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 3.5 children per woman as of 2022.

Chart and table of Palestine population from 1950 to 2025. United Nations projections are also included through the year 2100.

State of Palestine (West Bank and Gaza) Population Growth Rate: West Bank data was reported at 2.200 % in 2018. This stayed constant from the previous number of 2.200 % for 2017. State of Palestine (West Bank and Gaza) Population Growth Rate: West Bank data is updated yearly, averaging 2.600 % from Dec 1997 (Median) to 2018, with 13 observations. The data reached an all-time high of 3.600 % in 1997 and a record low of 2.200 % in 2018. State of Palestine (West Bank and Gaza) Population Growth Rate: West Bank 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.

Jews were the dominant religious group in the Israel-Palestine region at the beginning of the first millennia CE, and are the dominant religious group there today, however, there was a period of almost 2,000 years where most of the world's Jews were displaced from their spiritual homeland. Antiquity to the 20th century Jewish hegemony in the region began changing after a series of revolts against Roman rule led to mass expulsions and emigration. Roman control saw severe persecution of Jewish and Christian populations, but this changed when the Byzantine Empire adopted Christianity as its official religion in the 4th century. Christianity then dominated until the 7th century, when the Rashidun Caliphate (the first to succeed Muhammad) took control of the Levant. Control of region split between Christians and Muslims intermittently between the 11th and 13th centuries during the Crusades, although the population remained overwhelmingly Muslim. Zionism until today Through the Paris Peace Conference, the British took control of Palestine in 1920. The Jewish population began growing through the Zionist Movement after the 1880s, which sought to establish a Jewish state in Palestine. Rising anti-Semitism in Europe accelerated this in the interwar period, and in the aftermath of the Holocaust, many European Jews chose to leave the continent. The United Nations tried facilitating the foundation of separate Jewish and Arab states, yet neither side was willing to concede territory, leading to a civil war and a joint invasion from seven Arab states. Yet the Jews maintained control of their territory and took large parts of the proposed Arab territory, forming the Jewish-majority state of Israel in 1948, and acheiving a ceasefire the following year. Over 750,000 Palestinians were displaced as a result of this conflict, while most Jews from the Arab eventually fled to Israel. Since this time, Israel has become one of the richest and advanced countries in the world, however, Palestine has been under Israeli military occupation since the 1960s and there are large disparities in living standards between the two regions.

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 main objective of collecting data on the Palestinian Labour Force Survey 1998 (Third Quarter) including components of employment, unemployment and underemployment, is to provide basic information on the relative size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in employment. These data supported with information on other aspects of the economy provide a basis for the evaluation and analysis of macro-economic policies.

Geographic coverage

National

Analysis unit

• Household
• Individual aged 10 years and above

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: In the absence of a population census since 1967, the major task, with regard to constructing a master sample, was developing a sampling 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 is a two-stage stratified cluster random sample.

Target Population: All Palestinians aged 15 years and above living in the Palestinian Territories, excluding nomads and persons living in institutions such as prisons or shelters.

Stratification: Four levels of stratification were made: 1. Stratification by District. 2. Stratification by place of residence which comprises: (a) Municipalities; (b) Villages; and (c) Refugee Camps 3. Stratification by size of locality. 4. Stratification by cell identification by locality.

Sampling Unit: First stage sampling units are the area units (Cells) in the master sample. The second stage sampling units are households.

Sample Size: The sample size in the tenth round/ third quarter (July 1998 - September 1998) was about 7,632 (about 23,305 persons of age work).

Target cluster size: The next important issue in sample design is the target cluster size or "sample-take," the number of households to be selected per PSU on the average. In this survey persons of working age had been selected from 480 master sample areas. Therefore, the sample take was around 16 households.

Sample Rotation: Each round covered all the 480 master sample areas (except for the first round which covers 5/6 of these, i.e. 480 areas with proportionately increased sample-take per cluster so as to keep the same sample size). Basically, the areas remained fixed over time, but within each area a proportion of the households was replaced each round. During the first phase when the survey was conducted at 6- monthly interval or quarterly surveys were introduced, the same households remain in the sample over 6 consecutive rounds. A high overlap of 5¤6 is then achieved between consecutive rounds (making the sample efficient for monitoring trends), reducing linearly to zero overlap after 6 rounds. In each round, 1 6 (i.e. 80) clusters are listed - i.e. 320 over the whole year as before.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts: 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

1. 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).

2. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level.etc.

3. 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.

Response rate

• Response rate in the third quarter was 87.6%

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2012 (LFS). The survey rounds covered a total sample of about 30,887 households, and the number of completed questionaire is 26,898.

The main objective of collecting data on the labour force and its components, including employment, unemployment and underemployment, is to provide basic information on the size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in the employment situation. These data, supported with information on other aspects of the economy, provide a basis for the evaluation and analysis of macro-economic policies.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.

Geographic coverage

Covering a representative sample on the region level (West Bank, Gaza Strip), the locality type (urban, rural, camp) and the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The methodology was designed according to the context of the survey, international standards, data processing requirements and comparability of outputs with other related surveys.

---> Target Population: It consists of all individuals aged 10 years and older normally residing in their households in Palestine during 2012.

---> Sampling Frame: The sampling frame consists of the master sample, which was updated in 2011: each enumeration area consists of buildings and housing units with an average of about 124 households. The master sample consists of 596 enumeration areas; we used 498 enumeration areas as a framework for the labor force survey sample in 2012 and these units were used as primary sampling units (PSUs).

---> Sampling Size: The estimated sample size in the first quarter was 7,775 households, in the second quarter it was 7,713 households, in the third quarter it was 7,695 households and in the fourth quarter it was 7,704 households.

