The estimated population of the Gaza Strip for 2023 was around 2.1 million people. The Palestinian population of Gaza is relatively young when compared globally. More than half of Gazans are 19 years or younger. This is due to the comparably high fertility rate in the Gaza Strip of *** children per woman as of 2022.

Population ages 65 and above, total in Palestine was reported at 196427 Persons in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Palestine - Total Population for Age 65 and above (only 2005 and 2010) (in number of people) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Abstract

The survey is designed to collect, analyze, and disseminate demographic and health data pertaining to the Palestinian population living in the Palestinian Territory, with a focus on demography, fertility, infertility, family planning, unmet needs, and maternal and child health, in addition to youth and the elderly. The 2010 survey includes new sections and elements, such as basic health and socio-economic information on different groups within the population: ever married woman less than 55 years and children aged less than five years, child labor in the age 5-14 years, child discipline 2-14 years, person education 5-24 years, youth aged 15-29 years, and elderly people over the age of 60.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates

Analysis unit

Household, individual

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestine.

Kind of data

Sample survey data [ssd]

Sampling procedure

Target Population The target population of the survey consists of all the following groups: 1- All Palestinian households normally residing in the Palestinian Territory. 2- Females aged 15 - 54 years. 3- Elderly people aged 60 or over. 4- Children aged 0 - 14 years and divided into the following categories: 0-5 years, 2-14 years, 5-14 years, with parts of the questionnaire customized for each group. 5- Youth aged 15 - 29 years and divided into the following categories: 15-24 years, 25-29 years, with parts of the questionnaire customized for youth.

Sampling Frame We relied on sampling frames established in PCBS and basically comprising the list of enumeration areas. (The enumeration area is a geographical area containing a number of buildings and housing units of about 120 housing units on average.)

The total frame consists of the following two parts:

1- West Bank and Gaza Sampling Frame: containing enumeration areas drawn up in 2007. In the West Bank: each enumeration area consists of a list of households with identification data to ascertain the address of individual households. In Gaza: each enumeration area contains a list of housing units with addresses to ascertain the address of individual households, plus identification data of the housing units.

2- Jerusalem Sampling Frame (inside checkpoints): contains enumeration areas only, geographically divided with information about the total number of households in these areas. However, there is no detailed information about addresses inside enumeration areas and the size of the enumeration area can be ascertained without the ability to identify the addresses.

Design Strata In the survey, two variables were chosen to divide the population into strata, depending on the homogeneity of parts of the population. Previous studies have shown that Palestinian households may be divided as follows: 1- Governorates: there are 16 governorates in the Palestinian Territory: 11 governorates in the West Bank and 5 in the Gaza Strip. 2- Locality Types: there are three types : urban, rural and refugee camps. All the available frames contain the strata variables. Sample Size We use the following formula to estimate the sample size:

    n  =  [(1.15) f(1-r) (r)4]  
  [(nh) p2(r0.07)]  

Where: - n: sample size requested for the main indicator or main estimate - 4: is a factor to achieve a 95 percent level of confidence - r is the predicted or anticipated prevalence (coverage rate) for the indicator - being estimated - 1.15 is the factor necessary to raise the sample size by 20 percent for non-response - f is the design effect - 0.07r is the margin of error to be tolerated at the 95 percent level of confidence, defined as 7 percent of r (7 percent represents the relative sampling error of r) - p is the proportion of the total population upon which the indicator, r, is based - nh is the average household size

To estimate the sample size of the survey we rely on the percentage of children under 5 years who suffer from stunting. We consider it as the main indicator for the survey (r) and it equals 10.2% (from MICS3 data -2006). Also, by returning to census data in 2007 we find the percentage of children aged 0 - 4 years =14.1%. Finally, the sample size = 15,355

Sample Design and Type After determining the sample size, which equals 15456 households, we selected a probability sample - a multi-stage stratified cluster sample as follows: 1- First stage: selecting a sample of clusters (enumeration areas) using PPS without replacement method to obtain 644 enumeration areas from the total enumeration area frame. 2- Second stage: selecting 24 households from each selected enumeration area of the first stage and using the systematic sample method. When reaching households, we enumerate all the targeted individuals from the groups: women (15-54) years, elderly aged 60 and more, children aged 0-5 years. 3- Third stage: selecting one child of age group 2-14 years for part of the questionnaire and one young person from the 15-29 age group to answer the youth attachment in the questionnaire. We use the Kish table to select one person at random.

