Methodology and Quality Update

Latest Update on Methodology and Quality

09/10/2025

Statistical Presentation

Data description

The Short-Term Business Statistics provide fast-paced economic data used to measure the performance of various economic activities in the Kingdom of Saudi Arabia.
The Short-Term Business Statistics is a survey conducted to collect data on the main characteristics as follows:
•    Employees' compensations
•    Operating revenues.
•    New business registrations.
•    Bankruptcy declarations.
•    Building permits.
Data is also used to estimates:
•    Index and growth rates of compensation of employees.
•    Index and growth rates of operating revenues.
•    Index and growth rates of new business registrations.
•    Index and growth rates of bankruptcy declarations.
•    Index and growth rates of building permits.

Classifications

The following classification is applied in the Short-Term Business Statistics:
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.
The classifications are available on GASTAT’s website: www.stats.gov.sa

Statistical concepts and definitions

Terminologies and concepts of Short-term Business Statistics:
•    Establishment:
It is an economic unit with a legal entity (holding a commercial registration) that carries out a specific economic activity and is owned by an individual, a group of individuals, a company, a semi-governmental sector, or an institution.
•    Main economic activity:
The economic activity of any establishment is defined as all the activities or services the establishment engages in or provides, resulting in returns. Sometimes, the establishment may not generate financial returns from its activities, as is the case with charitable organizations that rely on donations. In the case of having multiple economic activities for a single establishment, the most revenue-generating activity is chosen. The classification of economic activity for establishments is based on the International Standard Industrial Classification (ISIC.4).
•    Compensation of Employees:
All amounts due periodically by the establishment to its employees during the month, including wages and salaries for regular working hours and any fixed allowances given to them, in addition to all kinds of benefits and allowances. such as housing and social insurance.
•    Operating revenues:
It refers to all cash revenues generated from the establishment’s main activity or other secondary activities, including sales of goods purchased for resale in the same condition.

Data sources

Short-Term Business Statistics data are based on two sources:
First source: The Short-Term Business Statistics Survey
 The main variables published from the Short-Term Business Statistics Survey data are:
•    Employees' compensations
•    Operating revenues.
Second source: Data from administrative records:
•    Ministry of Commerce.
•    Ministry of Municipalities and Housing.
•    Bankruptcy Commission (EISAR).
The main published variables from the administrative data source are:
•    New business registrations.
•    Bankruptcy declarations.
•    Building permits.

Designing the data collection tool

The Short-Term Business Statistics form was carefully designed to avoid unnecessary details that could negatively affect data quality and response rates, focusing instead on the essential items that mainly cover the number of employees, their compensation, and operating revenues.
Business rules were also incorporated to control data logic and ensure its accuracy and validity.
The latest update to the questionnaire design was carried out in 2023.
The short-term business survey questionnaire consists of several sections: 
•    Section one: It relates to the basic data of the establishment (such as identification data and economic activity). 
•    Section two: Number of employees.
•    Section three: Workers' compensations
•    Section four: Operating expenses.
•    Section five: Operating revenues, including e-commerce sales.
•    Section six: Changes in fixed assets.

Questionnaire test (cognitive test)

The outputs of the cognitive test conducted in 2022 were adopted for the Short-Term Business Statistics survey and the wholesale and retail trade statistics survey.

Statistical population

The statistical population of the Short-Term Business Statistics survey consists of all establishments engaged in economic activities in the Kingdom of Saudi Arabia within the business frame. This frame serves as the list containing all units of the target population for this survey and for other economic surveys conducted by the General Authority for Statistics. It includes the classification of all establishments by economic activity at multiple levels, as well as establishment size, administrative regions, and other basic data used in constructing various economic samples. The sampling frame is considered the list of all establishments that meet the survey conditions specified by the responsible department.

