Household Expenditure and Consumption Survey, 2023, Main Findings of Living Standards in the West Bank (Expenditure, Consumption and Poverty), 2023
West Bank and Gaza, 2023 - 2024
Get Microdata
Reference ID
PSE-PCBS-PECS-2023-V1.0
Producer(s)
Palestinian Central Bureau of Statistics
Collections
Created on
Aug 11, 2025
Last modified
Aug 11, 2025
Page views
359
Downloads
2
Identification
Survey ID Number
PSE-PCBS-PECS-2023-V1.0
Title
Household Expenditure and Consumption Survey, 2023, Main Findings of Living Standards in the West Bank (Expenditure, Consumption and Poverty), 2023
Subtitle
Main Findings of Living Standards in the West Bank (Expenditure, Consumption and Poverty), 2023
Translated Title
مسح إنفاق واستهلاك الأسرة، 2023
Country
| Name | Country code |
|---|---|
| Palestine | PSE |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
Palestinian Household Expenditure and Consumption Survey, with annual basis and a periodicity of 5 years
Abstract
The main objectives of the survey are as follows:
To know the consumption expenditure patterns and the impact of social variables on them.
To calculate the average monthly and annual expenditure of the individual and households on items of commodities and services and to know the factors affecting expenditure, such as educational, social and other levels.
To obtain data on household consumption and expenditure levels that can be used to determine poverty levels (monetary and multidimensional) and to analyze changes in living standards over time. It is also used by the Ministry of Social Development to calculate the aid eligibility equation.
To provide data for national accounts for final consumption of the household sector.
To provide weights data that reflect the relative importance of consumer spending items used in the preparation of consumer price index.
To access data on non-cash consumption such as consumption of own produced products and in-kind payments.
To know sources of income generation and household ownership of durable goods, tenure and agricultural property.
To know characteristics of the dwelling, and the availability of services within the dwelling.
To know the consumption expenditure patterns and the impact of social variables on them.
To calculate the average monthly and annual expenditure of the individual and households on items of commodities and services and to know the factors affecting expenditure, such as educational, social and other levels.
To obtain data on household consumption and expenditure levels that can be used to determine poverty levels (monetary and multidimensional) and to analyze changes in living standards over time. It is also used by the Ministry of Social Development to calculate the aid eligibility equation.
To provide data for national accounts for final consumption of the household sector.
To provide weights data that reflect the relative importance of consumer spending items used in the preparation of consumer price index.
To access data on non-cash consumption such as consumption of own produced products and in-kind payments.
To know sources of income generation and household ownership of durable goods, tenure and agricultural property.
To know characteristics of the dwelling, and the availability of services within the dwelling.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Palestinian Household
Version
Version Description
V1.0: (Public use file)
Version Date
2025-04-30
Version Notes
The main indicators of the PECS 2023 survey are published only for the West Bank, since data is intended to be collected for the entire year, ensuring that the main indicators regarding monthly average expenditure and consumption accounts for seasonality. However, due to the interruption of data collection in Gaza Strip during the last quarter of 2023 due to the Israeli aggression, the available data cannot accurately represent monthly expenditure and consumption. Consequently, a decision was made not to publish these indicators for Gaza in the survey's output tables.
