the known population totals on those auxiliary variables. Here calibration was made on the sampling weights of all quarters except the first to conform to the projected population of the quarters based on the population estimate of the first quarter. This procedure was adopted because independent and reliable projection projections were not available.
For the calculation of annual estimates, the quarterly sampling weights were simply divided by four. This procedure is equivalent to calculating annual estimates by the simple arithmetic average of the quarterly estimates.
The results indicate that on average on each sample person represents about 1100 persons for quarterly estimates and about 277 persons for annual estimates. The standard deviations of the quarterly or annual weights are about equal the average weights, indicating significant variability among the sampling weights, whether quarterly or annual.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2013-08-17 | 2013-09-01 | First round |
| 2013-11-02 | 2013-11-17 | Second round |
| 2014-01-02 | 2014-02-16 | Third round |
| 2014-05-01 | 2014-05-16 | Fourth round |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
The field operations of the labour force survey were launched in September 2013. The field staff was composed of 60 interviewers, 21 team leaders and 22 supervisors. The same team with one car covered both the urban and rural areas within each governorate.
The operations may be grouped into two major steps:
(a) complete listing of households in 209 sample enumeration areas (Primary sampling units) in each quarter; and (b) interviewing of 16 selected sample households in each of the sample enumeration areas.
The listing operations were meant are to update the sampling frame based on the population and housing census 2004, and to account for new household formations and population movements that has occurred since 2004.
Survey interviewing was carried from 17 August 2013 to 1 September 2014 for quarter 1; 2 to 17 November 2014 for quarter 2; 1 to 16 February 2014 for quarter 3; and 1 to 16 May 2014 for quarter 4. The interviewers were recruited from outside Central Statistical Organization through newspaper advertisements. They received training during a five-day period: three days for classroom training, 1 day for pilot interviewing and 1 day for evaluation.
The operations may be grouped into two major steps:
(a) complete listing of households in 209 sample enumeration areas (Primary sampling units) in each quarter; and (b) interviewing of 16 selected sample households in each of the sample enumeration areas.
The listing operations were meant are to update the sampling frame based on the population and housing census 2004, and to account for new household formations and population movements that has occurred since 2004.
Survey interviewing was carried from 17 August 2013 to 1 September 2014 for quarter 1; 2 to 17 November 2014 for quarter 2; 1 to 16 February 2014 for quarter 3; and 1 to 16 May 2014 for quarter 4. The interviewers were recruited from outside Central Statistical Organization through newspaper advertisements. They received training during a five-day period: three days for classroom training, 1 day for pilot interviewing and 1 day for evaluation.
Data Collectors
| Name | Abbreviation |
|---|---|
| Central Statistical Organization | CSO |
Questionnaires
Questionnaires
The questionnaire of the Yemen LFS 2013-2014 was designed on the basis of the ILO model LFS questionnaire (version A) and other national LFS questionnaires used in the region. The draft questionnaire was field tested with six households in Sana’a, each member of the field staff interviewing one sample household in his or her area. The experience gained in the field test was reviewed and led to some modifications of the draft questionnaire.
Apart from the cover page and the back page, the core LFS questionnaire contains 52 questions. There are 11 questions on the social and demographic characteristics of the household members in the household roster. In the individual questionnaire addressed to the working age population 15 years of age or older, there are 3 questions to identify the employed persons and 19 questions on their employment characteristics including timerelated underemployment followed by 8 additional questions on income from employment.
The individual questionnaire also includes 5 questions to identify the unemployment and the potential labour force and 5 follow-up questions on unemployment characteristics.
Apart from the cover page and the back page, the core LFS questionnaire contains 52 questions. There are 11 questions on the social and demographic characteristics of the household members in the household roster. In the individual questionnaire addressed to the working age population 15 years of age or older, there are 3 questions to identify the employed persons and 19 questions on their employment characteristics including timerelated underemployment followed by 8 additional questions on income from employment.
The individual questionnaire also includes 5 questions to identify the unemployment and the potential labour force and 5 follow-up questions on unemployment characteristics.
Data Processing
Data Editing
----> Raw Data
Data processing involved data entry, coding, editing and tabulation of the survey results. Data entry was carried out in parallel with the interviewing of sample households. It was conducted at the Central Statistical Organization headquarter in Sana'a where all data processing operations except tabulation were centralized.
The supervisory staff of the data entry operations was responsible for editing the questionnaires before actual data entry. Editing at this stage involved review of the questionnaire regarding its filled-in contents including ensuring that there is no missing block of information for household members aged 15 years old and over and correct coding of occupation, branch of economic activity and other variables.
The data files were further processed at ILO headquarters in Geneva. They were first converted into a single file with 86,778 records and augmented with several fields, in particular, the sampling weights (“weight”) and the key derived variables: employed (E), unemployed (U), time-related underemployment (TRU), potential labour force (PLF) as well as other derived variables such as informal sector employment (IS) and informal employment (IE).
----> Harmonized Data
- The SPSS package is used to clean and harmonize the datasets.
- The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency.
- All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization.
- A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
- A post-harmonization cleaning process is then conducted on the data.
- Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.
Data processing involved data entry, coding, editing and tabulation of the survey results. Data entry was carried out in parallel with the interviewing of sample households. It was conducted at the Central Statistical Organization headquarter in Sana'a where all data processing operations except tabulation were centralized.
The supervisory staff of the data entry operations was responsible for editing the questionnaires before actual data entry. Editing at this stage involved review of the questionnaire regarding its filled-in contents including ensuring that there is no missing block of information for household members aged 15 years old and over and correct coding of occupation, branch of economic activity and other variables.