---> Sample Design The sample is two stage stratified cluster sample with two stages : First stage: we select a systematic random sample of 498 enumeration areas for the whole round ,and we excluded the enumeration areas which its sizes less than 40 households. Second stage: we select a systematic random sample of 16 households from each enumeration area selected in the first stage, se we select a systematic random of 16 households of the enumeration areas which its size is 80 household and over and the enumeration areas which its size is less than 80 households we select systematic random of 8 households.

---> Sample strata: The population was divided by: 1- Governorate (16 governorate) 2- Type of Locality (urban, rural, refugee camps).

---> Sample Rotation: Each round of the Labor Force Survey covers all of the 498 master sample enumeration areas. Basically, the areas remain fixed over time, but households in 50% of the EAs were replaced in each round. The same households remain in the sample for two consecutive rounds, left for the next two rounds, then selected for the sample for another two consecutive rounds before being dropped from the sample. An overlap of 50% is then achieved between both consecutive rounds and between consecutive years (making the sample efficient for monitoring purposes).

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts:

---> 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

---> 2. Quality Control: This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data.

---> 3. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc.

---> 4. Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.

Cleaning operations

---> Raw Data The data processing stage consisted of the following operations: 1. Editing and coding before data entry: All questionnaires were edited and coded in the office using the same instructions adopted for editing in the field. 2. Data entry: At this stage, data was entered into the computer using a data entry template designed in Access. The data entry program was prepared to satisfy a number of requirements such as: - Duplication of the questionnaires on the computer screen. - Logical and consistency check of data entered. - Possibility for internal editing of question answers. - Maintaining a minimum of digital data entry and fieldwork errors. - User friendly handling. Possibility of transferring data into another format to be used and analyzed using other statistical analytic systems such as SPSS.

---> Harmonized Data - The SPSS package is used to clean and harmonize the datasets. - The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency. - All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization. - A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables. - A post-harmonization cleaning process is then conducted on the data. - Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

The survey sample consists of 30,887 households, of which 26,898 households completed the interview: 17,594 households from the West Bank and 9,304 households in Gaza Strip. Weights were modified to account for the non-response rate. The response rate in the West Bank was 90.2 %, while in the Gaza Strip it was 94.7%.

Sampling error estimates

---> Sampling Errors Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators: the variance table is attached with the final report. There is no problem in disseminating results at national or governorate level for the West Bank and Gaza Strip.

---> Non-Sampling Errors Non-statistical errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey, as well as practical and theoretical training during the training course. Also data entry staff were trained on the data entry program that was examined before starting the data entry process. To stay in contact with progress of fieldwork activities and to limit obstacles, there was continuous contact with the fieldwork team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by fieldworkers were discussed to clarify any issues. Non-sampling errors can occur at the various stages of survey implementation whether in data collection or in data processing. They are generally difficult to be evaluated statistically.

They cover a wide range of errors, including errors resulting from non-response, sampling frame coverage, coding and classification, data processing, and survey response (both respondent and interviewer-related). The use of effective training and supervision and the careful design of questions have direct bearing on limiting the magnitude of non-sampling errors, and hence enhancing the quality of the resulting data. The implementation of the survey encountered non-response where the case ( household was not present at home ) during the fieldwork visit

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 Palestinian Central Bureau of Statistics implemented the Survey of Smoking and Tobacco Consumption, 2021 represents the first specialized survey in Palestine on smoking, the survey based on the Global Adult Tobacco Survey (GATS). As a household survey of individuals 18 years and above. The topics of the Smoking and Tobacco Consumption Survey cover a wide range of indicators as the prevalence of smoking in Palestine, the basic characteristics of the respondents, tobacco use (smokers and non-smokers), electronic cigarettes use, cessation, second-hand smoke, economics, Media, and knowledge, attitudes and perceptions towards tobacco use, in the Palestinian society

Geographic coverage

The survey is nationally representative and covers three levels: the first is at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and the center of the main cities (Nablus, Ramallah, Hebron, Gaza).

Analysis unit

All individuals (18 years and above) and living with their households normally in Palestine.

Universe

The survey questionnaire comprised the following parts:

Questionnaire Cover: Includes the identification data and quality control. Part one: Data of households' members and social data. Part two: Includes data related to individuals (18 years and above), and the section covers identification data and characteristics of individuals (18 years and above),

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Size The estimated sample size is 9,232 households in the West Bank and Gaza Strip.

Sample Design The sample is three stage stratified cluster (pps) sample: First Stage: Selection of a stratified sample of 577 EA with (pps) method. Second Stage: Selection of a systematic random area sample of 16 households from each enumeration area selected in the first stage.

Third Stage: We selected one person in the household of the (18+) age group in a random method using Kish tables, so that the sex of the person chosen by the serial questionnaire number in the sample. If it is an odd number, we select a male household member and if it is an even number, we select a female household member.

Sample Strata The population was divided into the following strata:

1. Governorate (17 Governorates, where Jerusalem was considered as two statistical areas).
2. Locality type (urban, rural, refugee camp).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire comprised the following parts:

· Questionnaire Cover: Includes the identification data and quality control. · Part one: Data of households' members and social data. · Part two: Includes data related to individuals (18 years and above), and the section covers identification data and characteristics of individuals (18 years and above), in addition to: - Tobacco consumption. - Cessation. - Smokeless tobacco consumption. - Exposure to secondhand smoking. - The use of heated tobacco products. - The use of electronic cigarettes. - Water pipe smoking. - Anti-smoking policies. - Expenditure on smoking.