Mode of data collection

Face-to-face [f2f]

Research instrument

The design of the survey complied with the standard specifications of health surveys previously implemented by PCBS. In addition, the survey included indicators of MICS4 to meet the needs of all partners.

    1.  Main questionnaire with the following parts:
     · Household questionnaire: Covers demographic and educational characteristics, chronic disease, smoking, discipline of children (2-14 years), child labor (5-14 years), education of children (5-24 years) and housing characteristics.

     · Health of women (15-54 years) regardless of marital status, awareness about AIDS, anemia in women (15-49 years).

     · Ever married women (15-54 years): Covers general characteristics of qualified women, reproduction, child mortality, maternal care, reproductive morbidity, family planning, and attitudes towards reproduction.

     · Children under age of 5: Covers children's health, vaccination against childhood diseases, early childhood development, chronic disease, and anemia.


 2. Attached questionnaires
    ·  Youth questionnaire (15-29 years): Covers general characteristics, awareness and perception of family planning, health status, awareness about sexually transmitted diseases and reproduction.

    ·  Elderly questionnaire (60 years and over): Covers general characteristics, social relations, activities, time-use, health status, and use of mass media.

Cleaning operations

Data editing took place at a number of stages through the processing including:

1. office editing and coding
2. during data entry
3. structure checking and completeness
4. structural checking of SPSS data files

Response rate

The survey sample consists of about 15,355 households of which 13,629 households completed the interview; whereas 8,740 households from the West Bank and 4,889 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 90.5% while in the Gaza Strip it reached 94.8%. The response rate in the Palestinian Territory reached 92.0%.

Sampling error estimates

Detailed information on the sampling Error is available in the Survey Report.

Data appraisal

Different methods were applied in the assessment of the survey data, including: 1. Occurrences of missing values and answers like "other" and "do not know". 2. Examining inconsistencies between the various sections of the questionnaire, including within record and cross-record consistencies. 3. Comparability of data with previous surveys 2000, 2006 and showed logical homogeneity in the results. The results of these assessment procedures show that the data are of high quality and consistency.

State of Palestine (West Bank and Gaza) PS: Prevalence of Stunting: Height for Age: % of Children Under 5: Male data was reported at 11.900 % in 2010. This records a decrease from the previous number of 12.300 % for 2007. State of Palestine (West Bank and Gaza) PS: Prevalence of Stunting: Height for Age: % of Children Under 5: Male data is updated yearly, averaging 12.100 % from Dec 2007 (Median) to 2010, with 2 observations. The data reached an all-time high of 12.300 % in 2007 and a record low of 11.900 % in 2010. State of Palestine (West Bank and Gaza) PS: Prevalence of Stunting: Height for Age: % of Children Under 5: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. Prevalence of stunting, male, is the percentage of boys under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Abstract

The Jerusalem Household Social Survey 2010 is one of the most important statistical activities that have been conducted by PCBS. It is the most detailed and comprehensive statistical activity that PCBS has conducted in Jerusalem. The main objective of the Jerusalem household social survey, 2010 is to provide basic information about: Demographic and social characteristics for the Palestinian society in Jerusalem governorate including age-sex structure, Illiteracy rate, enrollment and drop-out rates by background characteristics, Labor force status, unemployment rate, occupation, economic activity, employment status, place of work and wage levels, Housing and housing conditions, Living levels and impact of Israeli measures on nutrition behavior during Al-Aqsa intifada, Criminal offence, its victims, and injuries caused.

Geographic coverage

Social survey data covering the province of Jerusalem only, the type locality (urban, rural, refugee camps) and Governorate

Analysis unit

households, Individual

Universe

The target population was all Palestinian households living in Jerusalem Governorate.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Sample Frame Were estimated sample size of Jerusalem by 2,075 family, including 1,200 families in the Area J1, and 875 families in the Area of J2 has been the establishment of Sample Frame to Jerusalem (J2) of the General Census of Population and Housing, and Establishment, which was carried out by the PCBS at the end of 2007. And the frame is a list of counting areas, and these areas are used as units an initial preview (PSUs) in the first stage of the process of selecting the sample. Stratified cluster random sample of regular two phases: Phase 1 was selected a stratified random sample of enumeration areas from Jerusalem (J1) and Jerusalem (J2). The number of enumeration areas that have been chosen counting area 75 divided into two Areas : 40 the count of Jerusalem (J1), 35 the count of Jerusalem (J2). Phase 2 Is to choose a random sample (in a field) of the households of the selected enumeration areas are selected so that 30 families from each of the complete count has been selected in the first phase of Jerusalem (J1) and 25 families are selected at random from each Areas regularly count has been selected in the first phase of Jerusalem (J2) on the completion of the data that are a minimum of 20 families from each Areas counted in Jerusalem (J2).

