Methodology and Quality Update

Latest Update on Methodology and Quality

23/07/2026

Statistical Presentation

Data description

The Short-term Business Statistics Survey provides fast-paced economic data used to measure the performance of various economic activities in Saudi Arabia. The survey is conducted to collect data on the main characteristics, as follows:

• Workers' compensations.
• Operating revenues.
• Bankruptcy declarations.
• Issued building permits.
  The data is also used to estimate the following:
• Index and growth rates of compensation of employees.
• Index and growth rates of operating revenues.
• Number of bankruptcy filings.
• Number of issued mining licenses:

Classifications

The following classification is applied in the Short-term Business Statistics.
The National Classification for Economic Activities (SSIC):
It is a statistical classification based on the International Standard Industrial Classification of All Economic Activities (ISIC4), and it is used to describe the productive activities of an establishment. 
The classifications are available on GASTAT’s website: 
The National Classification for Economic Activities

Statistical concepts and definitions

Terminologies and concepts of Short-term Business Statistics:

• Establishment:
  An establishment, or part of an establishment, with a fixed location, that carries out one or more economic activities under a single management and has, or can have, regular accounts. The owner of the establishment may be either a natural or a legal person.
• Main economic activity:
  The activity carried out by the establishment that accounts for the largest share of the total value of its production. The classification of economic activity for establishments is based on the International Standard Industrial Classification (ISIC.4).
• Compensation of Employees:
  All amounts of wages, salaries, in-kind benefits, and social contributions payable to employees during the accounting period in return for work performed, whether in cash or in kind, before any deductions such as social insurance contributions, taxes, and similar items.
• Operating revenues:
  Cash revenues generated from the establishment’s main economic activity or other secondary activities, such as the sale and marketing of its products, the provision of services to consumers, or the trading of goods in general. It also includes daily operating receipts. These revenues comprise the total value of sales of manufactured products, in addition to other operating revenues not directly related to the establishment’s main economic activity but associated with its secondary activities. They include revenues from industrial services, secondary activities, the sale of production waste, and the rental of non-agricultural buildings and land, as well as the leasing of machinery and equipment, etc., and any other operating revenues, provided that their types are specified. etc., and any other operating revenues, provided that their types are specified.

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:

• Workers' compensations
• Operating revenues.

Second source: Data from administrative records:

• Ministry of Municipalities and Housing.
• Bankruptcy Commission (Eisar).

The main published variables from the administrative data source are:

• Bankruptcy declarations.
• Issued building permits.

Designing the data collection tool

Data is collected using a questionnaire prepared and designed by specialists at the General Authority for Statistics (GASTAT). The data collection tool is developed in electronic formats (CAPI), (CATI), and (CAWI) to ensure ease of use by researchers. In designing the tool, international recommendations, standards, and definitions are taken into account. It is also shared with relevant entities to obtain their views and feedback. Furthermore, the questions are formulated in a specific scientific manner to standardize the wording of questions.
The latest update to the questionnaire design was carried out in 2023.
The Short-term Business Survey questionnaire consists of several sections: 

• 101: Type of economic activity
• 102: Number of paid employees.
• 103.: Number of unpaid employees.
• 104: Compensation of employees.
• 105: Operating revenues
• 106.: Job vacancies
• 107.: Operational expenses
• 108.: E-commerce sales
• 109: Changes in fixed assets.

Review and Correction Rules:
Validation and consistency rules are incorporated into the questionnaire to ensure that the collected data is consistent, accurate, and logical. These rules were designed by establishing logical relationships between responses, questions, and different variables to help the field researcher detect any errors directly during data entry.
To ensure the quality of the Short-term Business Statistics data, three types of validation and editing rules have been established, as follows:

• Navigation rules between sections and fields:
  Specific rules have been programmed to control the automatic navigation between sections and fields, based on the respondent’s inputs. There are two navigation rules.
• Error rules:
  Rules that cannot be bypassed during the data entry process. The researcher must correct the data by referring back to the respondent to verify its accuracy. There are four such rules.
• Alert rules (warnings):
  Rules established to verify the accuracy of the researcher’s data entry. The researcher may override these alerts if the data is confirmed to be correct; there are four (4) such rules.

