State of Palestine (West Bank and Gaza) PS: People Practicing Open Defecation: % of Population data was reported at 0.276 % in 2015. This records an increase from the previous number of 0.273 % for 2014. State of Palestine (West Bank and Gaza) PS: People Practicing Open Defecation: % of Population data is updated yearly, averaging 0.362 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.503 % in 2000 and a record low of 0.271 % in 2013. State of Palestine (West Bank and Gaza) PS: People Practicing Open Defecation: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted average;

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.

State of Palestine (West Bank and Gaza) PS: Employment To Population Ratio: National Estimate: Aged 15-24: Female data was reported at 3.673 % in 2017. This records a decrease from the previous number of 4.164 % for 2016. State of Palestine (West Bank and Gaza) PS: Employment To Population Ratio: National Estimate: Aged 15-24: Female data is updated yearly, averaging 4.163 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 5.247 % in 2000 and a record low of 3.058 % in 2013. State of Palestine (West Bank and Gaza) PS: Employment To Population Ratio: National Estimate: Aged 15-24: Female 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: Employment and Unemployment. Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2018.; Weighted average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Abstract

The Jerusalem Household Social Survey 2013 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, 2013 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 sampling frame for Jerusalem (J1 and J2) was based on the census implemented by PCBS in 2007 and consisting of enumeration areas. These enumeration areas were used as primary sampling units (PSUs) in the first stage of the sample selection.

The estimated sample size is 1,260 households responding in Jerusalem governorate.

Stratified cluster random sample with two-stages: First stage: Selection of a systematic random sample of 42 enumeration areas (24 EAs in J1 and 18 EAs in J2). Second stage: A sample of 30 responsive households from each enumeration area selected in the first stage.

Sample Strata The population was divided by: 1-Region (Jerusalem J1, Jerusalem J2) 2-Locality type (Jerusalem J1: urban, camp; Jerusalem J2: urban, rural, camp).

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 Access 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 1,820 family in Jerusalem Governorate, where the final results of the interviews were as follows: The number of families who were interviewed (1,188) in Jerusalem Governorate, (715) in J1, (473) in J2.

Sampling error estimates

Accuracy of the Data

Statistical Errors Data of this survey can be affected by statistical errors due to use of a sample. Variance was calculated for the most important indicators and demonstrates the ability to disseminate results for Jerusalem governorate. However, dissemination of data by J1 and J2 area indicates values with a high variance

Non-Statistical Errors It is possible for non-statistical errors to occur at all stages of project implementation or during the collection or entry of data. These errors can be summarized as non-response errors, response errors (respondent), corresponding errors (researcher) and data entry errors. To avoid errors and reduce their impact, strenuous efforts were made in the intensive training of researchers on how to conduct interviews, the procedures that must be followed during the interview and aspects that should be avoided. Practical exercises and theory were covered during the training session. Errors gradually decreased with the accumulation of experience by the field work team, which consisted of permanent and non-permanent researchers who conduct work on every PCBS survey.

In general, non-statistical errors were related to the nature of the Social Survey of Jerusalem and can be summarized as follows: · Many households considered the specific details of the survey as interference in their private lives. · Israeli impact on Palestine (curfew and closure). · Some households thought the survey was related to social assistance or to taxes. · Hesitation by households in the Jerusalem area to supply data because they were afraid of Israeli procedures against them if they participated in a Palestinian survey or activity.

Data Processing The data processing stage consisted of the following operations: 1. Editing and coding prior to 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 were 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. · Logic and consistency check of data entered. · Possibility for internal editing of question answers. · Maintaining a minimum of digital data entry and field work errors. · User-friendly handling. · Possibility of transferring data into another format to be used and analyzed using other statistical analytic systems such as SPSS.

Data entry began on April 17, 2013 and finished on July 14, 2013. Data cleaning and checking processes were initiated simultaneously with the data entry. Thorough data quality checks and consistency checks were carried out and SPSS for Windows version 10.0 was used to perform the final tabulation of results.

Possibility of Comparison At this stage, comparison can be made for time series periods and other sources. Where the survey results were compared with the data in 2010. The data were compared with the final results of the Population, Housing and Establishments Census of 2007 for Jerusalem and the results were very consistent.