Mode of data collection

Face-to-face [f2f]

Research instrument

A survey questionnaire the main tool for gathering information, so do not need to check the technical specifications for the phase of field work, as required to achieve the requirements of data processing and analysis, has been designed form the survey after examining the experience of other countries on the subject of social surveys, covering the form as much as possible the most important social indicators as recommended by the United Nations, taking into account the specificity of the Palestinian community in this aspect.

Cleaning operations

Data processing:

Input processing programs: Program is designed input beam programming Access, entry screens have been designed and auditing as well as the tests have been developed through automated checking the input and then cleaning the rules of programming questions and to examine variables at the level of form.

Data entry: After the completion of design input, testing and making sure readiness, started work on data entry and after the entrances have been trained to deal with the programs of the entry. Work began on the introduction of survey data as of 26/07/2010 until 28/11/2010. It was the number of entrances who worked on the introduction of statements 5 entrances at a minimum, where the number of employees to enter data commensurate with the flow of forms, note that the flow of the forms on the entry could not be uniform due to the difficulty of transportation because of security conditions, and was checking the forms returned from the entry of by the auditors to complete and re-adjusted and then re-entered its final form after their arrival from the field.

Check and clean the data: Been cleaned data queries run tests and adjust input errors immediately. And re-forms containing errors form to the project manager to deal with them. After the completion of the data entry process began work on the audit and examine the data as follows: 1. Check transitions, and allowed values. 2. Check compatibility and consistency between questions per section and the various departments, and this to us ? E logical relations. 3. Tests based on certain relationships between the different questions, so that was extracted list Balastmarat is matched, review and identify the source of a bug where, if found there are errors in the input was adjusted immediately, and if there are errors, the field was being converted to field work to re-visit again , and correct errors in form, have included the stage of data cleaning in two stages: the stage of cleaning the survey data in terms of consistency and logic and linked to age and date of birth, educational status and other per capita, and consistency of questions of each section of the form of households, while the second stage have included the examination of consistency between the results of Questions Social Survey 2010 and Social Survey of Jerusalem in 2005. Surveys and other surveys such as the impact of expansion and annexation wall on the population, 2008, as well as the Labour Force Survey - third quarter 2010.

Response rate

Were selected (2,374) represented the family of Jerusalem Governorate, a sample size which is equal to the original 2,075 family as well as samples to 299 additional families of Jerusalem (J2) The number of families who were interviewed (1,709) in Jerusalem Governorate, complete Questionnaires 72.0% (1,026) in J1 85.5% (683) in J2 58.2%

Sampling error estimates

Data were collected in a manner that the survey sample and not Balhsr destruction, so she is exposed to two main types of errors. The first sampling errors (statistical errors), and the second non-statistical errors. It is intended that sampling errors of the errors resulting from sample design, so it is easy to measure, the contrast has been calculated and the effect of sample design.

The non-statistical errors are possible to occur in every stage of project implementation, through data collection, inserting, and mistakes can be summarized by the non-response, and response errors (surveyed), and the mistakes of the interview (the researcher) and data-entry errors. To avoid errors and reduce the impact it has made significant efforts through the training of researchers extensive training, and the presence of a group of experts in the concepts and terminology, medical / health, and training on how to conduct interviews, and the things that must be followed during the interview, and the things that should be avoided.

Have been trained on the data entry program entry, program, and were examined in order to see the picture of the situation and reduce any problems, there was constant contact between supervisors and checkers through ongoing visits and periodic meetings. In addition, has been drafting a set of circulars and instructions reminder to the team. Also been circulated answers to questions and problems faced by the researchers during the field work.

As for office work have been trained crew to check the special forms and field detection of errors, which greatly reduces the rates of errors that can occur during field work. In order to reduce the proportion of errors that can occur during entry form to the computer, the software is designed to entry so as not to allow any errors Tnasagah can get during the process of input and contains many of the conditions Logical, where they were loading the program the input of many tests on private answers each question in addition to the relations between the different questions and testing the other logical. This process has led to the disclosure of most of the errors that are not found in previous phases of work, where they were correct all errors that have been discovered.

Data were evaluated according to the following areas: 1. Definition of family members and how to register. 2. Demographic characteristics that have a relationship on Christmas. 3. Breakdown of the profession and activity.