Sample Design

The sample was designed using the stratified systematic random sampling method, in which a systematic random sample of establishments was selected for each stratum of the adopted sampling design.
Stratification:
To increase the efficiency of the sample and improve its representation of the target population, establishments in the sampling frame were classified into homogeneous strata. In order to obtain more accurate results compared to the simple random sampling method of the same size, and to ensure an adequate number of establishments at publishable levels, a two-level stratification approach was applied as follows:
Stratification at the 2-digit level of economic activity (ISIC4).
Stratification by establishment size categories, which are:
•    Micro enterprises: Establishments with 1 to 5 employees.
•    Small enterprises: Establishments with 6 to 49 employees.
•    Medium enterprises: Establishments with 50 to 249 employees.
•    Large enterprises: Establishments with more than 249 employees.
Size of sample:
The sample size was calculated at the first section of the economic activity classification (ISIC4) to ensure the production of reliable estimates at this level (publication level) as well as at the national level. Based on the request of the survey-owning department, it was decided to include all large establishments within the sample. 
Parameters used in estimating the sample size:
•    The total number of establishments from the frame at the first section of the economic activity classification (ISIC4).
•    The mean and variance at the first level (division) of the economic activity classification (ISIC4) for estimating the average number of employees (based on the data from the previous survey round – September 2023).

•    The design effect at the first level (division) of the economic activity classification (ISIC4) for estimating the average number of employees (based on the data from the previous survey round – September 2023).

•    The response rate at the first level (division) of the economic activity classification (ISIC4) for estimating the average number of employees (based on the data from the previous survey round – September 2023), with the specification of an acceptable minimum threshold.

•    The allowable relative margin of error.

•    A confidence level was used in estimating the average number of employees  
The sample size for each study domain at the first level of ISIC4 was determined using the following equation:

Whereas:

• n_h: Sample size for each stratum h   (study domain).
• Deff_h: Estimated design effect for each stratum h  (study domain).
• resp_h: Estimated response rate for each stratum h   (study domain).
• S_h: Standard deviation for each stratum h  (study domain).
• α: Confidence level factor in estimating the indicator for each stratum h  (study domain).
•  re_h  : Allowed relative error in estimating the indicator for each stratum h  (study domain).
• yh : Average of the indicator for each stratum h  (study domain).
• Nh: Total establishments for each stratum  h (study domain) in the frame.​​​​

The result of the sample size calculation, using the previously mentioned equation, was distributed across the establishment size classes for each study domain. Large establishments within the same stratum were then excluded, since all large establishments were included in the sample with a 100% probability due to their importance. The remaining estimated sample size for each stratum was subsequently distributed across the three remaining size classes using (Power Allocation).
This is followed by the final step of distributing the sample at the second level of the economic activity classification (ISIC4), using the Probability Proportional to Size (PPS) allocation method, as this approach reduces the variance of the weighting factors, thereby reducing the variance of the estimates and increasing the efficiency of the design. 
The calculations outlined above resulted in a total sample size of 12,575 establishments, distributed as shown in the tables below:
Table Distribution of the survey sample at the 1-digit section of the International Standard Industrial Classification of Economic Activities (ISIC4).

Statistical unit (sampling unit)

The statistical unit of the Short-Term Business Statistics survey is the establishment.

Data collection

Data collection from the survey:
Data for the Short-Term Business Statistics is collected through Computer-Assisted Telephone Interviews (CATI), Computer-Assisted Web Interviews (CAWI), and Computer-Assisted Personal Interviews (CAPI).

Data collection frequency 

Monthly.

Reference area

The Short-Term Business Statistics cover all thirteen administrative regions of the Kingdom of Saudi Arabia.

Reference period (time reference)

References period to the variables or dataset as following:
•    The data for the Short-Term Business Statistics are based on the month preceding the data collection process.

Base period

The base year used is 2023.

Measurement unit

Some indicators are calculated as rates (e.g., Index and growth rates of compensation of employees.

Time coverage

The data are available to Auq 2025.

Publication frequency

Monthly.

Statistical processing

Error detection

 A total of nine rules were established to validate the data and ensure their consistency, as detailed below:
•    3 alert rules.
•    5 blocking rules.
•    1 transfer rule.

Data integration and matching from multiple sources 

Data extracted from administrative sources is used in integration with survey data to obtain the final indicators. The administrative data source is directly relied upon to feed the indicators related to new business registrations, bankruptcy declarations, and building permits.

