Labor Force Survey, LFS 2020
Palestine, 2020 - 2021
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Reference ID
PAL_LFS_2020_HD_V1
Producer(s)
Economic Research Forum, Palestinian Central Bureau of Statistics
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Created on
Aug 11, 2021
Last modified
Aug 11, 2021
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Identification
Survey ID
PAL_LFS_2020_HD_V1
Title
Labor Force Survey, LFS 2020
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
<p style="border:solid thin black;"> 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</p>
The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2020 (LFS). The survey rounds covered a total sample of about 23,915 households (about 5,980 households per quarter).
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.
The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2020 (LFS). The survey rounds covered a total sample of about 23,915 households (about 5,980 households per quarter).
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
V1.0: A cleaned and a harmonized version of the survey dataset, produced by the Economic Research Forum for dissemination.
Version date
2021-08
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
<p style="border:solid thin black;"> 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</p>
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 Above and there are staying normally with their households in the state of Palestine during 2020.
---> Sampling Frame:
The sampling frame consists of a comprehensive sample selected from the Population, Housing and Establishments Census 2017: This comprehensive sample consists of geographical areas with an average of 150 households, and these are considered as enumeration areas used in the census and these units were used as primary sampling units (PSUs).
---> Sampling Size:
The estimated sample size is 8,040 households in each quarter of 2020.
---> Sample Design
The sample is two stage stratified cluster sample with two stages :
First stage: we select a systematic random sample of 536 enumeration areas for the whole round.
Second stage: we select a systematic random sample of 15 households from each enumeration area selected in the first stage.
---> 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 536 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).
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 Above and there are staying normally with their households in the state of Palestine during 2020.
---> Sampling Frame:
The sampling frame consists of a comprehensive sample selected from the Population, Housing and Establishments Census 2017: This comprehensive sample consists of geographical areas with an average of 150 households, and these are considered as enumeration areas used in the census and these units were used as primary sampling units (PSUs).
---> Sampling Size:
The estimated sample size is 8,040 households in each quarter of 2020.
---> Sample Design
The sample is two stage stratified cluster sample with two stages :
First stage: we select a systematic random sample of 536 enumeration areas for the whole round.
Second stage: we select a systematic random sample of 15 households from each enumeration area selected in the first stage.
---> 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 536 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 rates
The survey sample consists of about 32,160 households of which 23,915 households completed the interview; whereas 15,490 households from the West Bank and 8,425 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 73.5% while in the Gaza Strip it reached 83.7%.
Weighting
The weight of statistical units (sampling unit) in the sample is defined as the mathematical inverse of the selection probability where the sample of the survey is two stage stratified cluster sample, so In the first stage, we calculate the weight of enumeration areas which depending on the probability of each enumeration area (a systematic random sample), then In the second stage we calculate weight of households in each enumeration area, Initial households weights resulted from product of weight of first stage and weight of second stage, final households weights obtained after adjustment of initial weights with the households estimates of the middle of each quarter of the year 2020 on the level of design strata (governorate, locality type ).
For the 10 years and over persons file we add the final household weight for each person, then we adjust the initial person weight with the persons estimates of the middle of each quarter of the year 2020 on the level of Region (West bank, Gaza strip), Sex (male, female ), Five -year age groups (14 groups) then we obtain the final adjusted person weight.
For the 10 years and over persons file we add the final household weight for each person, then we adjust the initial person weight with the persons estimates of the middle of each quarter of the year 2020 on the level of Region (West bank, Gaza strip), Sex (male, female ), Five -year age groups (14 groups) then we obtain the final adjusted person weight.
Survey instrument
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 collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2020-01-06 | 2020-04-03 | First round |
| 2020-04-04 | 2020-07-05 | Second round |
| 2020-07-06 | 2020-10-05 | Third round |
| 2020-10-06 | 2021-01-03 | Fourth round |
Data Collectors
| Name | Affiliation |
|---|---|
| Palestinian Central Bureau of Statistics | Palestinian National Authority |
Notes on data collection
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 processing
Cleaning operations
---> Raw Data
PCBS started collecting data since 1st quarter 2020 using the hand held devices in Palestine excluding Jerusalem in side boarders (J1) and Gaza Strip, the program used in HHD called Sql Server and Microsoft. Net which was developed by General Directorate of Information Systems. From the beginning of March 2020, with the spread of the COVID-19 pandemic and the home quarantine imposed by the government, the personal (face to face) interview was replaced by the phone interview for households who had phone numbers from previous rounds, and for those households that did not have phone numbers, they were referred to and interviewed in person (face to face interview).
Using HHD reduced the data processing stages, the fieldworkers collect data and sending data directly to server then the project manager can withdrawal the data at any time he needs.
In order to work in parallel with Gaza Strip and Jerusalem in side boarders (J1), an office program was developed using the same techniques by using the same database for the HHD.
---> 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.
PCBS started collecting data since 1st quarter 2020 using the hand held devices in Palestine excluding Jerusalem in side boarders (J1) and Gaza Strip, the program used in HHD called Sql Server and Microsoft. Net which was developed by General Directorate of Information Systems. From the beginning of March 2020, with the spread of the COVID-19 pandemic and the home quarantine imposed by the government, the personal (face to face) interview was replaced by the phone interview for households who had phone numbers from previous rounds, and for those households that did not have phone numbers, they were referred to and interviewed in person (face to face interview).
Using HHD reduced the data processing stages, the fieldworkers collect data and sending data directly to server then the project manager can withdrawal the data at any time he needs.
In order to work in parallel with Gaza Strip and Jerusalem in side boarders (J1), an office program was developed using the same techniques by using the same database for the HHD.
---> 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 errors
---> 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 23.2% 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 23.2% 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.
Data Access
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Economic Research Forum | Economic Research Forum (ERF) | www.erf.org.eg | erfdataportal@erf.org.eg |
Confidentiality
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes |
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 requirement
The users should cite the Economic Research Forum and the Palestinian Central Bureau of Statistics as follows:
OAMDI, 2021. Harmonized Labor Force Surveys (HLFS), http://erf.org.eg/data-portal/. Version 1.0 of Licensed Data Files; LFS 2020- Palestinian Central Bureau of Statistics (PCBS). Egypt: Economic Research Forum (ERF).
OAMDI, 2021. Harmonized Labor Force Surveys (HLFS), http://erf.org.eg/data-portal/. Version 1.0 of Licensed Data Files; LFS 2020- 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) 2021, Economic Research Forum | (c) 2020, Palestinian Central Bureau of Statistics
Contacts
Contacts
| Name | URL | |
|---|---|---|
| Economic Research Forum (ERF) - 21 Al-Sad Al-Aaly St., Dokki, Giza, Egypt | erfdataportal@erf.org.eg | www.erf.org.eg |
Metadata production
Document ID
PAL_LFS_2020_HD_V1
Producers
| Name | Role |
|---|---|
| Economic Research Forum | Cleaning and harmonizing raw data received from the Statistical Agency |
Date of metadata production
2021-08
Metadata version
Version
Version 1