Socio-Economic Survey, HSOCIOECOS 2020
Palestine, 2020 - 2021
Palestinian Central Bureau of Statistics
Identification
Survey ID Number
PAL_SOCIOECOS_2020_HD_V1
Title
Socio-Economic Survey, HSOCIOECOS 2020
Country
| Name | Country code |
|---|---|
| Palestine | PAL |
Study type
Other Household Survey [hh/oth]
Series Information
The Palestinian Socio-Economic Survey Programme consists of an integrated series of socio-economic surveys, the first of which was issued in 2001.
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 the Socio-Economic Survey 2020. The survey round covered a total sample of about 9926 households.
The main objective of collecting data on the socio-economic and its components, including demographic charachteristics, employment, unemployment, is to provide basic information on the size and structure of the Palestinian households, as well as other data on the status of housing and characteristics of individuals, the family and living conditions.
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
2023-03
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,assistance and coping strategies information.
Individuals: Includes demographics, education, current labor status, main and last held job characteristics, unemployment characteristics and inactivity reason(s), and freedom of mobility.
Individuals (18 years old and above): Includes life quality, assessment of health, education, services and information technology.
Individuals: Includes demographics, education, current labor status, main and last held job characteristics, unemployment characteristics and inactivity reason(s), and freedom of mobility.
Individuals (18 years old and above): Includes life quality, assessment of health, education, services and information technology.
Topics
| Topic | Vocabulary |
|---|---|
| Demographics | ERF |
| Education | 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 |
|---|---|
| Palestinian Central Bureau of Statistics | Palestinian National Authority |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| World Food Programme | WFP |
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 Palestinian households and individuals who habitually reside with their households in Palestine for the reference period of the survey, which is 2020, and there was a focus on individuals of the age group 18 years and over to complete an additional form for individuals in this category.
---> 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 3623 households in 2020.
---> Sample Design
The sample is two stage stratified cluster sample with three stages :
First stage: a systematic random sample of 161 enumeration areas for the whole round was selected.
Second stage: choosing (9-25) households from each enumeration area in the first stage in a systematic random manner.
Third stage: a male or female individual was selected from all sample families (old and new) in the second stage of individuals 18 years and over using check tables to complete the form for individuals 18 years and over (quality of life model). Taking into account that the household whose number is even in the enumeration area sample, we choose a female from it, and the household whose number is odd, from which we choose a male. In Jerusalem, Area J1, area sample of 25 households was selected from each enumeration area in the first stage.
---> Sample strata:
The population was divided by:
1. The governorate (16 governorates in the West Bank, including Jerusalem J1 governorate, which the Israeli occupation annexed to it by force after its occupation of the West Bank in 1967 as Tabqa and the Gaza Strip).
2. Type of settlement (urban, rural, camp).
3. Area C (class C, non-C) as an implicit class.
Response Rate
The survey sample consists of about 3623 households of which 3122 households completed the interview; whereas 2104 households from the West Bank and 1018 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 85.5% while in the Gaza Strip it reached 87.6%.
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 a three-stage stratified cluster systematic random sample. In the first stage, the weight of enumeration areas is calculated based on the probability of each enumeration area. In the second stage, the weight of households in each enumeration area is calculated. Initial household weights resulted from the product of the weight of the first stage and the weight of the second stage. Then the initial weight is adjusted by producing the initial weight and the attrition factor (attrition from the sample). The final household weights were obtained after adjustment of the initial weights with the household estimates for mid-2020 according to design strata (governorate, locality type).
Weights of households members’ portfolio are calculated by giving every member the final weight of his/her household, which is the primary individual/member weight. Primary Individual/Member’s Weight is then adjusted according to area, gender and age groups (17 groups) representing the age of individual/member by mid-December 2020. This enabled to obtain the individual/member’s final weight in his/her category. The weights are then merged in the individual/member’s portfolio for individuals aged 18 and above.
