Labor Force Survey, LFS 2012
Palestine, 2012
Economic Research Forum, Palestinian Central Bureau of Statistics
Identification
Survey ID Number
PAL_LFS_2012_HD_V1
Title
Labor Force Survey, LFS 2012
Country
| Name | Country code |
|---|---|
| Palestine | PAL |
Study type
Labor Force Survey [hh/lfs]
Series Information
The Palestinian Labour Force Survey Programme consists of an integrated series of labour force surveys, the first of which was issued in October 1995. This programme conducts surveys quarterly.
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 PALESTINIAN CENTRAL BUREAU OF STATISTICS
The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2012 (LFS). The survey rounds covered a total sample of about 30,887 households, and the number of completed questionaire is 26,898.
The main objective of collecting data on the labour force and its components, including employment, unemployment and underemployment, is to provide basic information on the size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in the employment situation. These data, supported with information on other aspects of the economy, provide a basis for the evaluation and analysis of macro-economic policies.
The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
1- Household/family.
2- Individual/person.
2- Individual/person.
Version
Version Description
V1.0: A cleaned and a harmonized version of the survey dataset, produced by the Economic Research Forum for dissemination.
Production
Date
2016-10
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 occupation and economic activity classifications 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, secondary 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, secondary 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
Covering a representative sample on the region level (West Bank, Gaza Strip), the locality type (urban, rural, camp) and the governorates.
Universe
The survey covered all Palestinian households who are a usual residence of the Palestinian Territory.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Economic Research Forum | |
| Palestinian Central Bureau of Statistics | Palestinian National Authority |
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 PALESTINIAN CENTRAL BUREAU OF STATISTICS
The methodology was designed according to the context of the survey, international standards, data processing requirements and comparability of outputs with other related surveys.
---> Target Population:
It consists of all individuals aged 10 years and older normally residing in their households in Palestine during 2012.
---> Sampling Frame:
The sampling frame consists of the master sample, which was updated in 2011: each enumeration area consists of buildings and housing units with an average of about 124 households. The master sample consists of 596 enumeration areas; we used 498 enumeration areas as a framework for the labor force survey sample in 2012 and these units were used as primary sampling units (PSUs).
---> Sampling Size:
The estimated sample size in the first quarter was 7,775 households, in the second quarter it was 7,713 households, in the third quarter it was 7,695 households and in the fourth quarter it was 7,704 households.
---> Sample Design
The sample is two stage stratified cluster sample with two stages :
First stage: we select a systematic random sample of 498 enumeration areas for the whole round ,and we excluded the enumeration areas which its sizes less than 40 households.
Second stage: we select a systematic random sample of 16 households from each enumeration area selected in the first stage, se we select a systematic random of 16 households of the enumeration areas which its size is 80 household and over and the enumeration areas which its size is less than 80 households we select systematic random of 8 households.
---> Sample strata:
The population was divided by:
1- Governorate (16 governorate)
2- Type of Locality (urban, rural, refugee camps).
---> Sample Rotation:
Each round of the Labor Force Survey covers all of the 498 master sample enumeration areas. Basically, the areas remain fixed over time, but households in 50% of the EAs were replaced in each round. The same households remain in the sample for two consecutive rounds, left for the next two rounds, then selected for the sample for another two consecutive rounds before being dropped from the sample. An overlap of 50% is then achieved between both consecutive rounds and between consecutive years (making the sample efficient for monitoring purposes).
Response Rate
The survey sample consists of 30,887 households, of which 26,898 households completed the interview: 17,594 households from the West Bank and 9,304 households in Gaza Strip. Weights were modified to account for the non-response rate. The response rate in the West Bank was 90.2 %, while in the Gaza Strip it was 94.7%.