Cleaning operations

1. Concurrently with the data collection process, a weekly check of the data entered was carried out centrally and returned to the field for modification during the data collection phase and follow up. The work was carried out thorough examination of the questions and variables to ensure that all required items are included, and the check of shifts, stops and range was done too.
2. Data processing was conducted after the fieldwork stage, where it was limited to conducting the final inspection and cleaning of the survey databases. Data cleaning and editing stage focused on: · Editing skips and values allowed. · Checking the consistency between different the questions of questionnaire based on logical relationships. · Checking on the basis of relations between certain questions so that a list of non-identical cases was extracted, and reviewed toward identifying the source of the error case by case, where such errors were immediately modified and corrected based on the source of the error with the documentation process for the checks occurred on the questionnaire.
3. The SPSS program was used to extract and modify errors and discrepancies, to prepare clean and accurate data ready for scheduling and publishing.

Response rate

The survey sample consists of about 9,232 households of which 7,763 households completed the interview; whereas 5,049 households from the West Bank and 2,714 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 85.4% while it reached 94.2% in Gaza Strip.

Sampling error estimates

The data accuracy test includes multiple aspects of the survey, the most notably is sampling errors and non-sampling errors which refers to the staff and survey tools, as well as survey response rates and their most important impact on estimates. This section includes the following:

• Sampling Errors Data of this survey are affected by sampling errors due to the use of a sample and not a complete enumeration for the target population. Therefore, certain differences are expected to appear in comparison with the real values obtained through censuses. Variance was calculated for the most important indicators. There is no problem at the level of dissemination of the mentioned estmiates at the national level and the level of governorates for both the West Bank and Gaza Strip.

• Non-Sampling Errors Non-sampling errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, through practical and theoretical training during the training course. Also, data entry employees were trained on the entry program that was examined before starting the data entry process. Continuous contacts with the fieldwork team were maintained through regular visits to the field and regular meetings during the different field visits. Problems faced by fieldworkers were discussed to clarify issues and provide relevant instructions.

The implementation of the survey encountered non-response, where the case (household was not present at home) during the fieldwork visit become the high percentage of the non-response cases. The total non-response rate reached 11.7% which is very low once compared to the household surveys conducted by PCBS. The refusal rate reached 4.1% which is relatively low percentage compared to the household surveys conducted by PCBS, and the reason behind that is that the questionnaire was short and the experience of fieldworkers.

Abstract

This survey was conducted in the West Bank and Gaza between June and September 2013 as part of the Enterprise Survey project, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country's business environment. The remaining questions assess the survey respondents' opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for West Bank and Gaza was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into one collective manufacturing industry, and two services industries (retail and other services).

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not common practice, apart from the construction and agriculture sectors which are not included in the survey.

Regional stratification was defined in two regions: the West Bank, Gaza.

The sample frame used for the survey in the West Bank and Gaza was from the the Palestinian Central Bureau of Statistics Enterprise Census 2012 database.

The enumerated establishments were then used as the frame for the selection of a sample with the aim of obtaining interviews at 360 establishments with five or more employees. Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 6.76% (40 out of 592 contacted establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Questionnaire; - Services Questionnaire.

All variables are named using, first, the letter of each section and, second, the number of the variable within the section, i.e. a1 denotes section A, question 1. Variable names proceeded by a prefix "MNA" indicate questions specific to the Middle East and North Africa region, therefore, they may not be found in the implementation of the rollout in other countries. All other suffixed variables are global and are present in all economy surveys over the world. All variables are numeric with the exception of those variables with an "x" at the end of their names. The suffix "x" denotes that the variable is alpha-numeric.

There are two establishment identifiers, idstd and id. The first is a global unique identifier. The second is a country unique identifier. The variables a2 (sampling region), a6a (sampling establishment's size), and a4a (sampling sector) contain the establishment's classification into the strata chosen for each country using information from the sample frame. The strata were defined according to the guidelines described above. Variable a4a is coded using ISIC Rev 3.1 codes for the chosen industries for stratification. These codes include most manufacturing industries (15 to 37), retail (52), and (45, 50, 51, 55, 60-64, 72) for other services.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

The number of contacted establishments per realized interview was 0.73. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.14.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond as a different option from don’t know. b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

Abstract

The main objective of collecting data on the Palestinian labour force 1995 including components of employment, unemployment and underemployment, is to provide basic information on the relative size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in employment. These data supported with information on other aspects of the economy provide a basis for the evaluation and analysis of macro-economic policies.

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 In the absence of a population census since 1967, the major task, with regard to constructing a 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 Unit First stage sampling units are the erea units in the master sample. the second stage sampling units are households.

Sample Size The sample size is about 7,625 households allowing for non-reponse and related losses. This amounts to a sample of around 26,000 persons of working age for the survey round. The sample size is large enough to provide estimates of the main characteristics of labour force at the national level and for major domains or sub-populations, and also to monitor significant changes in those characteristics (especially after the survey frequency is increased to quaterly rounds).

Stratification Four levels of stratification have been made: - Stratification by District. - Stratification by type of (Locality) which comprises: (a) Municipalities (b)Villages (c)Refugee Camps

• Stratification by locality size.
• Stratification by cell identification in that order.

Sampling deviation

Sample Design The target population: consist of all Palestinian individuals aged 15 years and above living in West Bank and Gaza Strip, excluding nomads and persons living in institutions such as prisons, shelters.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey tool was designed taking into account the Palestinian conditions, international standards, data processing requirements and the comparability of outputs with other related surveys conducted in the West Bank and Gaza Strip. The questionnaire included four parts:

• The first part for recoding necessary elements for survey management and controls;
• The second part for identifying the sample household;
• The third part for recoding the household roster and the demographic characteristics for household members
• The last part for recoding the labour force characteristics for household members in the working age.