Questionnaire test (cognitive test)

Cognitive testing was conducted on several questionnaire items. The interview sample consisted of a random sample of establishments distributed across the regions of Saudi Arabia.
During the cognitive testing process, the following evaluation pillars were taken into consideration: The overall concept of the question, clarity of question wording, clarity of terms used in the question, appropriateness of the response options, participants’ ability to answer the questions effectively, and the extent to which participants were willing to disclose their answers. This process resulted in a report summarizing the full findings of the cognitive test.

Statistical population

The statistical population of the Short-term Business Statistics Survey consists of all establishments engaged in economic activities in Saudi Arabia within the business frame, which is the list containing all units of the target population for this survey and for other economic surveys conducted by the General Authority for Statistics (GASTAT). The frame includes the classification of all establishments based on 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 the list of all establishments that meet the survey conditions specified by the responsible department.

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.
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. To obtain more accurate results compared with a simple random sample of the same size, and to ensure a sufficient number of establishments at publishable levels, a two-level stratification approach is 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. 

Sample size:
The sample size was calculated at the level of each stratum within the domain of study (economic activity at the first level (section) of ISIC4), taking into account retaining approximately 67% of the previously responding sample for the purposes of the survey.
The resulting sample size for each study domain (economic activity at the first level (section) of ISIC4) was then allocated across establishment size classes, and subsequently across the second level of ISIC4, using the Probability Proportional to Size (PPS) allocation method. This method reduces the variance of sampling weights, thereby reducing the variance of estimates, and improving the efficiency of the sample design. In addition, the sample size at the study domain level (economic activity at the first level (section) of ISIC4) was adjusted to a minimum acceptable number of establishments to obtain a sufficient response size for publishing accurate estimates of the indicators at the publication level. Moreover, all large establishments were included in the sample with a 100% selection probability due to their importance.
The above calculations resulted in a total sample size of 12,759 establishments, distributed as shown in the tables below.

Table1: Sample distribution at the ISIC1 (section) level. 
 

Statistical 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 Survey is collected through Computer-Assisted Telephone Interviewing (CATI), Computer-Assisted Web Interviewing (CAWI), and Computer-Assisted Personal Interviewing (CAPI).

Administrative records data collection:
In coordination with the relevant departments at GASTAT involved in implementing the survey and managing data collection, administrative data for the Short-term Business Statistics Publication is obtained from the Ministry of Municipalities and Housing and the Bankruptcy Commission (Eisar). This includes data on bankruptcy filings and issued building permits.
The data are stored in the Authority’s databases after undergoing validation and review processes in accordance with approved statistical methods and recognized quality standards. The data source is referred back to in case of detected errors or observations on the data.

Data collection frequency 

The data collection process for the Short-term Business Statistics is conducted monthly.

Reference area

The Short-term Business Statistics cover all thirteen administrative regions of Saudi Arabia.

Reference period (time reference)

Reference period of the variables or dataset is as follows:
The data for the Short-term Business Statistics for 2026 is 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., growth rates of compensation of employees).
Some results are measured in numbers (e.g., number of issued building permits).

Time coverage

The data is available from 2023 to the current month of 2026. 

Publication frequency

The results of the Short-term Business Statistics are published on a monthly basis in accordance with the approved statistical plan.