Weighting
The weight of statistical units (sampling units) in the sample is defined as the mathematical inverse of the selection probability where the sample of the survey is a two-stage stratified cluster sample. Thus, in the first stage we calculate the weight of enumeration areas depending on the probability of each enumeration area (a systematic random sample). In the second stage we calculate the weight of households in each enumeration area. Initial household weights resulted from the product of the weight of the first stage and the weight of the second stage. Final household weights were obtained after adjustment of initial weights with the household estimates of the middle of each quarter of 2012 with regard to design strata (governorate, locality type).
For individuals over 10 years, we added the final household weight for each person, then adjusted the initial individual weight with the estimates of individuals of the middle of each quarter of 2012 according to region (West Bank, Gaza Strip), sex ( male, female), five -year age groups (14 groups), then we obtained the final adjusted individual weight.
For individuals over 10 years, we added the final household weight for each person, then adjusted the initial individual weight with the estimates of individuals of the middle of each quarter of 2012 according to region (West Bank, Gaza Strip), sex ( male, female), five -year age groups (14 groups), then we obtained the final adjusted individual weight.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2012-01-01 | 2012-03-31 | First round |
| 2012-04-01 | 2012-06-30 | Second round |
| 2012-07-01 | 2012-09-30 | Third round |
| 2012-10-01 | 2012-12-31 | Fourth round |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Fieldworkers were trained on basic skills before the start of data Collection. The interviewers were trained on the Domestic and Outbound Tourism Survey by implementing the training course in Ramallah for the West Bank trainees, and in Gaza for Gaza Strip trainees. Instructions for filling the questionnaire were made available for the interviewers. The training provided the participant with aims and definitions of the different indicators and expressions of the survey and how to fill in the questionnaire.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Palestinian Central Bureau of Statistics | PCBS | Palestinian National Authority |
Questionnaires
Questionnaires
The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts:
---> 1. Identification Data:
The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.
---> 2. Quality Control:
This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data.
---> 3. Household Roster:
This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc.
---> 4. Employment Part:
This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.
---> 1. Identification Data:
The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.
---> 2. Quality Control:
This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data.
---> 3. Household Roster:
This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc.
---> 4. Employment Part:
This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.
Data Processing
Data Editing
---> Raw Data
The data processing stage consisted of the following operations:
1. Editing and coding before data entry: All questionnaires were edited and coded in the office using the same instructions adopted for editing in the field.
2. Data entry: At this stage, data was entered into the computer using a data entry template designed in Access. The data entry program was prepared to satisfy a number of requirements such as:
- Duplication of the questionnaires on the computer screen.
- Logical and consistency check of data entered.
- Possibility for internal editing of question answers.
- Maintaining a minimum of digital data entry and fieldwork errors.
- User friendly handling.
Possibility of transferring data into another format to be used and analyzed using other statistical analytic systems such as SPSS.
---> 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.
The data processing stage consisted of the following operations:
1. Editing and coding before data entry: All questionnaires were edited and coded in the office using the same instructions adopted for editing in the field.
2. Data entry: At this stage, data was entered into the computer using a data entry template designed in Access. The data entry program was prepared to satisfy a number of requirements such as:
- Duplication of the questionnaires on the computer screen.
- Logical and consistency check of data entered.
- Possibility for internal editing of question answers.
- Maintaining a minimum of digital data entry and fieldwork errors.
- User friendly handling.
Possibility of transferring data into another format to be used and analyzed using other statistical analytic systems such as SPSS.
---> 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.
Other Processing
- Errors in data processing, such as coding and data entry. The data underwent checking and completion of missing information in the office and checks on logic were conducted on computer as well as manually, including call-backs if required.
- Response errors which resulted from misunderstanding of the questions or interviewers' bias in asking the questions and probing. Thorough training, supervision and various quality control checks were used to minimize bias resulting from these kinds of errors.
- Response errors which resulted from misunderstanding of the questions or interviewers' bias in asking the questions and probing. Thorough training, supervision and various quality control checks were used to minimize bias resulting from these kinds of errors.