Cleaning operations

Editing after data entry: In this stage, all questionnaires were edited after data entry in order to minimize errors related data entry.

Data were entered to the computer using a data entry template written in BLAISE. Data entry was organized in one files, corresponding to the main parts of the questionnaire. A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks: logical check, range checks, consisting checks and cross-validation. Complete manual inspection of results after data entry was performed, and questionnaires containing field-related errors were sent back to the field for correction.

Response rate

" The overall response rate for the survey was 98.3%

Sampling error estimates

Since the data reported here are based on a sample suvrey and not on coplete enumeration, they are subject to two main types of errors: sampling errors and nonsampling errors.

Sampling errors are random outcomes of the sample design, and are, therefore, easily measurable. A description of the estimated variances and the effects of the sample design on sampling errors are provided in the report and Table A. In general, the assessments is that the sample size and sample design provide reliable estimates of the main labour force indicators.

Data appraisal

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

Abstract

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

Geographic coverage

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

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

In the absence of a population census since 1967, the major task, with regard to constructing a 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

Stratification Four levels of stratification have been made: Stratification by District. Stratification by place of residence which comprises: (a) Municipalities (b) Villages (c) Refugee Camps
Stratification by locality size. Stratification by cell identification in that order.

Sample Size The sample size is about 4,893 households allowing for non-response and related losses.

Target cluster size The next important issue in sample design is the target cluster size or “sample-take,” the number of households to be selected per PSU on the average. In this survey, the sample take is around 10 households.

Self-weighting design:

At the first stage, clusters or “cells” have been selected with PPS probability proportional to estimated measure of size (Mi) for unit (I):

Where the summation covers all clusters in the population; a-300 is the total number of selected clusters. It is highly desirable for the PECS to have a constant overall sampling rate (f), i.e. to have a self- weighting sample. This requires the second stage probability for the selection of households and persons within any sample cluster i to be as follows:

Where b is a constant (independent of i) to be determined to obtain the required sample size, n =3,000 households. Since the measure of size are likely to differ from the actual number of households listed in any cluster i, the actual number of households selected with the above shall vary from one cluster to another and are presented as:

Adding all clusters in the sample results in the required constant b, to achieve the target sample size n as:

Hence to control the overall sample size, b is determined after completing the listing in all sample areas.

The above procedure allows for variation in sample sizes bi at the level of individual clusters, in order to provide a self-weighting sample. Households within each sample cluster shall be selected systematically from the lists prepared for that purpose, using the sampling interval,

Where:

A  Number of cells in the sample (equals 480) 
Number of housing units in cell I    
Number of listed of households in cell i    
N  Proposed sample size (n= 4,893 HHs) 
B  Average sample take 
Sample take in cell I    
F  Sample rate 
First-stage sampling rate    
Second-stage sampling rate   

Which is fixed for each cluster but varies between clusters depending on the measure of size () with which the area was selected at the first stage.

The sample-take must be allowed to vary depending on the actual number of households found after listing. However, provision must be made to avoid extreme variation in cluster sample size. This could be done by using the above procedure to compute the ratio for each cluster in the sample. If this ratio lies outside the range say 0.5 - 4.0, adjust , i.e. the interval to be applied for the selection of households in the cluster, so as to keep the ratio within the above range.

Sample Rotation The total (480) cells have been divided into (24) groups (subsided sample), each one is constituted from (20) cells. The total (480) cells have been used around the year by using a monthly sample constituted from two minor ones (40 cells). The survey includes independent cells and not cross section ones, each of these is formed from (400) households for each month (round).

(Replication)

L K J I H G F E D C B A Month
× 1
× 2
× 3
× 4
× 5
× 6
× 7
× 8
× 9
× 10
× 11
× 12

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 house, 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.

Assistance and poverty: includes questions about household conditions and assistances that got through the the past month.

Second section: The second section of the questionnaire includes a list of 55 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 667 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 50-55 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, except the cars group the data of which was collected for three previous years. These data was abotained from the recording book which is covered a period of month for each household.

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

Selection of (4,893) households representing the West Bank and Gaza Strip, (3,490) households in the West Bank and (1,403) households in Gaza Strip.

After completing the last visit to the households during the survey period, The results of questionnaires were as follows:

Region Number of Questionnaires Number of incomplete Questionnaires Total Uninhabited Completed Refused Travel Movement Other
West Bank 3,490 68 3,213 120 65 7 17
Gaza Strip 1,403 19 1,335 22 21 2 4
Palestinian Territory 4,893 87 4,548 142 86 9 21

Excluding the uninhabited housing units, the sample of survey become (4,806) households, (3,422) households in the West Bank, And (1,384) households in Gaza Strip. (4,548) households completed the questionnaire: (3,213) households in the West Bank and (1,335) households in Gaza Strip. Therefore the percentage of non response rate was as indicated below:

Gaza Strip (%) West Bank (%) Palestinian Territories (%) Result of Interview
3.7 6.5 5.7 Non response
1.7 3.8 3.1 Refused 1.7 2.2 2.1 Not complete*
0.3 0.5 0.5 Other
*Not complete include movement and travel of Household.

response rate is 88.6% in palestinian territories (87.0% in west bank, 92.6% in gaza strip)

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.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2008 (LFS). The survey rounds covered a total sample of about 30,180 households, and the number of completed questionaire is 23,884, which amounts to a sample of around 107,361 individuals aged 10 years and over, including 86,076 individuals in the working-age population 15 years and above.

The importance of this survey lies in that it 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.

