The total population in Palestine was estimated at 5.4 million people in 2023, according to the latest census figures and projections from Trading Economics. This dataset provides - Palestine Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.

The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

Geographic coverage

National Coverage. The sample includes East Jerusalem.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above. The sample is nationally representative.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.

Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid.

Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.

The sample size in the majority of economies was 1,000 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.

State of Palestine (West Bank and Gaza) Crude Death Rate: per 1000 Population: Gaza Strip data was reported at 3.500 NA in 2018. This records an increase from the previous number of 3.400 NA for 2017. State of Palestine (West Bank and Gaza) Crude Death Rate: per 1000 Population: Gaza Strip data is updated yearly, averaging 3.950 NA from Dec 1997 (Median) to 2018, with 18 observations. The data reached an all-time high of 4.700 NA in 1997 and a record low of 3.300 NA in 2016. State of Palestine (West Bank and Gaza) Crude Death Rate: per 1000 Population: Gaza Strip data remains active status in CEIC and is reported by Palestinian Central Bureau of Statistics. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.G002: Vital Statistics.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National Coverage. Sample includes East Jerusalem.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size in West Bank and Gaza was 1,000 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Areas with security concerns close to the Israeli borders, areas that are accessible only to special Israeli permit holders, and areas with population concentrations less than 1000 people were excluded. The excluded areas represent less than 2% of the population. The sample includes East Jerusalem.

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for West Bank and Gaza is 1000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

The Palestinian Multiple Indicator Cluster Survey (PMICS) was carried out in 2014 by Palestinian Central Bureau of Statistics in collaboration with Ministry of Health, as part of the global MICS programme. Technical and financial support was provided by the Palestinian Government, the United Nations Children’s Fund (UNICEF) and United Nations Population Fund (UNFPA). The global MICS programme was developed by UNICEF in the 1990s as an international household survey programme to support countries in the collection of internationally comparable data on a wide range of indicators on the situation of children and women. MICS surveys measure key indicators that allow countries to generate data for use in policies and programmes, and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. The Palestinian Multiple Indicator Cluster Survey has as its primary objectives: To furnish data needed for monitoring progress toward goals established in the Millennium Declaration and other internationally agreed upon goals, as a basis for future action. To contribute to the improvement of data and monitoring systems in Palestine and to strengthen technical expertise in the design, implementation, and analysis of such systems. The Palestinian Multiple Indicator Cluster Survey, 2014 was conducted for a representative sample of Palestine. The survey was designed as a multi- stage cluster sample covering the entire country including two geographic regions; The West Bank which includes 11 governorates: (Jenin, Tubas, Tulkarm, Qalqiliya, Salfit, Nablus, Ramallah and Al Bireh, Jerusalem, Jericho and Al Aghwar, Bethlehem, Hebron) and Gaza Strip which includes 5 governorates (Gaza, Khan Yunis, Rafah, Deir El Balah and North Gaza) and was stratified according to urban, rural and camp areas. Of the 11,125 households selected in the sample, results showed that the number of occupied households were 10,568 of which 10,182 households were successfully interviewed during the survey, giving a response rate of 96 percent. There were 13,964 women in the 15-49 age group of which a total of 13,367 eligible women were successfully interviewed, achieving a response rate of 96 percent. In addition, the number of children was 7,919 child in the Household Questionnaire of which a total of 7,816 child were interviewed giving a response rate of 99 percent. The total households interviewed included 56,367 individual members who were listed. Of these, 28,542 were males and 27,825 were females with a sex ratio of 103 males per hundred females. It is noted that the Palestinian population is a young one. The percentage of individuals in the age group 0-17 years was 46 percent, whereas the percentage of individuals in the age group 18 and above was 54 percent. According to economic and social dependency categories, 39 percent individuals were in the age group 0-14 years, 58 percent in the age group 15-64 years which is the age category of economically active individuals; and 3 percent in the age group 65 years and over. The average household size in Palestine in 2014 was about 5.5 persons. About 91 percent of households are headed by men and about 9 percent of households are headed by women. The findings pertain to March-April 2014, when the fieldwork was conducted.

