Methodology and Quality Update

Latest Update on Methodology and Quality

07/07/2025 

 Statistical Presentation

Data description

The Labor Market Statistics publication is a quarterly publication that collects data from two sources:
First source: Labor Force Survey.
Second source: Administrative records data at entities concerned with the labor market (the Ministry of Human Resources and Social Development, the General Organization for Social Insurance, and the National Information Center).
The labor market statistics bulletin provides comprehensive data on the labor market in the Kingdom of Saudi Arabia and contributes to building a statistical database specific to the labor market, which can be utilized in preparing and planning future social and economic development programs in the Kingdom.
This publication provides data on key characteristics as follows:
•    Work.
•    Unemployment.
•    Participation in the labor force.
Data is also used to estimates:
•    Unemployment rate.
•    Labor force participation rate.
•    Employment rate of the population and others.

Classifications

The following classification guides are used in the Labor Market Statistics publication:
National Code of Countries and Nationalities (3166 ISO – codes Country):
A statistical classification based on the international standard (ISO 3166_Country codes), which is a standard issued by the International Organization for Standardization (ISO of the UN), and this classification gives numeric and literal codes for the 248 world countries, based on the classification of countries. The classification is used in the Labor Market Statistics publication to classify Saudi or non-Saudi individuals. 
Saudi Classification of Specializations and Educational Levels:
A statistical classification based on the International Standard Education Classification (ISCED_11) and (ISCED_13) for Education and Training Issued by United Nations Educational, Scientific and Cultural Organization (UNESCO) which is the reference classification for the organization of educational programs and related qualifications by education levels and fields. It is comprehensive for all educational programs, levels, and methods, and covers all levels of education from kindergarten to postgraduate levels. This classification is used in the Labor Market Statistics publication to classify individuals 15 years and older according to their majors and education levels.
Saudi Standard Classification of Occupations (ISCO_08):
A statistical classification based on the International Classification (ISCO_08) that provides a system for the classification and compilation of professional information obtained through censuses, statistical surveys, and administrative records. This classification is used in the Labor Market Statistics publication to classify employees based on their occupations.
The National Classification for Economic Activities (ISIC4):
It is a statistical classification based on the International Standard Industrial Classification of All Economic Activities (ISIC4), used to describe the productive activities of an establishment. 
Detailed data is collected through interviews to allow for the production of outputs according to all relevant classifications.
Classifications are available on the GASTAT website: www.stats.gov.sa