Methods of assessment vary according to the data subject in this survey include the following: 1. Occurrences of missing values and Answers "other" and "Do not know" and examine inconsistencies between different sections or between the date of birth and other sections. Add to examine the internal consistency of the data as part of a logical data and completeness. 2. Compared to survey data with the results of surveys of the relationship and by the Central Bureau of Statistics Palestinian implementation.

Can be summarized as sources of some non-statistical errors that have emerged during the implementation of the survey including the following: Inability to meet the data in some cases the forms because of the lack of a home or be in the housing unit does not exist or are uninhabited and there are families not able to provide some data or refused to do so. Some families did not take the form subject very seriously affecting the quality of the data provided. Errors resulting from the method of asking the question by the researcher in the field. Category understand the question and answer based on his understanding of it. The inability of the technical team overseeing the

State of Palestine (West Bank and Gaza) Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 0.600 % in 2016. This records an increase from the previous number of 0.500 % for 2011. State of Palestine (West Bank and Gaza) Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 0.600 % from Dec 2010 (Median) to 2016, with 3 observations. The data reached an all-time high of 0.700 % in 2010 and a record low of 0.500 % in 2011. State of Palestine (West Bank and Gaza) Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Abstract

The Labour Force Survey focuses mainly on labour force key indicators, main characteristics of the employed, unemployed, underemployed and persons outside labour force, labour force according to level of education, distribution of the employed population by occupation, economic activity, place of work, employment status, hours and days worked and average daily wage in NIS for the employees.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates

Analysis unit

Household, individual

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame

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: All Palestinians aged 10 years and over living in the Palestinian Territory, excluding persons living in institutions such as prisons or shelters. Sampling Frame: The sampling frame consisted of a master sample of enumeration areas (EAs) selected from the population housing and establishment census 2007, the master sample consists of area units of relatively equal size (number of households) , these units have been used as primary sampling units (PSUs). Sample Design: The sample is a two-stage stratified cluster random sample.

Stratification: Four levels of stratification were made: 1. Stratification by Governorates. 2. Stratification by type of locality which comprises: (a) Urban (b) Rural (c) Refugee Camps 3. Stratification by classifying localities, excluding governorate centers, into three strata based on the ownership of households of durable goods within these localities. 4. Stratification by size of locality (number of households).

The sample size was about 7,770 households in the 56th round and 7,818 households in the 57th round, and 7,819 households in the 58th round and 7,772 households in the 59th round. The total number of the households was about 31,179 households. The number of completed questionnaires was about 27,514 questionnaires and this was considered appropriate to provide estimations on main labour force characteristics in the Palestinian Territory. The sample size in 1st quarter, 2010 consisted of 7,770 households, which included 29,999 persons aged 10 years and over (including 24,395 aged 15 years and over). In the 2nd quarter, the sample consisted of 7,818 households, which included 29,483 persons aged 10 years and over (including 24,118 aged 15 years and over). In the 3rd quarter, the sample consisted of 7,819 households, which included 28,479 persons aged 10 years and over (including 23,260 aged 15 years and over). In the 4th quarter the sample consisted of 7,772 households; which included 28,478 persons aged 10 years and over (including 23,288 aged 15 years and over).

Sample Rotation: Each round of the Labor Force Survey covers all the 481 master sample areas. Basically, the areas remain fixed over time, but households in 50% of the EAs are replaced each round. The same household remains in the sample over 2 consecutive rounds, rests for the next two rounds and represented again in the sample for another and last two consecutive rounds before it is dropped from the sample. A 50 % overlap is then achieved between both consecutive rounds and between consecutive years (making the sample efficient for monitoring purposes). In earlier applications of the LFS (rounds 1 to 11); the rotation pattern used was different; requiring a household to remain in the sample for six consecutive rounds, then dropped. The objective of such a pattern was to increase the overlap between consecutive rounds. The new rotation pattern was introduced to reduce the burden on the households resulting from visiting the same household for six consecutive times.

Mode of data collection

Face-to-face [f2f]

Research instrument

The LFS questionnaire consists of four main sections: 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. 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. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc. 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.

Cleaning operations

Data editing took place at a number of stages through the processing including: 1. Office editing and coding 2. During data entry 3. Structure checking and completeness 4. Structural checking of SPSS data files

Response rate

The overall response rate for the survey was 86.5%

Sampling error estimates

Detailed information on the sampling Error is available in the Survey Report.