Abstract

The Agricultural Census aims in general to establish an updated, detailed and accurate holdings database to assist in planning and policy making at all levels related to the agricultural sector. It also aims in specific to provide data on the structure of agriculture, especially for small administrative and geographical units, rare items, and to enable detailed cross-tabulations, and to provide data that can be used as a benchmark for reconciliation of current agricultural statistics; and for setting estimates for subsequent years, in addition to provide frames for agricultural sampling surveys.

Geographic coverage

The census also covered all geographical levels in the West Bank and Gaza Strip, so that: 1. Implementation of a comprehensive listing in Gaza Strip that enumeration areas represent more than 5% of households that practice agricultural activity, according to the Population, Housing and Establishments Census, 2017 data. 2. Visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census, 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4%. 3. Implementation of a comprehensive listing in the West Bank for all localities except camps and city centers in the following governorates (Nablus, Ramallah & Al-Bireh, Hebron and J2 in Jerusalem Governorate). 4. Implementation of a comprehensive listing in the enumeration areas of camps and city centers in the following governorates (Nablus, Ramallah, Al-Bireh, Hebron and J2 of Jerusalem Governorate), for households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017, more than 5%, and visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4% in the same locality mentioned above. 5. About Jerusalem J1, a different methodology is applied in two phases. In the first phase, research and investigation are carried out in cooperation with responsible and dignitaries in Jerusalem J1 on agricultural holdings and holders, and in the second phase, enumeration of the holdings that were monitored in the first phase.

Analysis unit

Agricultural Holding

Universe

Includes agricultural holdings in Palestine in 2021

Kind of data

Census/enumeration data [cen]

Sampling procedure

The frame of the Agriculture Census includes a complete record of households and non-household agricultural holdings, where all households are enumerated and the household agricultural holdings are identified, in addition to a list of non-households holdings that is obtained by listing all buildings as well as a list from the Ministry of Agriculture which includes cooperative societies/charity societies, companies, and government and private holdings…etc.

The census also covered all geographical levels in the West Bank and Gaza Strip, so that: 1. Implementation of a comprehensive listing in Gaza Strip that enumeration areas represent more than 5% of households that practice agricultural activity, according to the Population, Housing and Establishments Census, 2017 data. 2. Visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census, 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4%. 3. Implementation of a comprehensive listing in the West Bank for all localities except camps and city centers in the following governorates (Nablus, Ramallah & Al-Bireh, Hebron and J2 in Jerusalem Governorate). 4. Implementation of a comprehensive listing in the enumeration areas of camps and city centers in the following governorates (Nablus, Ramallah, Al-Bireh, Hebron and J2 of Jerusalem Governorate), for households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017, more than 5%, and visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4% in the same locality mentioned above. 5. About Jerusalem J1, a different methodology is applied in two phases. In the first phase, research and investigation are carried out in cooperation with responsible and dignitaries in Jerusalem J1 on agricultural holdings and holders, and in the second phase, enumeration of the holdings that were monitored in the first phase.

Sampling deviation

Not applicable

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Computerized program

Cleaning operations

Post enumeration data processing phase was limited to final examination and cleaning of Agricultural Census databases, with documentation of examinations on all topics of Agricultural Census 2021 questions. Data processing phase focused on the following: 1. Checking the allowed transfers and values. 2. Checking the consistency between different questions of the census questionnaire based on logical relationships. 3. Checking on the basis of relations between certain questions so that a list of non-identical cases was extracted, reviewed and identified the source of the error case by case, and if such errors were immediately modified and corrected based on the source of the error3. Checking on the basis of relations between certain questions so that a list of non-identical cases was extracted, reviewed and identified the source of the error case by case, and if such errors were immediately modified and corrected based on the source of the error.

Response rate

Not Applicable.

Sampling error estimates

The sampling errors occur during the sample-based surveys but not in censuses as it is a comprehensive inventory of all agricultural holdings. These errors are easy to measure with the error point estimate also, since it is considered as an error in the sample.

Data appraisal

The non-sampling errors occur at any stage during the implementation of censuses and surveys. Therefore, it is necessary to provide for a data quality control system to ensure maximum accuracy. Many of these stages were used during the agriculture census planning and implementation where are-interview was carried out as follows:

• There are two models that were used to collect data and were uploaded to tablets. The first model is to enumerate households in all enumeration areas; in which the percentage of households that practiced an agricultural activity (according to the data of the Population, Housing and Establishments Census, 2017) is 5% or more, and the second model was used if the household had agricultural holdings.