The survey main objectives are: - To estimate the labor force and its percentage to the population. - To estimate the number of employed individuals. - To analyze labour force according to gender, employment status, educational level , occupation and economic activity. - To provide information about the main changes in the labour market structure and its socio economic characteristics. - To estimate the numbers of unemployed individuals and analyze their general characteristics. - To estimate the rate of working hours and wages for employed individuals in addition to analyze of other characteristics.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.

Geographic coverage

Covering a representative sample on the region level (West Bank, Gaza Strip), the locality type (urban, rural, camp) and the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The methodology was designed according to the context of the survey, international standards, data processing requirements and comparability of outputs with other related surveys.

Target Population:

All Palestinians aged 10 years or older living in the Palestinian Territory, excluding those 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 1997. 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, and (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).

Sample Size

The sample size in the first round consisted of 7,552 households, which amounts to a sample of around 21,116 persons aged 15 years and over. In the second round the sample consisted of 7,552 households, which amounts to a sample of around 20,314 persons aged 15 years and over, in the third round the sample consisted of 7,546 households, which amounts to a sample of around 23,465 persons aged 15 years and over. In the fourth round the sample consisted of 7,546 households; which amounts to a sample of around 21,181 persons aged 15 years and over. The sample size allowed for non-response and related losses. In addition, the average number of households selected in each cell was 16.

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: 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

1. 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.

2. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc.

4.Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.

Cleaning operations

Raw Data

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

Harmonized Data

• The SPSS package is used to clean and harmonize the datasets.
• The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency.
• All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
• A post-harmonization cleaning process is then conducted on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

The overall response rate for the survey was 84.2

More information on the distribution of response rates by different survey rounds is available in Page 10 of the data user guide provided among the disseminated survey materials under a file named "Palestine 2008- Data User Guide (English).pdf".

Sampling error estimates

Since the data reported here are based on a sample survey and not on a complete enumeration, they are subjected to sampling errors as well as non-sampling errors. Sampling errors are random outcomes of the sample design, and are, therefore, in principle measurable by the statistical concept of standard error. Data of this survey affected by statistical errors due to use the sample, Therefore, the emergence of certain differences from the real values expect obtained through censuses. It had been calculated variation of the most important indicators exists and the facility with the report and the dissemination levels of the data were particularized at the regional level in Governorate in the West Bank and Gaza Strip.

Data appraisal

Data entry staff was trained on the entry program that was examined before starting the data entry process. To have a fair idea about the situation and to limit obstacles, there was continuous contact with the fieldwork team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by fieldworkers were discussed to clarify any issues.

Non-sampling errors can occur at the various stages of survey implementation whether in data collection or in data processing. They are generally difficult to be evaluated statistically. They cover a wide range of errors, including errors resulting from non-response, sampling frame coverage, coding and classification, data processing, and survey response (both respondent and interviewer-related). The use of effective training and supervision and the careful design of

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2021 (LFS). The survey rounds covered a total sample of about 25,179 households (about 6,300 households per quarter).

The main objective of collecting data on the labour force and its components, including employment, unemployment and underemployment, is to provide basic information on the size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in the employment situation. These data, supported with information on other aspects of the economy, provide a basis for the evaluation and analysis of macro-economic policies.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.

Geographic coverage

Covering a representative sample on the region level (West Bank, Gaza Strip), the locality type (urban, rural, camp) and the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The methodology was designed according to the context of the survey, international standards, data processing requirements and comparability of outputs with other related surveys.

---> Target Population: It consists of all individuals aged 10 years and Above and there are staying normally with their households in the state of Palestine during 2020.

---> Sampling Frame: The sampling frame consists of a comprehensive sample selected from the Population, Housing and Establishments Census 2017: This comprehensive sample consists of geographical areas with an average of 150 households, and these are considered as enumeration areas used in the census and these units were used as primary sampling units (PSUs).

---> Sampling Size: The estimated sample size is 8,040 households in each quarter of 2021.

---> Sample Design The sample is two stage stratified cluster sample with two stages : First stage: we select a systematic random sample of 536 enumeration areas for the whole round. Second stage: we select a systematic random sample of 15 households from each enumeration area selected in the first stage.

---> Sample strata: The population was divided by: 1- Governorate (17 governorates, where Jerusalem was considered as two statistical areas) 2- Type of Locality (urban, rural, refugee camps).

---> Sample Rotation: Each round of the Labor Force Survey covers all of the 536 master sample enumeration areas. Basically, the areas remain fixed over time, but households in 50% of the EAs were replaced in each round. The same households remain in the sample for two consecutive rounds, left for the next two rounds, then selected for the sample for another two consecutive rounds before being dropped from the sample. An overlap of 50% is then achieved between both consecutive rounds and between consecutive years (making the sample efficient for monitoring purposes).

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts:

---> 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

---> 2. Quality Control: This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data.

---> 3. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc.

---> 4. Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.

Cleaning operations

---> Raw Data PCBS started collecting data since 1st quarter 2020 using the hand held devices in Palestine excluding Jerusalem in side boarders (J1) and Gaza Strip, the program used in HHD called Sql Server and Microsoft. Net which was developed by General Directorate of Information Systems. From the beginning of March 2020, with the spread of the COVID-19 pandemic and the home quarantine imposed by the government, the personal (face to face) interview was replaced by the phone interview for households who had phone numbers from previous rounds, and for those households that did not have phone numbers, they were referred to and interviewed in person (face to face interview). Using HHD reduced the data processing stages, the fieldworkers collect data and sending data directly to server then the project manager can withdrawal the data at any time he needs. In order to work in parallel with Gaza Strip and Jerusalem in side boarders (J1), an office program was developed using the same techniques by using the same database for the HHD.