Scope
Notes
Main Components of the PECS:
- Demographic and Socioeconomic Characteristics,
- Labor Force and Employment Status
- Housing Conditions and Utilities
- Social Assistance and Coping Strategies
- Household Income and Sources of Revenue
- Household Expenditure and Consumption Patterns
- Demographic and Socioeconomic Characteristics,
- Labor Force and Employment Status
- Housing Conditions and Utilities
- Social Assistance and Coping Strategies
- Household Income and Sources of Revenue
- Household Expenditure and Consumption Patterns
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| consumption/consumer behaviour [1.1] | CESSDA | Link |
Keywords
| Keyword | Vocabulary | URI |
|---|---|---|
| Standards of Living | قاعدة المصطلحات والمؤشرات الإحصائية | Link |
| Food Security | قاعدة المصطلحات والمؤشرات الإحصائية | Link |
| Poverty Percentage | قاعدة المصطلحات والمؤشرات الإحصائية | Link |
| Percentage of Poverty Gap | قاعدة المصطلحات والمؤشرات الإحصائية | Link |
| Average Household Consumption | قاعدة المصطلحات والمؤشرات الإحصائية | Link |
| Average Household Expenditure | قاعدة المصطلحات والمؤشرات الإحصائية | Link |
Coverage
Geographic Coverage
The Palestinian Expenditure and Consumption Survey (PECS) 2023 covers all Palestinian governorates in both the West Bank and Gaza Strip and all locality types; urban, rural and camps.
The survey is designed to provide representative data at the national level and both regions; West Bank and Gaza Strip. However, due to the Israeli aggression on Gaza started in the last quarter of 2023, data collection in Gaza was forcibly stopped. While some indicators from Gaza are included in the published report, a note clarifies that the data is incomplete and does not reflect Gaza's situation.
The survey is designed to provide representative data at the national level and both regions; West Bank and Gaza Strip. However, due to the Israeli aggression on Gaza started in the last quarter of 2023, data collection in Gaza was forcibly stopped. While some indicators from Gaza are included in the published report, a note clarifies that the data is incomplete and does not reflect Gaza's situation.
Universe
The target population of the Palestinian Expenditure and Consumption Survey (PECS) 2023 consists of all Palestinian households in the West Bank and Gaza Strip living in Palestine during 2023.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Palestinian Central Bureau of Statistics | دولة فلسطين |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| United Nations International Children's Emergency Fund | UNICEF | Funding |
| World Food Programme | WFP | Funding |
| World Bank | WB | Funding |
| European Union | EU | Funding |
Other Identifications/Acknowledgments
| Name | Role |
|---|---|
| European Union | Funding |
| World Bank | Funding |
| United Nations International Children's Emergency Fund | Funding |
| World Food Programme | Funding |
Sampling
Sampling Procedure
Target Population
The target population consists of all Palestinian households and individuals who were living normally with their households in the State of Palestine in 2023.
Sampling Frame
The sampling frame is based on a comprehensive sample selected from the Population, Housing, and Establishment Census, 2017. This comprehensive sample consists of geographically proximate areas (average of 150 households per area), known as enumeration areas (EAs) used in the census. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.
Sample Size
The sample size for the Palestinian Expenditure and Consumption Survey, 2023 was 7,032 households for the entire year; 4,992 for the West Bank and 2,040 for Gaza Strip. The non-response rate was assumed based on data from 2016/2017 for each governorate.
Sample Design
The sample is a two-stage stratified cluster random sample:
First stage: Selection of a stratified random sample of 586 enumeration areas.
Second stage: Selection of a systematic random sample of 12 households from each enumeration area selected in the first stage.
The enumeration areas were divided into four quarters, with each quarter's sample including all design strata as much as possible (governorate and locality type).
Sample Strata
The population was divided into strata as follows:
1.Governorate.
2.Locality type (urban, rural, refugee camps).
Sample Allocation
The sample was distributed using the Neyman allocation method, where the distribution relied on specific parameters such as the mean and standard deviation.
The target population consists of all Palestinian households and individuals who were living normally with their households in the State of Palestine in 2023.
Sampling Frame
The sampling frame is based on a comprehensive sample selected from the Population, Housing, and Establishment Census, 2017. This comprehensive sample consists of geographically proximate areas (average of 150 households per area), known as enumeration areas (EAs) used in the census. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.
Sample Size
The sample size for the Palestinian Expenditure and Consumption Survey, 2023 was 7,032 households for the entire year; 4,992 for the West Bank and 2,040 for Gaza Strip. The non-response rate was assumed based on data from 2016/2017 for each governorate.