Imputation and calibration

Imputation (for non-response cases or incomplete datasets):
The approach used for imputation in the Short-Term Business Statistics survey, whether for establishments with complete non-response or for missing data on specific variables. Reinterviews are allowed to obtain missing data from respondents or cases of non-response. Subsequently, missing, or non-response data are handled by following a scientific methodology to estimate the results, taking into account several considerations such as historical data series, monthly growth rates by activity, an acceptable range of missing data, and estimates based on stratum-level data.

Seasonal adjustments

Not applicable.

Adjustment of preliminary results 

Updated data: 60 days from the release of the preliminary data.

Used Resources

Quality dimensions

Suitability

A criterion that indicates how well the product meets users’ needs.

User needs 

Internal users in the GASTAT for the Short-Term Business Statistics data:
•    National accounts.
Some external users and beneficiaries greatly benefit from the short-term business statistics, including:
•    Government entities.
•    Regional and international organizations.
•    Research institutions.
•    Media.
•    Individuals.
The disseminated key variables that are mostly used by external users:

Completeness 

 The data is complete, having ensured comprehensive coverage of indicators to accurately encompass all targeted activities. Detailed indicators are provided according to the national classification of economic activities (ISIC4) at the first level, ensuring a full and integrated representation of all relevant economic activities.

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 

•    The data collected is improved through the researchers, that have been selected according to a set of practical and objective criteria and training program related to the field of work.
•    Alert, prevention, and correction rules are applied during the data collection process to the e-questionnaire of the (short-term business statistics) education and training survey in order to improve data quality.
•    Data is checked with previous months to identify any significant changes in the data.
•    The internal consistency of the data is checked before it is finalized.
•    The links between variables are checked and coherence between different data series is confirmed.

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 monthly basis, and with a delay of no more than 6 weeks (42 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 is released according to the dates specified in the statistical calendar for short-term business statistics, as published 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

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

Comparability – geographical

Some indicators can be compared locally at the administrative region level, such as the building permits indicator by administrative regions. Other indicators, however, are published for the Kingdom of Saudi Arabia as a whole without regional disaggregation. Moreover, the indicators can be compared across countries at the first level of the National Classification of Economic Activities.

Comparability - over time 

The survey started in 2016 as a quarterly survey. The major changes that have occurred recently: 
•    2019:
The survey was suspended at the end of 2019.
•    Q1 of 2023:
Data collection started as a monthly survey following the transformation and integration with the wholesale and retail trade statistics survey.

Coherence- Cross domain

The data are consistent, as data consistency was verified across the different classification levels according to ISIC4. It was ensured that the data classified at the second level (wholesale and retail trade statistics survey) align with the detailed data available at the first level (Short-Term Business Statistics survey). These procedures contribute to ensuring integration and coherence between classification levels, thereby enhancing the reliability of the data and the quality of the analysis based on them, and ensuring that the results are free of contradictions.

Coherence- Sub-annual and annual statistics 

Not applicable.

Coherence- National Accounts 

The data is consistent, as the results and information derived from relevant data sources and statistics were verified for compatibility.

Coherence- Internal 

The Short-Term Business Statistics have full internal consistency.

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 10.1. The press releases can be viewed on the website of GASTAT on the link: 
https://stats.gov.sa/news

Publications

GASTAT issues the Short-Term Business Statistics publication regularly within a pre-prepared dissemination plan, and it 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 results of the Short-Term Business Statistics are available at:
https://www.stats.gov.sa/statistics

On-line database

The data is published on the statistical database:
https://hue.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 requester 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

•    The methodological manual of European short-term business statistics (2021 edition):
The methodological manual of European short-term business statistics
•    System of National Accounts 2008 (SNA 2008):
https://unstats.un.org/unsd/nationalaccount/sna2008.asp

Quality assurance

GASTAT considers the following principles: 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 is validated through procedures and quality controls that are applied during the process at various stages, 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 07/12/1379, 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 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 Short-Term Business Statistics have been 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 publication's results once the Short-term Business 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).