PS: Employment To Population Ratio: Modeled ILO Estimate: Aged 15-24: Female data was reported at 3.832 % in 2018. This records an increase from the previous number of 3.537 % for 2017. PS: Employment To Population Ratio: Modeled ILO Estimate: Aged 15-24: Female data is updated yearly, averaging 4.273 % from Dec 1991 (Median) to 2018, with 28 observations. The data reached an all-time high of 5.163 % in 2007 and a record low of 3.074 % in 2013. PS: Employment To Population Ratio: Modeled ILO Estimate: Aged 15-24: Female 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: Employment and Unemployment. Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Abstract

Because of the importance of the household sector and due to it's large contribution to energy consumption in the Palestinian Territory, PCBS decided to conduct a special household energy survey to cover energy indicators in the household sector. To achieve this, a questionnaire was attached to the Labor Force Survey.

This survey aimed to provide data on energy consumption in the household and to provide data on energy consumption behavior in the society by type of energy.

The survey presents data on various energy households indicators in the Palestinian Territory, and presents statistical data on electricity and other fuel consumption for the household, using type of fuel by different activities (cooking, baking, conditioning, lighting, and water Heating).

Analysis unit

Households

Universe

The target population was all Palestinian households living in West Bank and Gaza.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The sampling frame consists of all the enumeration areas enumerated in 2007: each enumeration area consists of buildings and housing units with an average of around 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 3,184 households.

Sampling Design: The sample of this survey is a part of the main sample of the Labor Force Survey (LFS), which is implemented quarterly (distributed over 13 weeks) by PCBS since 1995. This survey was attached to the LFS in the third quarter of 2013 and the sample comprised six weeks, from the eighth week to the thirteen week of the third round of the Labor Force Survey of 2013. The sample is two-stage stratified cluster sample:

First stage: selection of a stratified systematic random sample of 206 enumeration areas for the semi-round.

Second stage: selection of a random area sample of an average of 16 households 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 camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The design of the questionnaire for the Household Energy Survey was based on the experiences of similar countries as well as on international standards and recommendations for the most important indicators, taking into account the special situation of the Palestinian Territory.

Cleaning operations

The data processing stage consisted of the following operations: - Editing and coding prior to data entry: all questionnaires were edited and coded in the office using the same instructions adopted for editing in the field. - Data entry: The household energy survey questionnaire was programmed onto handheld devices and data were entered directly using these devices in the West Bank. With regard to Jerusalem J1 and the Gaza Strip, data were entered into the computer in the offices in Ramallah and Gaza. At this stage, data were entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements: · To prevent the duplication of questionnaires during data entry. · To apply checks on the integrity and consistency of entered data. · To handle errors in a user friendly manner. · The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

During fieldwork 3,184 families were visited in the Palestinian Territory. There are 2,692 complete questionnaires, which in percentage was about 85%.

Sampling error estimates

Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences are anticipated in comparison with the real values obtained through censuses. The variance was calculated for the most important indicators: the variance table is attached with the final report. There is no problem in the dissemination of results at national and regional level (North, Middle, South of West Bank, Gaza Strip) and by locality. However, the indicator of averages of household consumption for certain fuels by region show a high variance.

Non Sampling Errors The implementation of the survey encountered non-response where the household was not present at home during the field work visit and where the housing unit was vacant: these made up a high percentage of the non-response cases. The total non-response rate was 10.8%, which is very low when compared to the household surveys conducted by PCBS. The refusal rate was 3.3%, which is very low compared to the household surveys conducted by PCBS and may be attributed to the short and clear questionnaire.

The survey sample consisted of around 3,184 households, of which 2,692 households completed the interview: 1,757 households from the West Bank and 935 households in the Gaza Strip. Weights were modified to account for the non-response rate. The response rate in the West Bank was 86.8 % while in the Gaza Strip it was 94.3%.