Data Appraisal
Estimates of Sampling Error
---> Sampling Errors
Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators: the variance table is attached with the final report. There is no problem in disseminating results at national or governorate level for the West Bank and Gaza Strip.
---> Non-Sampling Errors
Non-statistical errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey, as well as practical and theoretical training during the training course.
Also data entry staff were trained on the data entry program that was examined before starting the data entry process. To stay in contact with progress of fieldwork activities and to limit obstacles, there was continuous contact with the fieldwork team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by fieldworkers were discussed to clarify any issues.
Non-sampling errors can occur at the various stages of survey implementation whether in data collection or in data processing. They are generally difficult to be evaluated statistically.
They cover a wide range of errors, including errors resulting from non-response, sampling frame coverage, coding and classification, data processing, and survey response (both respondent and interviewer-related). The use of effective training and supervision and the careful design of questions have direct bearing on limiting the magnitude of non-sampling errors, and hence enhancing the quality of the resulting data.
The implementation of the survey encountered non-response where the case ( household was not present at home ) during the fieldwork visit and the case ( housing unit is vacant) become the high percentage of the non response cases. The total non-response rate reached 8.3% which is very low once compared to the household surveys conducted by PCBS , The refusal rate reached 2.1% which is very low percentage compared to the household surveys conducted by PCBS, and the reason is the short and clear questionnaire .
Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators: the variance table is attached with the final report. There is no problem in disseminating results at national or governorate level for the West Bank and Gaza Strip.
---> Non-Sampling Errors
Non-statistical errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey, as well as practical and theoretical training during the training course.
Also data entry staff were trained on the data entry program that was examined before starting the data entry process. To stay in contact with progress of fieldwork activities and to limit obstacles, there was continuous contact with the fieldwork team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by fieldworkers were discussed to clarify any issues.
Non-sampling errors can occur at the various stages of survey implementation whether in data collection or in data processing. They are generally difficult to be evaluated statistically.
They cover a wide range of errors, including errors resulting from non-response, sampling frame coverage, coding and classification, data processing, and survey response (both respondent and interviewer-related). The use of effective training and supervision and the careful design of questions have direct bearing on limiting the magnitude of non-sampling errors, and hence enhancing the quality of the resulting data.
The implementation of the survey encountered non-response where the case ( household was not present at home ) during the fieldwork visit and the case ( housing unit is vacant) become the high percentage of the non response cases. The total non-response rate reached 8.3% which is very low once compared to the household surveys conducted by PCBS , The refusal rate reached 2.1% which is very low percentage compared to the household surveys conducted by PCBS, and the reason is the short and clear questionnaire .
Data Appraisal
Concept of data quality covers many aspects, starting from the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are seven dimensions of the statistical quality: relevance, accuracy, timeliness, accessibility, comparability, coherence, and completeness.
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Economic Research Forum | 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 and the Palestinian Central Bureau of Statistics as follows:
OAMDI, 2016. Harmonized Labor Force Surveys (HLFS), http://erf.org.eg/data-portal/. Version 1.0 of Licensed Data Files; LFS 2012- Palestinian Central Bureau of Statistics (PCBS). Egypt: Economic Research Forum (ERF).
OAMDI, 2016. Harmonized Labor Force Surveys (HLFS), http://erf.org.eg/data-portal/. Version 1.0 of Licensed Data Files; LFS 2012- Palestinian Central Bureau of Statistics (PCBS). Egypt: Economic Research Forum (ERF).
Disclaimer and copyrights
Disclaimer
The Economic Research Forum and the Palestinian Central Bureau of Statistics 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) 2016, Economic Research Forum | (c) 2012, Palestinian Central Bureau of Statistics
Metadata production
DDI Document ID
PAL_LFS_2012_HD_V1
Producers
| Name | Abbreviation | Role |
|---|---|---|
| Economic Research Forum | ERF | Cleaning and harmonizing raw data received from the Statistical Agency |
Date of Metadata Production
2016-10
DDI Document version
Version 1