Statistical concepts and definitions

Concepts and Terminology of the Labor Market Statistics publication:
•    Dwelling: 
It is a building or part of a building originally intended for the housing of one or more households, with a separate entrance. Whether it is occupied by one or more households or vacant at the time of the survey, it may contain one or more establishments, and it is possible to have both a household and an establishment in the same unit. The housing may consist of one or more rooms, and the types of housing are:
•    Household:
An individual or a group of individuals, whether related or unrelated by kinship, who share meals and reside in the same dwelling during the survey period.
•    Head of the household:
The head of the household is the person designated by the household as its leader from among its residents. This person is typically responsible for making decisions on household matters and must be at least 15 years old. If the household consists of children and their mother, and a relative who does not reside with them looks after their affairs, that relative is not considered the head of the household and is not registered as a member of it, as they are registered as a member of another household. In this case, the mother is considered the head of the household.
•    Work:
Work includes any activity performed by individuals to produce goods or provide services to the market to earn a wage or profit.
•    Workers:
Individuals (15 years and older) who during the time reference period (the reference week prior to the family interview) were in contact with the family:
Have worked for at least one hour for a salary or profit (in cash or in kind), as regular or temporary employees, employers, self-employed, or as trainees engaged in work.
 Or have assisted for at least one hour in any commercial or agricultural activity owned by the household or one of its members or have helped a family member with their work or job.
Or were temporarily absent from their work during the reference period (the past seven days) due to vacation, illness, or any other reason, and will return to it again.
Or individuals with seasonal jobs during the period considered off-season if they continued to perform some tasks and duties related to the job during that period.
And the definition includes students, job seekers, retirees, housewives, etc., who worked for at least one hour during the seven days preceding the household interview. It is worth noting that this does not include household chores such as cooking and laundry performed by the housewife or routine home maintenance carried out by a household member.
•    Unemployed people:
Individuals (15 years and older) who, during the reference period,
were without work during the reference week preceding the household interview.
They have actively searched for work during the four reference weeks preceding the household interview (i.e., they have taken at least one method to look for a job or start their own business), or they will begin a new job or start a business they own in the upcoming period, having previously searched for work or started their own business before the reference period.
Able to work and ready to join employment (i.e., available, and willing to work) during the past week or the two weeks following the date of the household interview.
•    The labor force population:
all individuals (15 years and older) who, during the reference period, were either actually working (employed) or actively seeking work and able to work (unemployed).
•    Population outside the labor force:
All individuals (15 years and older) classified as neither employed nor unemployed, because they are not working, not seeking work, unable to work, or not ready to join work during the survey’s reference period, such as: Students and housewives.
•    Unemployment rate:
An indicator that measures the participation of the working-age population (15 years and older) in the labor force as unemployed, which is the ratio of the unemployed to the labor force (expressed as a percentage).
•    Labor force participation rate:
An indicator that measures the participation of the working-age population (15 years and older) in the labor force as employed or unemployed, which is the ratio of the labor force to the population 15 years and older (expressed as a percentage).
•    Employment rate of the population:
An indicator that measures the proportion of the population (15 years and older) who are employed (expressed as a percentage).
•    Average weekly working hours:
An indicator that measures the average weekly regular working hours of employed people (15 years and above), which is the ratio of total hours worked to total employed people.
•    Average monthly wage of wage earners:
An indicator that measures the average monthly wage of wage earners (15 years and above), which is the sum of the monthly wage to the total number of wage earners or wage trainees (who reported a wage).

Data sources

First source: The first source of Labor Market Statistics is the Labor Force Survey.
A household survey in which data is collected by engaging with a representative sample of the Saudi and non-Saudi populations in all administrative regions of the Kingdom. This includes occupied and unoccupied households. Interviews with households are conducted by completing an electronic questionnaire containing many questions. The survey provides estimates and indicators related to the labor force of the population aged 15 and older who reside in Saudi Arabia. It estimates the population (those in the labor force and those not in the labor force), and calculates key labor market indicators such as unemployment rates, participation rates, and the employed population in the working age group, and others. 
The disseminated key variables of survey data are:
Unemployment, employment, and labor force participation rates by the following variables:
•    Nationality.
•    Sex.
•    Age groups.
•    Educational level
•    Administrative regions
Second source: The second source of Labor Market Statistics is administrative records
They are the recorded and updated data and information held by government entities related to the labor market, generated through official electronic registration and documentation processes followed by the following government agencies.
•    General Organization of Social Insurance GOSI
•    Ministry of Human Resource and Social Development.
•    National Information Center.
These entities regularly provide the authority with the recorded data they hold, as they are considered a primary source of data on employed persons subject to the Civil Service system and the Labor Law in both the public and private sectors in the Kingdom of Saudi Arabia. 
Main variables of administrative data are: 
Workers subject to the Civil Service system, the Labor Law, and the regulations and systems of social insurance and domestic labor, according to the following variables.
•    Nationality.
•    Sex.
•    Age groups.
•    Administrative regions
•    Occupations.
•    Economic activities.