Non-Response Cases

No. of cases non-response cases
2,692 Household completed 35 Household traveling 17 Unit does not exist 111 No one at home
102 Refused to cooperate
152 Vacant housing unit 5 No available information
70 Other
3,184 Total sample size

Response and non-response formulas:

Percentage of over coverage errors = Total cases of over coverage x 100% Number of cases in original sample = 5.3%

Non response rate = Total cases of non response x 100% Net Sample size = 10.8%

Net sample = Original sample - cases of over coverage Response rate = 100% - non-response rate = 89.2%

Treatment of non-response cases using weight adjustment

Where

the primary weight before adjustment for the household i g: adjustment group by ( governorate, locality type ). fg: weight adjustment factor for the group g. : Total weights in group g
cases : Total weights of over coverage : Total weights of response cases

We calculate fg for each group ,and final we obtain the final household weight () by using the following formula:

Comparability The data of the survey are comparable geographically and over time by comparing data from different geographical areas to data of previous surveys and the 2007 census.

Data quality assurance procedures Several procedures were undertaken to ensure appropriate quality control in the survey. Field workers were trained on the main skills prior to data collection, field visits were conducted to field workers to ensure the integrity of data collection, editing of questionnaires took place prior to data entry and a data entry application was used that prevents errors during the data entry process, then the data were reviewed. This was done to ensure that data were error free, while cleaning and inspection of anomalous values were carried out to ensure harmony between the different questions on the questionnaire.

Technical notes The following are important technical notes on the indicators presented in the results of the survey: · Some households were not present in their houses and could not be seen by interviewers. · Some households were not accurate in answering the questions in the questionnaire.
· Some errors occurred due to the way the questions were asked by interviewers. · Misunderstanding of the questions by the respondents. · Answering questions related to consumption based on estimations. · In all calculations related to gasoline, the average of all available types of gasoline was used. · In this survey, data were collected about the consumption of olive cake and coal in households, but due to lack of relevant data and fairly high variance, the data were grouped with others in the statistical tables. · The increase in consumption of electricity and the decrease in the consumption of the other types of fuel in the Gaza Strip reflected the Israeli siege imposed on the territory.

Data appraisal

The data of the survey is comparable geographically and over time by comparing the data between different geographical areas to data of previous surveys.

Abstract

The survey provides basic data needed for the development of national policies. The main objectives of the Time Use Survey were as follows:

1. Measurement and analysis of quality of life or general well-being.
2. Identifying demographic and socio-economic characteristics of individuals in Palestinian society.
3. Measurement and valuation of unpaid work (domestic and volunteer work) and development of household production accounts.
4. Improving estimates of paid and unpaid work.
5. Assisting planners and policy makers to develop strategies and policies that may contribute to developmental planning issues.

It is also a rich source of information about the use of time to learn about the nature and structure of individuals in Palestinian society during the year 2012/2013, in different age groups, including children, women, youth and the elderly, and to illuminate the path for decision makers and policy makers in the process of comprehensive national development in this country.

Time Use Survey is a basic tool to determine gender issues. The data enable analysis of the quality of life and an assessment of the extent of female participation in paid and unpaid work (housework and volunteer work) and women's contribution to national accounts.

Geographic coverage

1- Governorate (16 governorates in west bank and Gaza strip) 2- Locality type (urban, rural, camps)

Analysis unit

Individual

Universe

The 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 .

Kind of data

Sample survey data [ssd]

Sampling procedure

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:

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

Sampling deviation

The sample size of the survey is 5,903 Palestinian households.

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). Third stage: selection two individuals male and female (10 years and more) from each household selected in second stage using random kish tables

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire 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. Identification Data This identifies a unified means of determining data that define a household, including the divisions of sample design: the number in the enumeration area, governorate and locality, building identification number, number of household, and the name of head of household.

2. Quality Control This is the development of controls of field and office operations and the sequencing in questionnaire stages, usually beginning with data collection through to field and office auditing, data coding, data entry, checks after data entry, and ending with the storage process.

3. 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.

4. 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.

5. 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 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).