Data appraisal

Detailed information on the data appraisal is available in the Survey Report

State of Palestine (West Bank and Gaza) Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 1.520 % in 2016. This records a decrease from the previous number of 1.740 % for 2010. State of Palestine (West Bank and Gaza) Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 1.740 % from Dec 2004 (Median) to 2016, with 7 observations. The data reached an all-time high of 2.680 % in 2006 and a record low of 1.310 % in 2005. State of Palestine (West Bank and Gaza) Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

State of Palestine (West Bank and Gaza) Proportion of Population Pushed Below the $3.65: Poverty Line by Out-of-Pocket Health Care Expenditure: 2017 PPP: % data was reported at 0.620 % in 2016. This records an increase from the previous number of 0.450 % for 2010. State of Palestine (West Bank and Gaza) Proportion of Population Pushed Below the $3.65: Poverty Line by Out-of-Pocket Health Care Expenditure: 2017 PPP: % data is updated yearly, averaging 0.360 % from Dec 2004 (Median) to 2016, with 7 observations. The data reached an all-time high of 0.870 % in 2007 and a record low of 0.190 % in 2004. State of Palestine (West Bank and Gaza) Proportion of Population Pushed Below the $3.65: Poverty Line by Out-of-Pocket Health Care Expenditure: 2017 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the $3.65 poverty line, but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

Abstract

The Socio-economic Monitoring of the Palestinian Households Survey 2010 was planned to fill data gaps in the Palestinian Territory. The survey was conducted in cooperation with Food and Agriculture Organization (FAO) and World Food Program (WFP). It covers socio- economic indicators that are used in formulating a comprehensive database utilized in the Palestinian Territory.

This survey provides mainly the following indicators: • Palestinians Socio-economic characteristics
• Household expenditure and income • Coping strategies used by the households • General overview on the Palestinian households during last six months • Households basic needs • Received assistance, assessment of received assistance

Geographic coverage

Palestinian Territory

Analysis unit

Household

Universe

The target population consisted of all Palestinian households that usually reside in the Palestinian Territory

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame consisted of a master sample of enumeration areas (EAs) selected from the Population Housing and Establishment Census 2007 The master sample consists of area units of relatively equal size (number of households, about 150 housing units), and these units has been used as primary sampling units (PSUs).

Sample Size The sample size was 7,500 households, located in 300 enumeration areas in the Palestinian Territory, distributed by 5000 households in West Bank and 2500 in Gaza Strip. The design considered dissemination on governorate level and the localities affected by the annexation wall.

Sample design

The sample is two stage stratified cluster sample with two stages: First stage: selection of a stratified systematic random sample of 300 Enumeration Areas (200 in west Bank, 100 in Gaza strip). Second stage: selection of a systematic random sample of 25 households from each enumeration area selected in the first stage. And then to choose a legible person aged 18 years and above to be the respondent of the questionnaire questions.

Note: in Jerusalem Governorate (J1), 20 enumeration areas were selected; then in the second phase, a group of 25 households from each enumeration area were chosen using census-2007 method of delineation and enumeration. This method was adopted to ensure household response is to the maximum to comply with the percentage of non-response as set in the sample design.

Mode of data collection

Face-to-face [f2f]

Research instrument

A special questionnaire was designed in accordance with UN standards and recommendations, the questionnaire include the identification data in addition to the quality control measures, it covers the following fields: Part one: Social data which include name, relation with head of household, sex, age, refugee status, place of residence, reasons of changing place of residence if happened, health insurance, difficulties, education, labor and marital status. Part two: that covers the housing unit data. Part three: that covers the agricultural data. Part four: that covers the data on assistants. Part five: that covers the data on coping strategies> Part six: that covers the income data. Part seven: that covers the data on expenditure and consumption. Part eight: that covers the nutrition and lack of food. Part nine: that covers the data on freedom of movement.

Cleaning operations

Both data entry and tabulation were completed by using the ACCESS and SPSS software programs. Data entry was organized into two files, corresponding to the main parts of the questionnaire. Data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks: logical check, range checks, consistency checks and cross-validation.

Response rate

Response rate was 92%

Sampling error estimates

Statistical Errors: Sampling rather than comprehensive enumeration has been used to collect data in this survey. Therefore it is liable to two types of errors affecting the quality of survey data, sampling (statistical errors) and non-sampling errors (non-statistical errors). Statistical errors mean the errors resulting from sample designing and this is computed simply. Variance and effect of sample design has been computed for the Palestinian Territory, the West Bank and Gaza Strip.

Non-Statistical Errors: Non-statistical errors, on the other hand, could not be determined easily, due to the diversity of sources from which they may arise, e.g., the interviewer, respondent, editor, coder, and data entry operator.