Designing the data collection tool

•    The survey’s questionnaire was drafted and designed by specialists in the Labor Market Statistics Department at GASTAT. International recommendations, standards, and definitions were taken into consideration during the design of the questionnaire, which was presented to experts, specialists, and relevant entities to obtain their insights and comments. Questions were redrafted based on a specific scientific approach aimed at unifying question formats used by researchers.
•    The questionnaire was programmed, and tools for conducting computer-assisted personal and telephone interviews (CAPI & CATI) were developed.
•    Audit and control rules have been established in the form to ensure that the data collected is consistent, accurate, and logical. These rules are designed to establish a logical relationship between answers and different questions and variables to help the researcher detect any errors directly when filling out the data with the household.
•    The questionnaire includes several sections, including:
Housing and household Metadata
Characteristics of household members that measure demographic and social indicators such as age, sex, and education 
Data on employed individuals (15 years and above) and measures employment indicators by occupation, economic activities, wages, and hours worked
Job search and job availability data (individuals 15 years and older who are not employed) measures unemployment indicators by job search methods, duration of unemployment, and previous work experience
The detailed form can be viewed through the following link:
https://www.stats.gov.sa/documents/d/guest/labor-force-survey-2025-q1-en-1

Questionnaire test (cognitive test)

Not available

Statistical population

The Labor Force Survey Framework consists of a list of all buildings and housing units in the Kingdom and is a result of the 2022 Saudi Census. The target population for the Labor Force Survey in Saudi Arabia is the population aged 15 years and above, both Saudi and non-Saudi, who reside in buildings intended for private housing.

Sample Design

The sample was designed with a two-stage stratified cluster systematic random sampling method in which, in the first stage, a random sample was selected from the primary sampling units (counting areas) for each stratum of the adopted sampling design. In the second stage, a systematic random sample of housing units (households) is selected within each selected initial sampling unit.
The sample was divided into 13 administrative regions, 9 metropolitan cities, and 6 special regions, collectively forming the initial stratification. See Table (1). This addition will enable, in the future, the extraction of indicators by major cities and special zones, in addition to the administrative regions. As a result, we now have 29 geographical divisions. If we add the classification into urban, other urban, and rural, this results in 59 primary strata.
In addition, the main advantage of stratification is that it eliminates all existing variation between strata in survey estimates. The ideal approach to stratification is to achieve homogeneity within strata and eliminate it (i.e., achieve heterogeneity) between them based on certain characteristics. To the extent that this is achieved, stratification becomes a powerful tool for reducing variation in survey estimates.
The 59 primary strata were divided into 447 secondary strata based on population data collected during the Saudi Census 2022. The population data used can be summarized as follows:
•    Individual characteristics:
Demographic: age, sex, nationality, marital status, etc.
Social: education, income
by economic activity, occupation, and sector.
•    Household characteristics:
 Distribution of households by type.
 Nationality of the head of the household
•    Housing characteristics:
Housing type
Housing tenure (owned or rented)
An additional advantage of geographical stratification is that it ensures a good geographical distribution of the sample.

Table1: Major Cities and Special Zones:

The sample was allocated using power allocation with an exponent of 0.4 to distribute the sample across the 13 regions. This allocation met the sample size requirements for the 13 regions and all nine other major cities. However, it did not meet the sample size requirements for all six special zones. The sample size requirements were met with only 2 out of the 6 special zones. In the second step, we increased the sample for the remaining four special zones to meet the required sample sizes. This resulted in a total sample of 97,019 housing units.
The design was based on considering enumeration areas as primary sampling units. As for the large enumeration areas, they were subdivided into multiple sampling units so that their selection probabilities are less than 1. The cluster size reached 13 housing units.
In addition, the primary sampling units were reviewed by selecting random probabilities proportional to size, resulting in the selection of 7,100 primary sampling units.
Sample rotation was used by keeping households in the sample for four consecutive quarters, with 25% of the sample each quarter consisting of households being surveyed for the first time, and 75% consisting of rotating households, those already included in the samples from previous quarters.
The main reason for designing the sample rotation system is to reduce the existing variances in estimates related to changes made from one quarter to another. In any ongoing survey, achieving consistency and coherence in estimates of changes over time is extremely important.
In addition to the above, the sample rotation design helps reduce variances in change estimates due to the positive correlation resulting from the similarity of respondents providing data from one quarter to the next.
Reducing the existing variances in change estimates will enhance the surveys' ability to detect significant statistical changes from one quarter to another, as well as help minimize fluctuations between quarters within time series data.
Table showing sample sizes by region:

Statistical unit (sampling unit)

The statistical unit in the Labor Market Statistics publication sample is:
•    The primary sampling unit consists of enumeration areas made up of dwellings.
•    The final sampling unit includes both occupied and vacant dwellings.
•    The observation unit is the households that reside in the dwellings regularly.