Cleaning operations

Data verification: comprehensive automated rules of data verification in between questions ensured consistency and identification of answers that were out of range or irrational. This was carried out by a special program performed on a regular basis. The team reviewed error messages and modification of errors based on observations or returned the questionnaire to the field for double checking. The auditing mechanism was prepared by the project management and applied to the data entry program by a programmer where necessary. Appropriate data auditing tests proposed by the project management during the auditing procedure were inclusive and covered all questions in the questionnaire. The questionnaires were drawn from extracted lists and checked automatically, corrected and adjusted on the computer. Then a second list was extracted for the same questionnaires to ensure that the amendment was valid and that all questionnaires had been modified.

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

Sampling error estimates

Survey data may be affected by statistical errors as a result of the use of a sample rather than a comprehensive survey covering all units of the study population. Thus, differences may be anticipated from the real values that emerge from a census and variations were calculated for the most important indicators.

The results indicated that there was no problem in the dissemination of data applicable to Palestine as a whole or on a regional basis (the West Bank and the Gaza Strip).

Data appraisal

The concept of data quality includes multiple aspects, starting from initial planning for the survey and ending with data dissemination and interpretation of data for optimal use. The most important components of statistical quality include accuracy, comparability, and quality control procedures. Statistical quality also includes checking and auditing data accuracy in multiple aspects of the survey, particularly statistical errors due to the use of a sample, plus non-statistical errors by staff and the use of survey tools. Response rates may also have a crucial impact on estimates

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(LFS) 2013. The survey rounds covered a total sample of about 30,524 households, and the number of completed questionaire is 26,420.

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 2013.

---> Sampling Frame: The sampling frame consists of master sample which updated in 2011, each enumeration area consists of buildings and housing units with average of about 124 households in it. These master sample consists of 596 enumeration areas, we used 494 enumeration areas as a framework for the labor force survey sample in 2013, and these units have been used as primary sampling units (PSUs).

---> Sampling Size: The estimated sample size in the first quarter is 7,676 households, in the second, third, and fourth quarter is 7,616 household for each quarter.

---> Sample Design The sample of this survey is implemented periodically every quarter by PCBS since 1995, so this survey implement every quarter in the year (distributed over 13 weeks). The sample is two stage stratified cluster sample with two stages: first stage we select a systematic random sample of 494 enumeration areas for the whole round. second stage we select a random area sample of average 16 households from each enumeration area selected in the first stage.

---> 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 494 master sample enumeration 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 for 2 consecutive rounds, left for the next two rounds, then selected for the sample for another 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).

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 about 30,524 households of which 26,420 households completed the interview; whereas 17,162 households from the West Bank and 9,258 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 89.3% while in the Gaza Strip it reached 95.6%.

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 possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers 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, which was tested before starting the data entry process. To stay in contact with the progress of field work activities and to limit obstacles, there was continuous contact with the field work team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by field workers were discussed to clarify any issues. Non-sampling errors can occur at 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 a direct bearing on limiting the magnitude of non-sampling errors and hence enhancing the quality of the resulting data. The following are possible sources of non-sampling errors: The implementation of the survey encountered non-response where the case (household was not present at home) during the fieldwork visit and (Vacant Housing unit) become the high percentage of the non response cases. The total non-response rate reached 8.6% which is very low once

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years excluding people in hospitals, prisons and living outside the household for a period longer than 6 months.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 1000

Mode of data collection

Face-to-face [f2f]

Research instrument

For each wave, suggestions for questions are solicited by social scientists from all over the world and a final master questionnaire is developed in English. Since the start in 1981 each successive wave has covered a broader range of societies than the previous one. Analysis of the data from each wave has indicated that certain questions tapped interesting and important concepts while others were of little value. This has led to the more useful questions or themes being replicated in future waves while the less useful ones have been dropped making room for new questions.

The questionnaire is translated into the various national languages and in many cases independently translated back to English to check the accuracy of the translation. In most countries, the translated questionnaire is pre-tested to help identify questions for which the translation is problematic. In some cases certain problematic questions are omitted from the national questionnaire.

WVS requires implementation of the common questionnaire fully and faithfully, in all countries included into one wave. Any alteration to the original questionnaire has to be approved by the EC. Omission of no more than a maximum of 12 questions in any given country can be allowed.

Sampling error estimates

Estimated error: 3.2