Labor Force Survey, LFS 2023
Palestine, 2023 - 2024
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Reference ID
PAL_LFS_2023_HD_V1
Producer(s)
Economic Research Forum, Palestinian Central Bureau of Statistics
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Created on
Jul 16, 2026
Last modified
Jul 16, 2026
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Identification
Survey ID
PAL_LFS_2023_HD_V1
Title
Labor Force Survey, LFS 2023
Abbreviation or acronym
LFS
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
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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
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The Palestinian Central Bureau of Statistics (PCBS) conducted four rounds of the 2023 Labor Force Survey (LFS). The planned sample size was 8,040 households per round. However, in the fourth round, only 4,006 households were successfully interviewed in the West Bank, and no questionnaires were completed in the Gaza Strip due to the Israeli war on the Gaza Strip. Consequently, the four survey rounds covered a total sample of approximately 22,753 households.
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 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
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The Palestinian Central Bureau of Statistics (PCBS) conducted four rounds of the 2023 Labor Force Survey (LFS). The planned sample size was 8,040 households per round. However, in the fourth round, only 4,006 households were successfully interviewed in the West Bank, and no questionnaires were completed in the Gaza Strip due to the Israeli war on the Gaza Strip. Consequently, the four survey rounds covered a total sample of approximately 22,753 households.
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
2026-07
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
The survey was designed to provide representative estimates at the regional level, by locality type (urban, rural, and camp), and at the governorate level.
Gaza Strip was covered only in the first three survey rounds due to the war on Gaza.
Gaza Strip was covered only in the first three survey rounds due to the war on Gaza.
Universe
The survey covered all the Palestinian persons aged 10 years and above who are a usual residence in State of Palestine
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Economic Research Forum | |
| Palestinian Central Bureau of Statistics | Palestinian National Authority |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| Core Funding Group | CFG |
Sampling
Sampling procedure
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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
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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 2023.
---> 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 around 8,040 households in each quarter of 2023.
---> 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 (17 governorates, where Jerusalem was considered as two statistical areas)
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 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
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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 2023.
---> 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 around 8,040 households in each quarter of 2023.
---> 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 (17 governorates, where Jerusalem was considered as two statistical areas)
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
(See https://microdata.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/731/study-description)
The response rate was 86.2% in the first quarter 2023
The response rate was 83.6% in the second quarter 2023
The response rate was 83.7% in the third quarter 2023
The response rate was 98.8% in the fourth quarter 2023 in the West Bank only
The response rate was 86.2% in the first quarter 2023
The response rate was 83.6% in the second quarter 2023
The response rate was 83.7% in the third quarter 2023
The response rate was 98.8% in the fourth quarter 2023 in the West Bank only
Weighting
The fundamental objectives of the weights calculation procedure were improvement of:
1. Estimation efficiency
2. Address non response case
3. Mitigation of bias risks
The main procedural steps taken were
Step 1: Derive initial weights for households and roster individuals. by the reciprocals of the inclusion probabilities generated by the PPS sampling algorithm
Step 2: Adjust the weights of households and roster individuals for household-level nonresponse.
Step 3: Calibrate the weights obtained at step 2, using as calibration benchmarks suitable household level and individual-level by demographic estimation. (see the LFS 2022 report in the accompanying documents)
1. Estimation efficiency
2. Address non response case
3. Mitigation of bias risks
The main procedural steps taken were
Step 1: Derive initial weights for households and roster individuals. by the reciprocals of the inclusion probabilities generated by the PPS sampling algorithm
Step 2: Adjust the weights of households and roster individuals for household-level nonresponse.
Step 3: Calibrate the weights obtained at step 2, using as calibration benchmarks suitable household level and individual-level by demographic estimation. (see the LFS 2022 report in the accompanying documents)
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 |
|---|---|---|
| 2023-01-02 | 2023-04-02 | The first round |
| 2023-04-03 | 2023-07-06 | The second round |
| 2023-07-07 | 2023-10-06 | The third round |
| 2023-10-07 | 2024-01-04 | The fourth round |
Mode of data collection
- Computer Assisted Personal Interview [capi]
Data Collectors
| Name | Affiliation | Abbreviation |
|---|---|---|
| Palestinian Central Bureau of Statistics | Palestinian National Authority | PCBS |
Notes on data collection
Data were collected using the proxy interview method for individuals aged 10 years and above who were usual residents of the State of Palestine in 2020. Data was collected using PC-tablets in the West Bank, while paper forms were used in Jerusalem (J1).
Starting March 2020, and due to the COVID-19 pandemic outbreak and the home quarantine imposed by the government, the personal interview was replaced by the phone interview for households whose phone numbers are available from previous quarters, while households whose phone numbers are not available were interviewed face to face.
Gaza Strip was covered only in the first three survey rounds due to the war on Gaza.
Starting March 2020, and due to the COVID-19 pandemic outbreak and the home quarantine imposed by the government, the personal interview was replaced by the phone interview for households whose phone numbers are available from previous quarters, while households whose phone numbers are not available were interviewed face to face.
Gaza Strip was covered only in the first three survey rounds due to the war on Gaza.
Data processing
Cleaning operations
---> 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 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 14.4% which is very low once compared to the household surveys conducted by PCBS.
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 14.4% which is very low once compared to the household surveys conducted by PCBS.
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, 2026. Harmonized Labor Force Surveys (HLFS), http://www.erfdataportal.com/index.php/catalog/. Version 1.0 of Licensed Data Files; LFS 2023- Palestinian Central Bureau of Statistics (PCBS). Egypt: Economic Research Forum (ERF).
OAMDI, 2026. Harmonized Labor Force Surveys (HLFS), http://www.erfdataportal.com/index.php/catalog/. Version 1.0 of Licensed Data Files; LFS 2023- 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) 2026, Economic Research Forum | (c) 2023, 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_2023_HD_V1
Producers
| Name | Abbreviation | Role |
|---|---|---|
| Economic Research Forum | ERF | Cleaning and harmonizing raw data received from the Statistical Agency |
Date of metadata production
2026-07
Metadata version
Version
Version 1