Data collection

Data collection from the survey:
Data for the Labor Market are collected through computer-assisted telephone interviews (CATI) and computer-assisted personal interviews (CAPI).
Data collection from administrative records:
In coordination with the relevant departments of the authority, administrative records data for the Labor Market Publication are obtained from the General Organization for Social Insurance, the Ministry of Human Resources and Social Development, and the National Information Center. These data include the number of workers according to a number of variables. 
The data is stored in the authority's databases after undergoing auditing and review processes following approved statistical methods and recognized quality standards. If errors or discrepancies are discovered, the data is cross-referenced with the data source for correction or clarification.

Data collection frequency 

A weekly sample that continuously collects data throughout the quarter.

Reference area

The survey sample is a representative sample for Saudi Arabia's 13 administrative regions.
The stratified sample distribution is based on dividing enumeration areas into urban, other urban, and rural categories.

 Reference period (time reference)

References period to the variables or dataset as following:
•    Data on the number of household members and their demographic characteristics are based on the date of the household interview.
•    Employment data refer to the reference week preceding the household interview, which is defined as a full week starting from Sunday and ending on Saturday 
•    Data on job seekers and those enrolled in education and training refer to the four reference weeks preceding the household interview, defined as four full weeks before the interview date (from Sunday of the first week to Saturday of the last week).
•    Availability for work data refers to the reference week preceding the household interview or the two weeks following it. The two following weeks are defined as the two weeks after the household interview, from Sunday of the first following week to Saturday of the second following week.
It is important to note that in cases of re-interviewing the household or requesting completion of individuals’ data at a later time, the data refer to the reference period of the initial household interview.

Base period

Not applicable.

Measurement unit

Results are measured in the following units:
•    Individuals: They are displayed as absolute numbers (e.g.: Number of workers, number of unemployed people, and working-age population. 
•    Rates, percentages, and relative distribution (e.g.: Unemployment rate, labor force participation rate, ratio of workers to the working-age population, and percentage distribution of workers by educational level.
•    Saudi Riyal: displayed as averages (such as: Average monthly wage)
•    Hours: displayed as averages (such as: Average operating hours/week).

Time coverage

Data has been available since 1999 with annual releases, then semi-annual releases, and starting from 2016, data began to be released quarterly.

Publication frequency

•    1999–2002: Annual.
•    2003–2005: Suspended due to population census activities.
•    2006–2015: Semi-annual.
•    2016–present: Quarterly.

Statistical processing

Error detection

Meticulous processes were implemented to detect errors in the data collected, using automated and manual methods aimed at ensuring quality and accuracy.
These included the following:
•    Identification of illogical or out-of-range values (such as impossible ages or contradictory data).
•    Detecting missing or incomplete data and handling it according to established policies.
•    Reviewing internal consistency among questionnaire responses.
•    Data are reviewed and matched to ensure their accuracy and precision in a way that suits their nature, with the aim of giving the presented statistics quality and accuracy.
•    The data from the current year publication is compared with the data from the previous year to ensure their integrity and consistency in preparation for processing data and extracting and reviewing results.
•    Data processing and tabulation to verify accuracy.
 In addition to the data processing and tabulation to check their accuracy, all the outputs are stored and uploaded to the database after being calculated by GASTAT to be reviewed and processed by specialists in the Labor Market Statistics Department through modern technologies and software designed for this purpose.

Data integration and matching from multiple sources 

In the labor force survey, the national ID of household members is collected and linked with data from the National Information Center during the household interview. This is used to complete data on name, sex, date of birth, age, and relationship to the head of the household, which helps improve the quality of the household’s demographic data.