Sample Design
The sample is a two-stage stratified cluster random sample:
First stage: Selection of a stratified random sample of 586 enumeration areas.
Second stage: Selection of a systematic random sample of 12 households from each enumeration area selected in the first stage.
The enumeration areas were divided into four quarters, with each quarter's sample including all design strata as much as possible (governorate and locality type).
Sample Strata
The population was divided into strata as follows:
1.Governorate.
2.Locality type (urban, rural, refugee camps).
Sample Allocation
The sample was distributed using the Neyman allocation method, where the distribution relied on specific parameters such as the mean and standard deviation.
Response Rate
Response rate was 70.3%
Weighting
Weights Calculation
The weight of a statistical unit (sampling unit) is defined as the reciprocal of the probability of selecting that unit. The survey sample is a stratified, clustered, systematic random sample implemented in two stages. During the first stage, the weight of the enumeration areas is determined based on the probability of selecting each area. In the second stage, the household weight is calculated within each selected enumeration area. The initial household weight is obtained by multiplying the first stage weight by the second stage weight. These weights are subsequently adjusted using mid-2023 household estimates, with the adjustment categories being the strata (governorate and type of locality). This process yields the final household weight. An additional stage was introduced to calculate the weights using the RIM (Revised Iterative Method) algorithm, which is employed in many statistical applications to enhance estimates and model parameters in distribution models.
rw variable used as the relative household weight in the West Bank and Gaza Strip for the first three quarters of the year 2023
rw_wb variable used as the relative household weight in the West Bank over the year of 2023
The weight of a statistical unit (sampling unit) is defined as the reciprocal of the probability of selecting that unit. The survey sample is a stratified, clustered, systematic random sample implemented in two stages. During the first stage, the weight of the enumeration areas is determined based on the probability of selecting each area. In the second stage, the household weight is calculated within each selected enumeration area. The initial household weight is obtained by multiplying the first stage weight by the second stage weight. These weights are subsequently adjusted using mid-2023 household estimates, with the adjustment categories being the strata (governorate and type of locality). This process yields the final household weight. An additional stage was introduced to calculate the weights using the RIM (Revised Iterative Method) algorithm, which is employed in many statistical applications to enhance estimates and model parameters in distribution models.
rw variable used as the relative household weight in the West Bank and Gaza Strip for the first three quarters of the year 2023
rw_wb variable used as the relative household weight in the West Bank over the year of 2023
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2023-01-02 | 2024-01-10 | 5 years |
Time periods
| Start date | End date |
|---|---|
| 2023-01-01 | 2023-12-31 |
Data Collection Mode
Computer Assisted Personal Interviewing - CAPI
Supervision
The total number of candidates for work was 61 fieldworkers in the West Bank, including 12 reserve fieldworkers, 9 supervisors, and 1 editor for Jerusalem J1. In Gaza Strip, the team consisted of 26 fieldworkers, including 6 reserve fieldworkers and 3 supervisors.
PCBS fieldworkers made regular visits to households during the registration period, ranging from 8-10 visits per month, to obtain more reliable data. There were also periodic field and office visits by project management and Technical Committee members, distributed across governorates, totaling about 8-15 visits per month.
PCBS fieldworkers made regular visits to households during the registration period, ranging from 8-10 visits per month, to obtain more reliable data. There were also periodic field and office visits by project management and Technical Committee members, distributed across governorates, totaling about 8-15 visits per month.
Data Collection Notes
The team was called to work on the survey based on the final exam results and the evaluation of the trainees' performance during the training course, considering their attendance and participation. Training started on Monday, 12/12/2022, and ended on Thursday, 22/12/2022, which lasted for 9 days. The total number of trainees was 61 in the West Bank and 26 in Gaza Strip, where some withdrew at the beginning of the course, for which replacements were called in. The training was unified and centralized, conducted via videoconference for Gaza Strip, and led by a group of trainers specialized in their respective subjects (education, labor, housing… etc.). The training covered statistical knowledge, the questionnaire, the registration book, the registration mechanism, conducting interviews, and using maps.