Statistical processing

Error detection

First: Survey data:
Accurate procedures are carried out to detect errors in data collected during the field survey and stored in the data lake. This is achieved by automating the data collection tool and implementing necessary constraints and procedures to control and manage the entered data, ensuring quality, accuracy, and consistency. Additionally, supportive methods are used to measure quality indicators, such as the survey response rate.
Second: Administrative records data: 
Verification and review procedures are conducted through: 

• Identifying illogical or out-of-range values.
• Classifying data to verify its accuracy, with reference to the primary data source when any errors or data quality issues are identified.
• Reviewing internal consistency among the data to ensure logical coherence.
• Comparing the data with previous data to verify its validity and initiate the data processing stage, including the extraction and review of results.

Data integration and matching from multiple sources 

Data extracted from administrative sources is used in conjunction with survey data to produce the final indicators.
The administrative data source is used directly to produce indicators related to bankruptcy filings, and issued building permits.

Imputation and calibration

Compensation (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 permitted to obtain missing data from respondents or to address cases of non-response. Subsequently, missing data and non-response are handled by applying a scientific methodology to estimate the results, taking into account several considerations, including historical data series, monthly growth rates by activity, an acceptable range of missing data, and estimates based on stratum-level data.
Formulas used:
Average compensation of employees in the establishment: Total compensation of employees in the establishment / total number of employees in the establishment
Average compensation of employees in the stratum: Sum of the average compensation of employees across all establishments in the stratum / number of establishments in the stratum
Monthly growth rate of compensation (for the target month): Compensation of employees in the previous month × growth rate of compensation in the stratum for the target month
Average revenue per employee in the establishment: Total compensation of employees in the establishment / total number of employees in the establishment
Average operating revenues in the stratum: Sum of the average operating revenues across all establishments in the stratum / number of establishments in the stratum
Monthly growth rate of revenues (for the target month): Compensation of employees in the previous month × growth rate of compensation in the stratum for the target month
Weighting:
The base sample weights are calculated based on the strata used in the sample design and allocation. The selection probability of establishment i  in stratum h is denoted by π_hi Accordingly, the weight of the selected establishment is given as follows:

Non-response weight adjustment:
Weight adjustment is applied to compensate for non-response or missing data, in order to ensure the representativeness of the sample. This adjustment is carried out after data collection and processing, once response statuses have been identified, in accordance with the following formula: 

  It represents the non-response adjusted weight in the stratum (or adjustment class)   , where the adjustment (or correction) factor for each stratum (or adjustment class)   is calculated as follows: 

Where R represents the responses and NR represents the non-responses . 

Seasonal adjustments

No seasonal adjustment methodology is applied to the Short-term Business Statistics data, as the actual values are used as they are without removing or adjusting for potential seasonal effects. 
    Adjustment of preliminary results 
Preliminary results of the Short-term Business Statistics are released and published in accordance with the specified schedule, with data for the previous three months updated when revised information or necessary corrections become available.

Used Resources

Quality dimensions

Suitability

A criterion that measures the extent to which the product meets users’ needs.

User needs 

Internal users at GASTAT of Short-term Business Statistics:

• National accounts.

Several external users significantly benefit from the data of the Short-term Business Statistics, including:

• Government entities.
• Regional and international organizations.
• Research institutions.
• Media.
• Individuals.

Key variables most utilized by external users:
 

 Completeness 

The data is complete, as comprehensive coverage of indicators has been ensured to accurately cover all targeted activities. Detailed indicators are provided according to the national classification of economic activities (ISIC4) at the first level (section), ensuring a comprehensive and complete representation of all relevant economic activities.

Accuracy and reliability 

A measure of the extent to which estimates or calculations are close to the true or exact values that reflect reality.

Overall accuracy 

• Data quality is enhanced through the selection of researchers based on a set of practical and objective criteria related to the nature of the work, as well as through their qualification and training.
• Alert, prevention, and correction rules are applied during the data collection process to the e-questionnaire of the Short-term Business Statistics Survey 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 

Timeliness: A standard that indicates the length of time between the availability of information and the occurrence of the event.
Punctuality: It reflects the time lag between the data publication date and the target date when publication actually occurs.