Imputation and calibration

Imputation of missing values:
In cases of non-response from households, compensation is done by adjusting the weight. Using weight adjustment factors, which are applied to primary sampling units in the labor force survey. Using the weight adjustment factor, the non-response adjustment factor is calculated using the following formula:
Non-response adjustment factor = (Number of households in the primary sampling unit) / (Number of responding households in the primary sampling unit).
In cases of incomplete datasets, some data are compensated using data from the previous rotating sample of the group according to specific conditions and controls. If data from the previous rotating sample is unavailable, compensation is done sparingly and under strict conditions using the statistical method known as "hot deck" imputation, which involves selecting a random similar case for the group based on a set of variables.
In addition, administrative data are used to compensate for some incomplete data sets according to approved conditions and controls.
Calibration:
Survey data weighting:
Weighting the data is a necessary step to produce survey estimates. There are four main steps in weighting survey data as follows:
Weight design
Design weight is considered the inverse of the selection probability. If the selection probability in a certain area is 1/200, then the design weight for that administrative region will be 200. So that all responding households (and the individuals within those households) in the area receive the same design weight value for that area.
Non-response weights
Non-response is compensated by adjusting the weight. By applying a weight adjustment factor at a lower level, such as the level of primary sampling units, which is the approach used for primary sampling units in the labor force survey. The non-response adjustment factor is calculated using the following formula:
Non-response adjustment factor = (Number of households in the primary sampling unit) / (Number of responding households in the primary sampling unit)
Calibration methodology
Calibration is the final step in weight adjustment. In this step, the sample weights are adjusted so that the population estimates in the labor force survey align with the population projections. The raking ratio methodology is used to calibrate the final weights. Using the following control totals in the final weights across two dimensions: 
•    First dimension (Kingdom-level controls):
Five-year age groups (5 years per age group) × sex × nationality
•    Dimension 2 (Controls at the administrative region level):
Administrative region (13 regions) × 3 aggregated age groups (under 15, 15–24, 25 and older) × sex × nationality

Seasonal adjustments

Not applicable, only final results will be published.

Adjustment of preliminary results 

Not applicable, only final results will be published.

Used Resources

Quality dimensions

Suitability

A standard that measures the extent to which the product meets the needs of users.

User needs 

Internal users in the GASTAT for the Labor Market Statistics publication data:
•    Departments under the General Directorate of Social Statistics.
•    Departments under the General Directorate of Economic Statistics.
•    Departments under the General Directorate of Spatial Statistics and Resources.
•    Partnerships and Customer Support Department.
•    Statistical database.
External users and major beneficiaries for the Labor Market Statistics publication data include:
•    Entities concerned with the labor market (Ministry of Economy and Planning, Ministry of Human Resources and Social Development, General Organization for Social Insurance, and National Information Center).
•    Regional and international organizations.
•    Research institutions. Researchers.
•    Media.
•    Individuals. 

The disseminated key variables used by external users:

Completeness 

The Labor Market Statistics Publication data is based on two main sources:
First source: Labor Force Survey.
Second source: Administrative records data from entities concerned with the labor market (the Ministry of Human Resources and Social Development, the General Organization for Social Insurance, and the National Information Center), to provide comprehensive and updated information on statistics of workers and job seekers.

Accuracy and reliability 

A standard that measures how close the calculations or estimates are to the exact or true values that reflect reality.

Overall accuracy 

Data accuracy and reliability are ensured through:
•    Using updated statistical frameworks.
•    Training and qualifying data specialists to enhance their efficiency.
•    Applying quality control rules and error detection during data collection through the electronic questionnaire.
•    Checking the correlation between variables and data consistency.
•    Data is checked with previous years to identify any significant changes in the data.
•    The internal consistency of the data is checked before it is finalized.

Timeliness and punctuality 

A standard that measures the time gap between the availability of information and the occurrence of the event.
However, timeliness reflects the time difference between the date of data publication and the target date when it is actually published.