The team was distributed according to the sample for each governorate. The total number of candidates for work was 61 fieldworkers in the West Bank, including 12 reserve fieldworkers, 9 supervisors, and 1 editor for Jerusalem J1. In Gaza Strip, the team consisted of 26 fieldworkers, including 6 reserve fieldworkers and 3 supervisors.
Data Collection
Data collection for the Household Expenditure and Consumption Survey, 2023 was conducted electronically via a custom application on tablets, reflecting the survey questionnaire. This application included initial electronic auditing rules linking all questionnaire sections. Data collection began on Monday, 02/01/2023, and ended on Wednesday, 10/01/2024, in the West Bank. For Gaza Strip, data collection ceased on 06/10/2023 due to Israeli aggression. For the registration (diary) book that remains with the household, entries were initially written manually on paper by the household, and during subsequent visits (8-10 visits per month), the fieldworker ensured the recorded data's accuracy and promptly entered them into the application. In Jerusalem J1 areas, data collection remained manual using paper forms due to Israeli occupation restrictions.
Field Supervision and Editing
PCBS fieldworkers made regular visits to households during the registration period, ranging from 8-10 visits per month, to obtain more reliable data. There were also periodic field and office visits by project management and Technical Committee members, distributed across governorates, totaling about 8-15 visits per month.
Electronic Auditing:
Tablets were used for data collection through an application reflecting the survey questionnaire, incorporating initial automatic audit rules for real-time data transfer to the central database. During this phase, initial audit rules enhanced data reliability by addressing potential errors during data collection through:
- Validating responses in real-time to ensure they fall within expected ranges or formats.
- Enforcing mandatory questions, preventing progress until all required fields are completed.
- Automatically flagging inconsistent or abnormal responses with a note for the fieldworker to review and verify.
Office Editing:
For Jerusalem J1 forms, they were submitted weekly to the central office editor for review, ensuring data accuracy and consistency between sections, and addressing any inconsistent or abnormal values with fieldworkers. The reviewed forms were then handed over to the coding Division and subsequently to the data entry Division.
Data collection was disrupted in the Gaza Strip during the last quarter of 2023 due to the Israeli aggression.
The team was distributed according to the sample for each governorate. The total number of candidates for work was 61 fieldworkers in the West Bank, including 12 reserve fieldworkers, 9 supervisors, and 1 editor for Jerusalem J1. In Gaza Strip, the team consisted of 26 fieldworkers, including 6 reserve fieldworkers and 3 supervisors.
Data Collection
Data collection for the Household Expenditure and Consumption Survey, 2023 was conducted electronically via a custom application on tablets, reflecting the survey questionnaire. This application included initial electronic auditing rules linking all questionnaire sections. Data collection began on Monday, 02/01/2023, and ended on Wednesday, 10/01/2024, in the West Bank. For Gaza Strip, data collection ceased on 06/10/2023 due to Israeli aggression. For the registration (diary) book that remains with the household, entries were initially written manually on paper by the household, and during subsequent visits (8-10 visits per month), the fieldworker ensured the recorded data's accuracy and promptly entered them into the application. In Jerusalem J1 areas, data collection remained manual using paper forms due to Israeli occupation restrictions.
Field Supervision and Editing
PCBS fieldworkers made regular visits to households during the registration period, ranging from 8-10 visits per month, to obtain more reliable data. There were also periodic field and office visits by project management and Technical Committee members, distributed across governorates, totaling about 8-15 visits per month.
Electronic Auditing:
Tablets were used for data collection through an application reflecting the survey questionnaire, incorporating initial automatic audit rules for real-time data transfer to the central database. During this phase, initial audit rules enhanced data reliability by addressing potential errors during data collection through:
- Validating responses in real-time to ensure they fall within expected ranges or formats.