---> Harmonized Data - The SPSS package is used to clean and harmonize the datasets. - The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency. - All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization. - A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables. - A post-harmonization cleaning process is then conducted on the data. - Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

The survey sample consists of about 32,160 households of which 25,179 households completed the interview; whereas 16,355 households from the West Bank and 8,824 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 79.8% while in the Gaza Strip it reached 90.5%.

Sampling error estimates

---> Sampling Errors Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators: the variance table is attached with the final report. There is no problem in disseminating results at national or governorate level for the West Bank and Gaza Strip.

---> Non-Sampling Errors Non-statistical errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey, as well as practical and theoretical training during the training course. Also data entry staff were trained on the data entry program that was examined before starting the data entry process. To stay in contact with progress of fieldwork activities and to limit obstacles, there was continuous contact with the fieldwork team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by fieldworkers were discussed to clarify any issues. Non-sampling errors can occur at the various stages of survey implementation whether in data collection or in data processing. They are generally difficult to be evaluated statistically.

They cover a wide range of errors, including errors resulting from non-response, sampling frame coverage, coding and classification, data processing, and survey response (both respondent and interviewer-related). The use of effective training and supervision and the careful design of questions have direct bearing on limiting the magnitude of non-sampling errors, and hence enhancing the quality of the resulting data. The implementation of the survey encountered non-response where the case ( household was not present at home ) during the fieldwork visit and the case ( housing unit is vacant) become the high percentage of the non response cases. The total non-response rate reached 16.7% which is very low once compared to the

State of Palestine (West Bank and Gaza) PS: Prevalence of Underweight: Weight for Age: % of Children Under 5: Male data was reported at 4.000 % in 2010. This records an increase from the previous number of 2.200 % for 2007. State of Palestine (West Bank and Gaza) PS: Prevalence of Underweight: Weight for Age: % of Children Under 5: Male data is updated yearly, averaging 3.100 % from Dec 2007 (Median) to 2010, with 2 observations. The data reached an all-time high of 4.000 % in 2010 and a record low of 2.200 % in 2007. State of Palestine (West Bank and Gaza) PS: Prevalence of Underweight: Weight 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 underweight, male, is the percentage of boys under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. 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 main objective of collecting data on the Palestinian Labour Force Survey 1999 (Fourth Quarter) including components of employment, unemployment and underemployment, is to provide basic information on the relative size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in employment. These data supported with information on other aspects of the economy provide a basis for the evaluation and analysis of macro-economic policies.

Geographic coverage

National

Analysis unit

• Household
• Individual aged 10 years and above

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The sampling frame consisted of a master sample of enumeration areas (EAs) selected from the population housing and establishment census 1997, 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.

Target Population: All Palestinians aged 15 years and above living in the Palestinian Territories, excluding persons living in institutions such as prisons or shelters.

Stratification: Four levels of stratification: 1. Stratification by Governorates. 2. Stratification by place of residence which comprises: (a) Urban, (b) Rural, (c) Refugee Camps

1. Stratification by classifying localities, excluding governorate capitals, into three strata based on the ownership of households within these localities of durable goods.
2. Stratification by size of locality (number of households).

Sampling Unit: First stage sampling units are the area units (EAs) in the master sample. The second stage sampling units are households.

Sample Size: The sample size in the fourth quarter/ round 15 (October 1999 - December 1999) was 7,559 (29,111 persons of working age). The sample is distributed over 481 enumeration areas.

Target cluster size: The next important issue in sample design is the target cluster size or "sample-take," the number of households to be selected per PSU on the average. In this survey households have been selected from 481 master sample areas. Therefore, the sample take was around 16 households.

Sample Rotation: Each round of the LFS covered 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 comes back to 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 trends).

In earlier applications of the LFS; 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 is to increase overlap between consecutive rounds, the new rotation pattern is introduced to reduce the burden on the households resulted from visiting the same household for six consecutive times.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts: 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

1. 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).

2. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level.etc.

3. 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.

Response rate

• Response rate in the fourth quarter was 90.5%

Abstract

The Jerusalem Household Social Survey 2005 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, 2005 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 3,300 family, including 2,240 families in the region J1, and 1,060 families in the region 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 1997, was create Sample Frame to Jerusalem (J1) of project data that has been exclusively in 2004. 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 I: 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 123 divided into two regions: 70 the count of Jerusalem (J1), 53 the count of Jerusalem (J2). Phase II: A random sample was withdrawn systematically with size of 20 families from each enumeration area that was selected in the first stage of the Jerusalem J2, and 32 families from each enumeration area that was selected in the first stage of the Jerusalem J1.

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

Phase included a set of data processing Activities and operations that have been made to the Forms to prepare her for the analysis phase, This phase included the following operations: Before the introduction of audit data: at this stage was Check all the forms using the instructions To check to make sure the field of logical data and re- Incomplete, including a second field. Data Entry: The data entry Central to the central headquarters in Al-Bireh, was organized The data entry process using the BLAISE Program Where the form has been programmed through this program. Was marked by the program that was developed in the Device properties and features the following: The possibility of dealing with an exact copy of the form The computer screen. The ability to conduct all tests and possibilities Possible and logical sequence of data in the form. Maintain a minimum of errors Portal Digital data or errors of field work. Ease of use and deal with the software and data (User-Friendly). The possibility of converting the data to the other formula can be Use and analysis of the statistical systems Analysis such as SPSS.