The data files were further processed at ILO headquarters in Geneva. They were first converted into a single file with 86,778 records and augmented with several fields, in particular, the sampling weights (“weight”) and the key derived variables: employed (E), unemployed (U), time-related underemployment (TRU), potential labour force (PLF) as well as other derived variables such as informal sector employment (IS) and informal employment (IE).
----> Harmonized Data
- The SPSS package is used to clean and harmonize the datasets.
- The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency.
- All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization.
- A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
- A post-harmonization cleaning process is then conducted on the data.
- Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.
Data Appraisal
Estimates of Sampling Error
Sampling errors arise due to the fact that the survey does not cover all elements of the population, but only a selected portion. The sampling error of an estimate is based on the difference between the estimate and the value that would have been obtained on the basis of a complete count of the population under otherwise identical conditions.
Knowing about the magnitude of sampling errors is crucial for interpreting the survey results. It allows decision on the precision of the estimates and on the degree of confidence that may be attached to them, especially relevant in the case of small population subgroups for which the survey results may not be statistically significant due to the small number of observations on which the estimates may be based. Information on sampling errors is also crucial for sample design for future surveys.
In principle, sampling errors may be decomposed into two components: (i) sampling bias; and (ii) sampling variance. Sampling bias reflects the systematic error that may occur due to the failures of the sample design, for example, certain elements of the population receiving zero probability of selection. The sampling variance, on the other hand, reflects the uncertainty associated to a sample estimate due to the particular sample used for its calculation, among all possible other samples that could have been selected from the frame with the same sampling design.
The calculation of the sampling variance of survey estimates for complex multistage designs is generally based on the following principle: the variance contributed by the later stages of sampling is, under broad conditions, reflected in the observed variation among the sample results for first-stage units. Thus, the sampling variance of a variety of statistics, such as totals, means, ratios, proportions, and their differences can be obtained on the basis of totals calculated for primary sampling units (PSUs).
More information on the estimates of Sampling Errors (for main labour force indicators) is available in the annual report provided among the disseminated survey materials under a file named "Report, Yemen, LFS 2013-2014 (English).pdf".
Knowing about the magnitude of sampling errors is crucial for interpreting the survey results. It allows decision on the precision of the estimates and on the degree of confidence that may be attached to them, especially relevant in the case of small population subgroups for which the survey results may not be statistically significant due to the small number of observations on which the estimates may be based. Information on sampling errors is also crucial for sample design for future surveys.
In principle, sampling errors may be decomposed into two components: (i) sampling bias; and (ii) sampling variance. Sampling bias reflects the systematic error that may occur due to the failures of the sample design, for example, certain elements of the population receiving zero probability of selection. The sampling variance, on the other hand, reflects the uncertainty associated to a sample estimate due to the particular sample used for its calculation, among all possible other samples that could have been selected from the frame with the same sampling design.
The calculation of the sampling variance of survey estimates for complex multistage designs is generally based on the following principle: the variance contributed by the later stages of sampling is, under broad conditions, reflected in the observed variation among the sample results for first-stage units. Thus, the sampling variance of a variety of statistics, such as totals, means, ratios, proportions, and their differences can be obtained on the basis of totals calculated for primary sampling units (PSUs).
More information on the estimates of Sampling Errors (for main labour force indicators) is available in the annual report provided among the disseminated survey materials under a file named "Report, Yemen, LFS 2013-2014 (English).pdf".
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Economic Research Forum | ERF | erfdataportal@erf.org.eg | www.erf.org.eg |
Contacts
| Name | URL | |
|---|---|---|
| Economic Research Forum (ERF) - 21 Al-Sad Al-Aaly St., Dokki, Giza, Egypt | erfdataportal@erf.org.eg | www.erf.org.eg |
Confidentiality
To access the micro data, researchers are required to register on the ERF website and comply with the data access agreement.
The data will be used only for scholarly research, or educational purposes. Users are prohibited from using data acquired from the Economic Research Forum in the pursuit of any commercial or private ventures.
Access conditions
Licensed datasets, accessible under conditions.
Citation requirements
The users should cite the Economic Research Forum, the International Labor Office (ILO) and the Central Statistical Organization (CSO) as follows:
OAMDI, 2017. Harmonized Labor Force Surveys (HLFS), http://erf.org.eg/data-portal/. Version 1.0 of Licensed Data Files; LFS 2013-2014- ILO and Central Statistical Organization (CSO), Yemen. Egypt: Economic Research Forum (ERF).
OAMDI, 2017. Harmonized Labor Force Surveys (HLFS), http://erf.org.eg/data-portal/. Version 1.0 of Licensed Data Files; LFS 2013-2014- ILO and Central Statistical Organization (CSO), Yemen. Egypt: Economic Research Forum (ERF).
Disclaimer and copyrights
Disclaimer
The Economic Research Forum and the International Labor Office have granted the researcher access to relevant data following exhaustive efforts to protect the confidentiality of individual data. The researcher is solely responsible for any analysis or conclusions drawn from available data.
Copyright
(c) 2017, Economic Research Forum | (c) 2015, ILO
Metadata production
DDI Document ID
YEM_LFS_2013_HD_V1
Producers
| Name | Abbreviation | Role |
|---|---|---|
| Economic Research Forum | ERF | Cleaning and harmonizing raw data received from the Statistical Agency |
Date of Metadata Production
2017-09
DDI Document version
Version 1