- Enforcing mandatory questions, preventing progress until all required fields are completed.
- Automatically flagging inconsistent or abnormal responses with a note for the fieldworker to review and verify.
Office Editing:
For Jerusalem J1 forms, they were submitted weekly to the central office editor for review, ensuring data accuracy and consistency between sections, and addressing any inconsistent or abnormal values with fieldworkers. The reviewed forms were then handed over to the coding Division and subsequently to the data entry Division.
Data collection was disrupted in the Gaza Strip during the last quarter of 2023 due to the Israeli aggression.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Palestinian Central Bureau of Statistics | PCBS | Palestinian National Authority |
Questionnaires
Questionnaires
The PECS, 2017 was the basis for designing the main survey questionnaire for the 2023 round. To ensure continuity and comparability between PECS surveys.
The data will be collected during the registration month during the visit of the fieldworker to the household, and include the following sections:
First part (Cover page): This section records the necessary household information, including the date of visit, data on field and office staff, and the number of household members by gender.
Second part: Contains demographic and social questions about household members.
Third part: Includes general questions about the characteristics of the labor force.
Fourth part: Covers housing characteristics, including various topics such as type of housing, number of rooms, house ownership, rental value, access to services like electricity, water, and sanitation, main source of cooking fuel and heating, and distance to transportation, education, and health centers.
Fifth part: Contains data on the consumer basket, which includes around 950 goods and services, described with their measurement units (kilogram, liter, and number), quantity, and value.
Sixth part: Contains questions on social assistance and adaptation strategies, including the type and value of assistance received by the household or individuals, its source and frequency, and the circumstances and shocks experienced by the household or its members.
Seventh part: Contains questions about income and means of income generation, as well as data on monthly and annual income, collected from different sources at the household level at the end of the registration period.
Note: Additional questions have been added to some of the parts to cover indicators of poverty and multidimensional child poverty.
The used language was Arabic.
The data will be collected during the registration month during the visit of the fieldworker to the household, and include the following sections:
First part (Cover page): This section records the necessary household information, including the date of visit, data on field and office staff, and the number of household members by gender.
Second part: Contains demographic and social questions about household members.
Third part: Includes general questions about the characteristics of the labor force.
Fourth part: Covers housing characteristics, including various topics such as type of housing, number of rooms, house ownership, rental value, access to services like electricity, water, and sanitation, main source of cooking fuel and heating, and distance to transportation, education, and health centers.
Fifth part: Contains data on the consumer basket, which includes around 950 goods and services, described with their measurement units (kilogram, liter, and number), quantity, and value.
Sixth part: Contains questions on social assistance and adaptation strategies, including the type and value of assistance received by the household or individuals, its source and frequency, and the circumstances and shocks experienced by the household or its members.
Seventh part: Contains questions about income and means of income generation, as well as data on monthly and annual income, collected from different sources at the household level at the end of the registration period.
Note: Additional questions have been added to some of the parts to cover indicators of poverty and multidimensional child poverty.
The used language was Arabic.
Data Processing
Data Editing
Electronic Auditing:
Tablets were used for data collection through an application reflecting the survey questionnaire, incorporating initial automatic audit rules for real-time data transfer to the central database. During this phase, initial audit rules enhanced data reliability by addressing potential errors during data collection through:
-Validating responses in real-time to ensure they fall within expected ranges or formats.
-Enforcing mandatory questions, preventing progress until all required fields are completed.
-Automatically flagging inconsistent or abnormal responses with a note for the fieldworker to review and verify.
Office Editing:
For Jerusalem J1 forms, they were submitted weekly to the central office editor for review, ensuring data accuracy and consistency between sections, and addressing any inconsistent or abnormal values with fieldworkers. The reviewed forms were then handed over to the coding Division and subsequently to the data entry Division.