Timeliness 

GASTAT uses the Special Data Dissemination Standard (SDDS) issued by the International Monetary Fund. According to this Standard, all statistics agencies are required to publish data on a quarterly basis, and with a delay of not more than mid of year (90 days) after the end of the reference period. If the data are from different source, they may be published in a different frequency.

Punctuality 

The publication takes place according to the published release dates on the statistical calendar for the Labor Market Statistics publication on the website of the General Authority for Statistics.
The data are available at the expected time, as scheduled in the statistical release calendar, If the publication is delayed, reasons shall be provided.

Coherence and comparability

Statistics should be consistent internally and over time, and logically interconnected across scope and statistical domains, meaning that data should be comparable across regions and countries as well as across different time periods for the same region, and data from diverse sources can be combined and used interchangeably.

Comparability - geographical

Data are fully comparable.

Comparability - over time 

Since the beginning of the labor force survey in 1999, the survey has undergone continuous improvements and development in terms of the periodicity of the survey, the form, and updating the methodology. Amendments and revisions are made to the survey form to make it compatible with the latest recommendations of the International Labor Organization and the best international practices of the statistical offices of leading countries, taking into account the preservation of comparability with previous data, as a methodology is developed to harmonize recent data after development with historical data; therefore, continuous data since the beginning of the survey is comparable over time.
The following are the most significant changes that have occurred in recent years:
•    1999-2006:
 The survey was conducted annually, except for the years 2004, 2005, and 2010: The survey was not conducted due to the population census being carried out in 2004 and 2010.
•    2007-2015:
The labor force survey began to be conducted semi-annually, except in 2009 and 2011 when it was conducted annually due to the 2010 population census.
•    2011:
Redesigning the survey questionnaire and adding detailed questions to measure employed and unemployed people.
•    2013:
Computer-assisted Personal Interviewing (CAPI) is beginning to be used as the main and only collection method. 
•    2016- Q2:
The survey period was conducted on a quarterly basis.
•    2018:
Redesigning the survey questionnaire and adding detailed questions to measure employed persons, unemployed persons, and those outside the labor force, using the standards and guidelines outlined in Resolution No. 1 issued by the 19th International Conference of Labor Statisticians (19th ICLS) in October 2013.
•    2020- Q2:
The transition to computer-assisted telephone interviews (CATI) was made due to the coronavirus pandemic.
•    Q2 of 2022:
Computer-Assisted Personal and Telephone Interviewing (CAPI & CATI).
•    Q1 of 2023:
The survey shifted to using a weekly sampling method, with continuous data collection covering all weeks within the quarter, in addition to employing a sample rotation system. 
•    Q1 of 2025:
Redesigning the survey questionnaire and adding detailed questions to measure employed persons, unemployed persons, and those outside the labor force.
And applying the standards and guidelines outlined in Resolution No. 1 issued by the 20th International Conference of Labor Statisticians (20th ICLS) in October 2018.
 Related to the new employment status classification (ICSE-18).
The criteria and standards applied in the survey are based on Resolution No. 1 issued by the 21st International Conference of Labor Statisticians (21st ICLS) in October 2013: Related to measuring informal employment.

Coherence- cross domain

Not applicable.

Coherence- sub-annual and annual statistics 

Not applicable 

Coherence- National Accounts 

Data on workers by economic activity and wages are used as inputs in estimating national accounts.

Coherence- internal 

The Labor Market Statistics publication estimates have full internal coherence, as they are all based on the same corpus of microdata, and they are calculated using the same estimation methods.

Accessibility and clarity

The ability for users to access data, the availability of accurate or complete data, and the availability of a methodology and quality report.