Timeliness 

GASTAT uses the Special Data Dissemination Standard (SDDS) issued by the International Monetary Fund. According to this standard, all statistical agencies are required to publish data on a monthly basis, with a time lag not exceeding six weeks (42 days) after the end of the reference period.

Punctuality 

The Short-term Business Statistics are published in accordance with the release dates specified in the Statistical Calendar on GASTAT’s website.
The data is available at the expected time, as scheduled in the Statistical Calendar. In case of any delay in publication, the reasons are provided.

Coherence and comparability

The ability of users to access data, the availability of detailed or aggregated data, and the availability of the Methodology and Quality Report.

Comparability - geographical

Some indicators can be compared locally at the level of administrative regions, such as the indicator of issued building permits by administrative region. Other indicators, however, are published at the level of Saudi Arabia as a whole, without geographical disaggregation. In addition, the indicators can be compared across countries at the first level (section) of ISIC4.

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 is consistent, as consistency is verified across different classification levels in accordance with ISIC4. In addition, the consistency of data classified at the second level (Wholesale and Retail Trade Statistics Survey) is checked against the detailed data available at the first level (Short-term Business Statistics Survey). These procedures contribute to ensuring integration and coherence across classification levels, thereby enhancing the reliability of the data and the quality of the analysis based on it and ensuring that the results are free from inconsistencies.

Coherence- Sub-annual and annual statistics 

Not applicable, as the Short-term Business Statistics Survey is conducted on a monthly basis only.

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 exhibit full internal consistency.

Accessibility and clarity

It refers to users’ access to data, the availability of detailed and aggregate data, as well as the availability of the 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: 
Press releases

Publications

GASTAT issues the Short-term Business Statistics publication regularly within a pre-prepared dissemination plan, and it is published on GASTAT’s website. The Authority is keen to disseminate its results in a manner that serves all types of users, including publications in various formats that contain dissemination tables and charts for data and indicators, the Methodology and Quality Report, and the questionnaires used, in both Arabic and English.
The results of the Short-term Business Statistics are available at:
https://www.stats.gov.sa/statistics 

Online database

Not available.

Microdata accessibility

Microdata refers to detailed data at the unit level, obtained from multiple sources such as sample surveys, the General Population and Housing Census, and administrative systems. It provides detailed information on the characteristics of individuals, households, business entities, and geographical areas, supporting the development of statistical indicators and scientific research.
Different types of microdata files are available to meet diverse 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 by 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 were established based on a specific methodology requested by the data requester to extract the datasets with specific characteristics used for strategic studies and decision-making, as well as 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 confidentiality protection standards and procedures can access scientific-use files of microdata through the “Etaha” platform of GASTAT, while more sensitive data is made available through visits to the Microdata Lab within a secure environment managed by GASTAT.

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:
  https://unstats.un.org/unsd/nationalaccount/sna2008.asp

Quality assurance

GASTAT ensures that the following principles are taken into account: 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 carries out all statistical activities in accordance with the National Model (Generic Statistical Business Process Model – GSBPM). During the comprehensive evaluation stage, which is the final stage of GSBPM, information collected across all stages and sub-processes is used to prepare an evaluation report that summarizes all challenges related to the quality of each statistical process and serves as an input for improvement and development processes.

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 is presented in appropriate tables to facilitate summarization, understanding, the derivation of results, and comparison with other data, enabling the extraction of statistical insights about the study population. It also facilitates easy reference through tables without the need to review the original questionnaires, which often contain certain data such as 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 in such a way that the respondent cannot be identified either directly, such as by (Names, addresses, contact numbers, or identification numbers. etc.) or indirectly by combining different - especially rare - characteristics of respondents, such as 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; therefore, it provides them with the results of the Short-term Business Statistics Publication immediately upon release.
Customer questions and inquiries regarding the publication and its results are also received through various communication channels, such as:

• GASTAT official website:  www.stats.gov.sa
• GASTAT official email 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).