Data Processing
Tablets Application and Data Entry Platform
The survey form was developed as a tablet application linked to the sample to facilitate data collection for fieldworkers. This application provided an easy-to-use interface, allowing fieldworkers to navigate the form easily, ensuring accurate and consistent data entry. Integrated with GPS and GIS technologies, the application provided real-time location tracking and interactive maps to guide fieldworkers in identifying household units in the sample.
For paper forms in Jerusalem J1, the data entry program was designed to align with the survey form application with automatic audit rules. Data entry was done promptly after office editing and coding at PCBS main premises. Data entry program with the initial audit rules enhanced data reliability by addressing potential errors during data entry through:
-Real-time validation of responses to ensure they fall within expected ranges or formats.
-Enforcing mandatory questions, preventing progress until all required fields are completed.
-Automatically flagging inconsistent or abnormal responses with a note for the fieldworker to review and verify.
Office Data Cleaning Techniques
The automatic and secure transfer of survey data to the central database was done in real-time, allowing data sets to be downloaded in the agreed format and design between project management and the data processing department. Data cleaning and quality assurance were performed using various statistical software, primarily R programming language via its RStudio interface, along with SPSS and Excel. This stage included detailed data cleaning and quality assurance processes to:
-Verify variable types within the databases.
-Detect outlier values for both numerical and categorical variables using different statistical methods and check relationships between variables to identify unexpected correlations or their absence.
-Check data consistency and logical coherence across similar questions or sections.
-Verify missing data due to technical or human errors.
All values that failed cleaning stages were periodically sent to the field for verification and follow-up with households if necessary.
Tablets were used for data collection through an application reflecting the survey questionnaire, incorporating initial automatic audit rules for real-time data transfer to the central database. During this phase, initial audit rules enhanced data reliability by addressing potential errors during data collection through:
-Validating responses in real-time to ensure they fall within expected ranges or formats.
-Enforcing mandatory questions, preventing progress until all required fields are completed.
-Automatically flagging inconsistent or abnormal responses with a note for the fieldworker to review and verify.
Office Editing:
For Jerusalem J1 forms, they were submitted weekly to the central office editor for review, ensuring data accuracy and consistency between sections, and addressing any inconsistent or abnormal values with fieldworkers. The reviewed forms were then handed over to the coding Division and subsequently to the data entry Division.
Data Processing
Tablets Application and Data Entry Platform
The survey form was developed as a tablet application linked to the sample to facilitate data collection for fieldworkers. This application provided an easy-to-use interface, allowing fieldworkers to navigate the form easily, ensuring accurate and consistent data entry. Integrated with GPS and GIS technologies, the application provided real-time location tracking and interactive maps to guide fieldworkers in identifying household units in the sample.
For paper forms in Jerusalem J1, the data entry program was designed to align with the survey form application with automatic audit rules. Data entry was done promptly after office editing and coding at PCBS main premises. Data entry program with the initial audit rules enhanced data reliability by addressing potential errors during data entry through:
-Real-time validation of responses to ensure they fall within expected ranges or formats.
-Enforcing mandatory questions, preventing progress until all required fields are completed.
-Automatically flagging inconsistent or abnormal responses with a note for the fieldworker to review and verify.
Office Data Cleaning Techniques
The automatic and secure transfer of survey data to the central database was done in real-time, allowing data sets to be downloaded in the agreed format and design between project management and the data processing department. Data cleaning and quality assurance were performed using various statistical software, primarily R programming language via its RStudio interface, along with SPSS and Excel. This stage included detailed data cleaning and quality assurance processes to:
-Verify variable types within the databases.
-Detect outlier values for both numerical and categorical variables using different statistical methods and check relationships between variables to identify unexpected correlations or their absence.
-Check data consistency and logical coherence across similar questions or sections.
-Verify missing data due to technical or human errors.
All values that failed cleaning stages were periodically sent to the field for verification and follow-up with households if necessary.