• The enumerator visited Palestinian households in the enumeration areas in which the percentage of households that practiced agricultural activity (according to the data of the Population, Housing and Establishments Census, 2017) is less than 5%, so that the inventory model and the model prepared for agricultural holdings were if the tenure conditions were met.

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The target population in the sample survey comprises all households living in the West Bank and Gaza Strip, excluding nomads and students.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered a national sample of households and all permanently residing individuals in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

In the absence of a population census since 1967, the major task, with regard to constructing master sample, was developing a frame of suitable units covering the whole country. Such units have been used as the PSUs (Primary Sampling Units) in the first stage of selection. For the second stage of selection, all PSUs have been listed in the field at the household level. This provided a sampling frame for selecting the households.

Sample design:

The sample design is, therefore, a stratified two-stage design for households selected to be interviewed. Four levels of stratification have been made: 1. Stratification by District. 2. Stratification by place of residence, which comprises: (a) Municipalities (b) Villages (C) refugees camps 3. Stratification by locality size 4. Stratification by cell identification in that order

Sample size:

The sample size is about 4893 households allowing for non-response and related losses.

Target cluster size:

The target cluster size or "sample-take" is the average number of households to be selected per PSU. In this survey, the sample take is around 10 households.

Detailed information/formulas on the sampling design are available in the user manual.

Sampling deviation

The standard errors for the main survey estimates were calculated to give the user an idea of their reliability or precision. Whereas, the variance was calculated using the method of ultimate clusters within any domain of estimation.

Detailed information on the sampling design deviation and calculation of the variance is available in the user manual.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First section: Certain articles / provisions of the form filled at the beginning of the month, and the remainder filled out at the end of the month. The questionnaire includes the following provisions:

Cover sheet: It contains detailed and particulars of the family, date of visit, particular of the field/office work team, number/sex of the family members.

Statement of the family members: Contains social, economic and demographic particulars of the selected family.

Statement of the long-lasting commodities and income generation activities: Includes a number of basic and indispensable items (i.e, Livestock, or agricultural lands).

Housing Characteristics: Includes information and data pertaining to the housing conditions, including type of shelter, number of rooms, ownership, rent, water, electricity supply, connection to the sewer system, source of cooking and heating fuel, and remoteness/proximity of the house to education and health facilities.

Monthly and Annual Income: Data pertaining to the income of the family is collected from different sources at the end of the registration / recording period.

Second section: The second section of the questionnaire includes a list of 54 consumption and expenditure groups itemized and serially numbered according to its importance to the family. Each of these groups contains important commodities. The number of commodities items in each for all groups stood at 707 commodities and services items. Groups 1-21 include food, drink, and cigarettes. Group 22 includes homemade commodities. Groups 23-45 include all items except for food, drink and cigarettes. Groups 50-54 include all of the long-lasting commodities. Data on each of these groups was collected over different intervals of time so as to reflect expenditure over a period of one full year.

Cleaning operations

Raw Data

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all 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 run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

Excluding the uninhabited housing units, the survey sample is (4806) households, from which (3422) households are in the West Bank, and (1384) households are in Gaza Strip. A total of (4584) households completed the questionnaire: (3213) household in the West bank and (1335) households in Gaza Strip. The non-response rate is, accordingly, 5.7% for all the Palestinian territory.

Sampling error estimates

Generally, surveys samples are exposed to two types of errors. The statistical errors, being the first type, result from studying a part of a certain society and not including all its sections. And since the Household Expenditure and Consumption Surveys are conducted using a sample method, statistical errors are then unavoidable. Therefore, a potential sample using a suitable design has been employed whereby each unit of the society has a high chance of selection. Upon calculating the rate of bias in this survey, it appeared that the data is of high quality. The second type of errors is the non-statistical errors that relate to the design of the survey, mechanisms of data collection, and management and analysis of data. Members of the work commission were trained on all possible mechanisms to tackle such potential problems, as well as on how to address cases in which there were no responses (representing 3.1%).