Response rate

during the field work we visit 3,300 family in Jerusalem Governorate, 2,240 in Area J1 and1,060 in Area J2 where the final results of the interviews were as follows: The number of families who were interviewed (2,485) in Jerusalem Governorate, complete questioner 75.3% (1,773) in J1 79.2% (712) in J2 67.2%

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 project from the field visit on a regular basis for all duty stations in order to see the workflow and meet researchers and directing them, especially in the area J1. There was difficulty in reaching the families because of the construction of the wall, especially in the Ram Area and also in the area of Bir Nabala where the switch was a full count area due to additional incompleteness caused by the absence of the families in the region because of the separation wall. It was not easy to follow and adjust the time researchers because of the prevailing security conditions.

Abstract

The central statistical offices in most countries place heavy emphasis on constructing sound databases for all activities within the services sector. PCBS’ Services Statistics Program is part of the Economic Statistics Program, which is part of the larger program for establishing the System of Official Statistics for Palestine. PCBS initiated, in the reference year 1994, the economic surveys series. The series includes, in addition to the services survey, surveys on industry, internal trade construction-contractors, and transport and storage sectors for the purpose of establishing a time series data base of economic activities in line with international recommendations specified in System of National Account (SNA) 93 and in the UN manual for Services Statistics. The sampling frame for the different economic surveys was based on the findings of the 2007 Establishment Census conducted by PCBS.

Objectives: The objective of the survey was to obtain data on:

1. Number of enterprises and persons engaged in services by activity and location.
2. Value of output, intermediate consumption and stocks.
3. Value added components.
4. Payments and transfers.
5. Capital formation.
6. Contribution of the surveyed activities to the GDP and other National Accounts variables.

Target Population

PCBS depends on the International and Industrial Classification of all economic activities, version 3, (ISIC - 3) by the United Nation to classify the economic activities. All enterprises and establishments are classified according to the Establishments Census 2007, which works in agreement with (ISIC - 3).
The services survey covers the following activities: 1. Hotels and Restaurants 2. Real Estate, Renting and Business Activities 3. Education 4. Health and Social Work 5. Other Community, Social and Personal Service Activities

Geographic coverage

West Bank and Gaza Strip

Analysis unit

enterprise constitutes the primary sampling unit (PSU)

Universe

Sample from Services Enterprises (privet sector)

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame

The sample of the Services Survey is a single-stage stratified random - systematic sample in which the enterprise constitutes the primary sampling unit (PSU). Four levels of strata were used to arrive at an efficient representative sample (i.e. economic activity, size of employment and geographical levels. The kind profit or non profit). The sample size amounted to (2,267) enterprises out of the (24,024) enterprises that comprise the survey frame in the Palestinian Territory.

Mode of data collection

Face-to-face [f2f]

Research instrument

They are two forms of the services survey questionnaire 2009 of the Palestinian Territory, the first one is related to household and branches, and the second is related to non-financial companies sector. The questionnaire contains the following main variables: 1. Number of employees in a company and their compensations. 2. The output of the main and second activities. 3. Goods production inputs. 4. Various payments and transfers. 5. Taxes on production and fees. 6. Enterprises assets.

Cleaning operations

Data processing: For insuring quality and consistency of data a set of measures were taken in to account for strengthening accuracy of data as follows: ·Preparing data entry program before data collection for checking readiness of the program for data entry. ·A set of validation rules were applied on the program for checking consistency of data. ·Efficiency of the program was checked through pre-testing in entering few questionnaires, including incorrect information for checking its efficiency, in capturing these information. ·Well trained data keyers were selected and trained for the main data entry. ·Weekly or by weekly data files were received by project management for checking accuracy and consistency, notes of correction are provided for data entry management for correction.

Response rate

· Sample size in 2009 of services sector was 2,290 enterprises (including economic activity change) in the Palestinian Territory: · Non-response cases: 645 · Over coverage cases: 89 · Net sample: 2,290-89= 2,201 · Response rate: 70.7% · Non-response rate: 29.3%

Sampling error estimates

Statistical Errors: The findings of the survey are affected by statistical errors due to using sampling in conducting the survey for the units of the target population, which increases the chances of having variances from the actual values we expect to obtain from the data had we conducted the survey using comprehensive enumeration.. The variance of the key goods in the survey was computed and dissemination was carried out on the level of the Palestinian Territory for reasons related to sample design and computation of the variance of the different indicators.

Non-Statistical Errors These types of errors could appear on one or all the survey stages that include data collection and data entry: Response errors: these types of errors are related to, responders, fieldworkers, and data entry personnel's. And to avoid mistakes and reduce the impact has been a series of actions that would enhance the accuracy of the data through a process of data collection from the field and the data processing.

Abstract

The aim of this survey is to provide data for important indicators on the activity of the domestic and outbound tourism and the pattern of movement of the households that reside in the Palestinian Territory and out of the Palestinian Territory, where the survey data will be an important reference for decision-makers in the development of the tourism sector.

The survey provided data on: - Percentage of the households that traveled for domestic or outbound tourism. - Methods of trip organization and destinations.
- Expenditure during the trip. - Type and level of services provided in the visited areas.

Report Structure

This report consists of five chapters: - The first chapter presents the background of the Domestic and Outbound Tourism Survey 2009 and the objectives of the survey - The second chapter presents the main definitions used in the report. - The third chapter exhibits the main findings of the Domestic and Outbound Tourism Survey. - The fourth chapter discusses the methodology used in this survey. - The fifth chapter presents the quality of the data of the survey.

Geographic coverage

Palestinian Territory.

Analysis unit

Households

Universe

All the households in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The sampling frame consists of all enumeration areas defined in the Population, Housing and Establishment Census 2007. Each enumeration area consists of buildings and housing units comprising an average of 124 households. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.

Sample Size: The estimated sample size is 7,820 households in the West Bank and Gaza Strip.

Target Population: This consists of all Palestinian households who normally reside in the Palestinian Territory (West Bank and Gaza Strip) during 2011.