Data Appraisal
Estimates of Sampling Error
Sampling Errors
The data in this survey are subject to sampling errors, as they are derived from a sample rather than a full census of the study population. Consequently, there may be differences between the estimated values and the true population values that would be obtained from a complete census. To assess the reliability of the estimates, sampling variances were calculated for the survey's key indicators using SPSS, particularly focusing on the coefficient of variation (CV) as a measure of relative precision.
The variance analysis indicated that there were no significant issues in data dissemination at the West Bank level. More information are seen in the attached report in page 39 in the English version after the Arabic.
The data in this survey are subject to sampling errors, as they are derived from a sample rather than a full census of the study population. Consequently, there may be differences between the estimated values and the true population values that would be obtained from a complete census. To assess the reliability of the estimates, sampling variances were calculated for the survey's key indicators using SPSS, particularly focusing on the coefficient of variation (CV) as a measure of relative precision.
The variance analysis indicated that there were no significant issues in data dissemination at the West Bank level. More information are seen in the attached report in page 39 in the English version after the Arabic.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Division of user services | Palestinian Central Bureau of Statistics | Dus@pcbs.gov.ps | www.pcbs.gov.ps |
| Diwan | Palestinian Central Bureau of Statistics | Diwan@pcbs.gov.ps | www.pcbs.gov.ps |
Confidentiality
General Statistics Law No. (5) for Year 2000
Article (17)
1. All individual information and data submitted to the Bureau for statistical purposes shall be treated as confidential and shall not be divulged, in whole or in part, to any individual or to a public or private body,
or used for any purpose other than for preparing statistical tables.
2. The Bureau shall endeavor to issue official statistical publications in aggregate tables, which do not disclose individual data, in conformity with the confidentiality of statistical data.
Access conditions
1. Pledges the utilization of "data" or any copies thereof shall be limited to the purposes agreed upon including not granting any third parties any access to these data. Restrictions applies to any data duplication
or transformed setting for purposes other than meeting the requirements of the statistical programs used in data analysis.
2. Utilization of "data" or any copies thereof is limited to personal computers normally .
3. Pledges not to alter the value of any observation in the original "data"; nevertheless, this does not apply on subjecting data to any processes or procedures aiming to derive new variables. The first party does
not bear any professional, administrative or financial responsibility for any losses incurred as a result of changes in the variables values.
or transformed setting for purposes other than meeting the requirements of the statistical programs used in data analysis.
2. Utilization of "data" or any copies thereof is limited to personal computers normally .
3. Pledges not to alter the value of any observation in the original "data"; nevertheless, this does not apply on subjecting data to any processes or procedures aiming to derive new variables. The first party does
not bear any professional, administrative or financial responsibility for any losses incurred as a result of changes in the variables values.
Citation requirements
Palestinian Central Bureau of Statistics. Main Findings of Living Standards in the West Bank (Expenditure, Consumption and Poverty), 2023. V1.0(08-2024). Ramallah - Palestine.
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Palestinian Central Bureau of Statistics (PCBS) | State of Palestine | Diwan@pcbs.gov.ps | www.pcbs.gov.ps |
| Palestinian Central Bureau of Statistics (PCBS) | State of Palestine | Dus@pcbs.gov.ps | www.pcbs.gov.ps |
Disclaimer and copyrights
Disclaimer
PCBS provid data collected for purely statistical purposes, and therefore does not assume any responsibility for legal or professional from any claim or analysis or interpretation or misuse of this data.
Copyright
© All Rights Reserved. Palestinian Central Bureau of Statistics, 2023
Metadata production
DDI Document ID
DDI-PSE-PCBS-PECS-2023-V1.0
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Palestinian Central Bureau of Statistics (PCBS) | PCBS | State of Palestine | Data collection, processing and dissemination |
Date of Metadata Production
2024-08-07
DDI Document version
V1.0