Weights of households members’ portfolio are calculated by giving every member the final weight of his/her household, which is the primary individual/member weight. Primary Individual/Member’s Weight is then adjusted according to area, gender and age groups (17 groups) representing the age of individual/member by mid-December 2020. This enabled to obtain the individual/member’s final weight in his/her category. The weights are then merged in the individual/member’s portfolio for individuals aged 18 and above.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2020-12-09 | 2021-01-25 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
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 questionnaire is the key tool for data collection. It must be conforming to the technical
characteristics of fieldwork to allow for data processing and analysis. The survey
questionnaire comprised the following parts:
- Part one: Identification data.
- Part two: Quality control
- Part three: Data of households’ members and social data.
- Part four: Housing unit data
- Part five: Assistance and Coping Strategies Information
- Part six: Expenditure and Consumption
- Part seven: Food Variation and Facing Food Shortage
- Part eight: Income
- Part nine: Agricultural and economic activities.
- Part ten: Freedom of mobility
- In addition to a questionnaire for individuals (18 years old and above): Questions on suffering and life quality, assessment of health, education, administration (Ministry of the Interior) services and information technology.
characteristics of fieldwork to allow for data processing and analysis. The survey
questionnaire comprised the following parts:
- Part one: Identification data.
- Part two: Quality control
- Part three: Data of households’ members and social data.
- Part four: Housing unit data
- Part five: Assistance and Coping Strategies Information
- Part six: Expenditure and Consumption
- Part seven: Food Variation and Facing Food Shortage
- Part eight: Income
- Part nine: Agricultural and economic activities.
- Part ten: Freedom of mobility
- In addition to a questionnaire for individuals (18 years old and above): Questions on suffering and life quality, assessment of health, education, administration (Ministry of the Interior) services and information technology.
Data Processing
Data Editing
---> Raw Data
PCBS started collecting data since 9/12/2020 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.
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 9/12/2020 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.
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 Error
---> Sampling Errors
Those errors result from studying part (sample) of the society and not all society units. Since the socio-economic conditions survey 2020 was conducted on a sample, sampling errors are expected to occur. To minimize sampling errors, a properly designed probability sample was used to calculate errors throughout the process. This means that for every unit of the society there is a probability to be selected in the sample. The variance was calculated to measure the impact on sample design for Palestine.
---> Non-Sampling Errors
Non-Sampling errors are possible at all stages of the project, during data collection or processing. Those are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous 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, as well as practical and theoretical training during the training course. Non-sampling errors in the survey resulted from the private data it collected and that some households considered this as interference in the very details of their private life. They refused to cooperate with data. Several methods were used to convince households provide answers and minimize non-response.
Those errors result from studying part (sample) of the society and not all society units. Since the socio-economic conditions survey 2020 was conducted on a sample, sampling errors are expected to occur. To minimize sampling errors, a properly designed probability sample was used to calculate errors throughout the process. This means that for every unit of the society there is a probability to be selected in the sample. The variance was calculated to measure the impact on sample design for Palestine.
---> Non-Sampling Errors
Non-Sampling errors are possible at all stages of the project, during data collection or processing. Those are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous 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, as well as practical and theoretical training during the training course. Non-sampling errors in the survey resulted from the private data it collected and that some households considered this as interference in the very details of their private life. They refused to cooperate with data. Several methods were used to convince households provide answers and minimize non-response.
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, 2023. Harmonized Socio-Economic (HSOCIOECOS), http://www.erfdataportal.com/index.php/catalog. Version 1.0 of Licensed Data Files; HSOCIOECOS 2020- Palestinian Central Bureau of Statistics (PCBS). Egypt: Economic Research Forum (ERF).
OAMDI, 2023. Harmonized Socio-Economic (HSOCIOECOS), http://www.erfdataportal.com/index.php/catalog. Version 1.0 of Licensed Data Files; HSOCIOECOS 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) 2023, Economic Research Forum | (c) 2020, Palestinian Central Bureau of Statistics
Metadata production
DDI Document ID
PAL_ SOCIOECOS_2020_HD_V1
Producers
| Name | Abbreviation | Role |
|---|---|---|
| Economic Research Forum | ERF | Cleaning and harmonizing raw data received from the Statistical Agency |
Date of Metadata Production
2023-03
DDI Document version
Version 1