Sampling Design: The sample for this survey is the same as that of the Labour Force Survey (LFS), which has been conducted quarterly by PCBS since 1995. The Domestic and Outbound Tourism survey is attached with the LFS in the first quarter of 2011.

The sample is a stratified cluster sample with two stages. In the first stage, we selected a systematic random sample of 502 enumeration areas for the whole round. In the second stage, we selected a random area sample of 16 households on average from each enumeration area selected in the first stage.

Sample Strata: The population was divided by: 1- Governorate (16 governorates) 2- Type of Locality (urban, rural, refugee camp)

Mode of data collection

Face-to-face [f2f]

Research instrument

The Domestic and Outbound Tourism Survey questionnaire was designed in accordance with similar country experience and with international standards and recommendations for the most important indicators, taking into account the special situation of the Palestinian Territory and according to previous questionnaries

Cleaning operations

• Duplication of the questionnaires on the computer screen.
• Logical and consistency check of data entered.
• Possibility for internal editing of question answers.
• Maintaining a minimum of digital data entry and fieldwork errors.
• User friendly handling.
• Possibility of transferring data into another format to be used and analyzed using other statistical analytic systems such as SPSS.

Response rate

Response rate 89.3%

Sampling error estimates

Statistical Errors Data of the Domestic and Outbound Tourism Survey was affected by statistical errors due to the use of the sample, therefore, certain differences emerge from the real values obtained through surveys. The variation had been calculated from the most important indicators and their use in the report. The dissemination levels of the data were particularized at the regional level in the West Bank (North, Middle, South) and the Gaza Strip, due to the sample design and the variance calculations for the different indicators.

Non-Statistical Errors Non-statistical errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained in how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey and practical and theoretical training during the training course.

Also data entry staff were trained on the entry program that was examined before starting the data entry process. Continuous contacts with the fieldwork team were maintained through regular visits to the field and regular meetings during the different field visits. Problems faced by fieldworkers were discussed to clarify issues and provide relevant instructions.

Abstract

Time use surveys are crucial instruments in social science research that provide valuable insights into how individuals allocate their time across various activities. These surveys systematically capture and quantify the amount of time people spend on diverse pursuits, such as work, leisure, household chores, and personal care. The data collected through time use surveys offer researchers a comprehensive understanding of societal trends, patterns, and dynamics, shedding light on evolving social structures, economic activities, and cultural practices. By examining how individuals distribute their time, researchers can discern patterns related to gender roles, socioeconomic disparities, and lifestyle changes. Time use surveys also play a pivotal role in informing public policy and program development, guiding decisions on issues ranging from labor market regulations to family support systems. Furthermore, these surveys contribute to the advancement of our understanding of human behavior and well-being, offering a nuanced perspective on the complexities of modern life and its impact on individuals and societies. As such, time use surveys are indispensable tools for scholars, policymakers, and social scientists alike, fostering a deeper comprehension of the intricate interplay between time allocation and various socio-economic factors.

Geographic coverage

Governorate (16 governorates in west bank and Gaza strip) Locality type (urban, rural, camps)

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame of the survey consists of a list of enumeration areas from the population and buildings and establishments census which was implemented by PCBS in 2007 (the enumeration area is a geographical area contains number of households of about 124 households in average).The enumeration areas will be used as primary sampling units in sampling design (PSUs). Sample Size The sample size of the survey is 5,903 Palestinian households. Sampling Design After determining the sample size, the sample type is three-stage stratified cluster sample as following: 1- First stage: selecting systematic sample of 220 clusters (enumeration areas). 2- Second stage: selection sample of 21 responded households from each EA selected in the first stage (we use the area sampling to get this number of responded households). 3- Third stage: selection two individuals male and female (10 years and more) from each household selected in second stage using random kish tables. The population was divided to strata by: 1- Governorate (16 governorates in west bank and Gaza strip) 2- Locality type (urban, rural, camps) Target population of the survey consists of all Palestinian individuals of age group 10 years and over, who are living normally with their households in Palestine in 2012/2013 .

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is the main tool for data collection and was designed on the basis of international surveys specially designed for time use surveys, as well as on the basis of the recommendations of the workshop on time use surveys held in Jordan in 2010. This was organized by ESCWA in cooperation with UNSD to develop a questionnaire for a time use survey and coding manual, along with adding activities related to the Palestinian context compatible with the coding manual of the United Nations of 2006. The questionnaire meets the technical specifications for the field work phase and data processing and analysis requirements. The questionnaire included several sections: 1. Household Members Background Details:
These include household members, relationship to the head of household, gender, date of birth and age, in addition to other demographic and economic data for the household as a whole. 2. Household Questionnaire:
This includes questions related to the household in terms of type of housing unit, material used as flooring in the housing unit, primary fuel type used in cooking, goods and services available, monthly household income, and other indicators. 3. Daily Record Questionnaire: This part of the questionnaire comprised two time records: in the first record, one male member of the household aged 10 years and above is selected at random and in the second record, one female household member aged 10 years and above is selected at random. The day was divided into periods of time of up to 30 minutes each from midnight until six am and [00] 10 minutes for each period during the day from six am until twelve o'clock at night. The record also contains information that shows whether the activity was performed for a fee or financial return or not. Any secondary activity is also recorded. This information identifies the respondent performing these activities, with whom and the means of transportation or venue where the individual performed the various activities throughout the day (during a 24-hour period).

Response rate

The sample size of the survey was 5,903 households and 4,605 households were completed. Weights were adjusted to compensate for the non-response cases. The response rate in the survey in Palestine was 79.6% for households, and 98.1% for the individuals , where 8,560 completed the questionnaire out of 8,779 individuals.