Press releases

The announcements for each publication are available on the statistical calendar as mentioned in 7.2. The press releases can be viewed on the website of GASTAT on the link: 
https://stats.gov.sa/news

Publications

GASTAT issues the Labor Market Statistics publication and reports regularly within a pre-prepared dissemination plan and is published on GASTAT’s website. GASTAT is keen to publish its publications in a way that serves all users of different types, including publications in different formats that contain (publication tables, data graphs, indicators, metadata, methodology, and questionnaires) in both English and Arabic.
The Labor Market Statistics publication is available on the link:
Publications

On-line database

The data is published on the statistical database on the link:
GASTAT (stats.gov.sa)

Microdata accessibility

Accurate data is unit-level disaggregated data obtained from multiple sources such as sample statistical surveys, general population and housing censuses, and administrative systems, providing detailed information about the characteristics of individuals, families, business entities, and geographical areas, supporting the construction and development of statistical indicators and scientific research.
The different types of microdata files to meet different information needs:
•    Public use: 
It consists of sets of records containing information on individuals, households, or business entities anonymized in such a way that the respondent cannot be identified either directly such as: (name, address, contact number, identity number etc.) or indirectly (by combining different - especially rare - characteristics of respondents) such as: (age, occupation, education etc.).
•    Scientific use:
These files established based on specific methodology asked by data requesters to extract the datasets with specific characteristics used for strategic studies and decision making as well scientific research purposes on individuals, households, and enterprises with no direct identifiers, which have been subject to control methods to protect confidentiality.
Qualified users who meet the standards and procedures of confidentiality protection can access the files of scientific use of accurate data through the platform "ITAHA" of the General Authority for Statistics, while the most sensitive data for use is shared by visiting the accurate data laboratory within a secure environment managed by the Authority.

References and standards

Framework of the Labor Market Statistics publication:
The concepts, definitions, and classifications are based on international guidelines and standards adopted by the International Labor Organization (ILO).
The labor force survey applies the labor statistics standards and guidelines issued by the International Conference of Labor Statisticians (ICLS), which are updated periodically.
The detailed methodology can be accessed through the following link: https://www.stats.gov.sa/documents/d/guest/methodology-of-labor-market-statistics-q1-2025-en

Quality assurance

GASTAT takes the following principles into consideration: Impartiality, ensuring that the statistical product is user-oriented, maintaining the quality of processes and outputs, enhancing the effectiveness of statistical operations, and reducing the burden on respondents. 
Data validation is carried out through procedures and quality controls that are implemented at different stages throughout the process such as: (data entry, data collection, and other final controls).

Quality assessment

GASTAT performs all statistical activities according to a national model (Generic Statistical Business Process Model – GSBPM). According to the GSBPM, the final stage of statistical activities is overall evaluation using information gathered in each stage or sub-process. This information is used to prepare the evaluation report, which outlines all the quality issues related to the specific statistical activity and serves as input for improvement actions.

Confidentiality

Confidentiality – Policy

According to Royal Decree No. 23 dated 07/12/1397, data must always be kept confidential and must be used by GASTAT for statistical purposes only.
Therefore, the data is protected in the data servers of GASTAT.

Confidentiality - Data Treatment

Data of SMEs survey are presented in the right tables in order to summarize, understand, as well as extract their results. Moreover, to compare them with other data, and to obtain statistical significance about the selected study population. However, referring to such data indicated in tables is much easier than going back to check the original questionnaire that may include some data like names and addresses of individuals, and names of data providers, which violates data confidentiality of statistical data.
“Anonymity of data” is one of the most important procedures. To keep data confidential,
GASTAT removed information on individual persons, households, or business entities such a way that the respondent cannot be identified either directly such as: (Names, addresses, contact numbers, or identification numbers. etc.) or indirectly (by combining different - especially rare - characteristics of respondents: (age, occupation, education etc.).

Dissemination policy

Statistical calendar

The Labor Market statistics publication is included in the statistical calendar.
Statistical Calendar

User access

One of GASTAT’s objectives is to better meet its clients' needs, so it immediately provides them with the results once the Labor Market statistics publication is published. 
It also receives questions and inquiries from clients about the publication and its results through various communication channels, such as:
•    GASTAT official website: www.stats.gov.sa
•    GASTAT official e-mail address:  info@stats.gov.sa
•    Client support e-mail address:  info@stats.gov.sa 

•   Official visits to GASTAT’s official head office in Riyadh or one of its branches in Saudi Arabia.
•    Official letters.
•    Statistical telephone: (199009).