Methodology and Quality Update

Latest Update on Methodology and Quality

03/12/2025

Statistical Presentation

Data description

The Wholesale and Retail Trade Statistics provide data on the short-term performance of the wholesale and retail trade sector in the Kingdom of Saudi Arabia.
The Wholesale and Retail Trade Statistics is a survey conducted to collect data on the main characteristics as follows:
•    Compensation of Employees
•    Operating revenues
•    E-commerce sales
Data is also used to estimates:
•    Compensation of Employees Index and Growth Rates
•    Operating Revenues Index and Growth Rates
•    E-commerce Sales Index and Growth Rates 

Classifications

The following classification is applied in the Wholesale and Retail Trade 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 the Wholesale and Retail Trade 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).
•    Compensations of Employees:
All amounts due periodically by the establishment to its employees during the quarter, including wages and salaries for regular working hours, as well as fixed allowances, in addition to all types of benefits and allowances, such as housing and social insurance.
•    Operating revenues:
It includes the sales of goods purchased for the purpose of resale in the same condition for which a purchase value has been recorded, whether the sales relate to the main activity (wholesale or retail trade) or secondary wholesale or retail activities. It also includes the cash revenues generated from carrying out motor vehicle maintenance and repair activities, as well as other secondary activities performed by the establishment.
•    E-commerce sales:
It includes the value of sales made through the internet, whether via the establishment’s website or application, or through an intermediary.

Data sources

 The main source of data for the Wholesale and Retail Trade Statistics is the Short-Term Business Statistics Survey. 
The main variables targeted for dissemination in the Wholesale and Retail Trade Statistics are:
•    Compensation of Employees
•    Operating revenues
•    E-commerce sales

Designing the data collection tool

The Wholesale and Retail Trade Statistics rely on the Short-Term Business Statistics questionnaire, which was carefully designed to avoid unnecessary details that may negatively affect data quality and response rates. The form focuses on key items that mainly cover the number of employees, their compensation, operating revenues, and e-commerce sales.
Operational rules (including alert rules, error rules, and navigation rules) were also incorporated to control the logical consistency of the data and ensure its accuracy and integrity.
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.
Indicators of the survey:
•    Index = (Value of the Quarter/ Average value of the base year).
•    Quarterly Growth Rate = ((Current Quarter value – Previous Quarter value) / Previous Quarter value).
Wholesale and Retail Trade Statistics Survey Questionnaire:
Survey questionnaire

Questionnaire test (cognitive test)

The outputs of the cognitive test conducted in 2022 were adopted for the Wholesale and Retail Trade Statistics Survey and the Short-Term Business Statistics Survey.

Statistical population

The statistical population of the Wholesale and Retail Trade Statistics Survey consists of all economic establishments engaged in wholesale trade, retail trade, and the maintenance and repair of motor vehicles, and classified as commercial entities through operating licenses issued by the relevant government authorities in the Kingdom of Saudi Arabia.

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. 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 level (division) 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 level (division) 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 (1-α)=0.95.
The sample size for each study domain at the fourth 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).
•     : 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 level (section) of the International Standard Industrial Classification of Economic Activities (ISIC4):

Statistical unit (sampling unit)

The statistical unit in Wholesale and Retail Trade Statistics is an establishment engaged in economic activities.

Data collection

Data collection from the survey:
The data of the Wholesale and Retail Trade Statistics is collected based on the Short-Term Business Statistics through Computer-Assisted Telephone Interviews (CATI), Computer-Assisted Web Interviews (CAWI), or Computer-Assisted Personal Interviews (CAPI).

Data collection frequency 

The data collection process for the Wholesale and Retail Trade Statistics is carried out on a quarterly basis.

Reference area

The Wholesale and Retail Trade Statistics cover all thirteen administrative regions in the Kingdom of Saudi Arabia.

Reference period (time reference)

References period to the variables or dataset as follows:
The data of the Wholesale and Retail Trade Statistics is based on the quarter preceding the data collection period.

Base period

The base year used is 2023.

Measurement unit

Some indicators are calculated as rates (e.g., Compensation of employees' index and growth rate).

Time coverage

The data is available from 2023 to the first quarter of 2025.

Publication frequency

The results of the Wholesale and Retail Trade Statistics are disseminated quarterly in accordance with the approved statistical plan.

Statistical processing

Error detection

During the data collection process, a critical stage begins to ensure data quality, which involves applying alert, blocking, and correction rules, as well as reviewing the consistency and accuracy of the data. This stage aims to verify that the collected data is reliable and free from errors or outliers before proceeding with statistical processing and producing the final results.

Data integration and matching from multiple sources 

All data is regularly entered into the data collection system upon receipt. The specialized team ensures that the data is entered correctly and accurately. The data is verified for completeness and reviewed to ensure that it has been correctly incorporated into the system.

Imputation and calibration

Compensation (for non-response cases or incomplete datasets): 
The approach used for imputation in the Wholesale and Retail Trade 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

It refers to the estimation and removal of seasonal effects from data, ensuring that the data are free from seasonal influences arising from climatic conditions, social customs, and calendar-related events such as Eid al-Fitr, Eid al-Adha, National Day, Founding Day, and variations in weekend structures. The data are updated annually in December to minimize seasonal effects.

Adjustment of preliminary results 

The initially calculated statistical outputs were reviewed and updated after processing to correct identified errors or improve accuracy based on internal reviews. The updated data is within 90 days of the release of the preliminary data, and any differences between the preliminary and final results are documented for users.

Used Resources

Quality dimensions

Suitability

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

User needs 

Internal users at GASTAT of the Wholesale and Retail Trade Statistics data:
•    National accounts.
Several external users and beneficiaries benefit from the Wholesale and Retail Trade Statistics, including:
•    Government entities.
•    Regional and international organizations.
•    Research institutions.
•    Media.
•    Individuals.
Key variables that are mostly used by external users:

Completeness 

The data is complete, with comprehensive coverage of indicators that accurately encompass all targeted activities. Detailed indicators are provided according to the national classification of economic activities (ISIC4) up to the fourth 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 who have been selected according to a set of practical and objective criteria and a 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 education and training survey to improve data quality.
•    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.
•    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 quarterly basis, with a delay of not more than mid-year (90 days) after the end of the reference period. If the data are from different sources, they may be published at a different frequency.

Punctuality 

Publication takes place in accordance with the published release dates for the Wholesale and Retail Trade Statistics on the GASTAT webpage.
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

A standard that refers to the necessity of internal and temporal consistency of statistics, their logical coherence, and their comparability and integration across different regions and sources.

Comparability - geographical

The data are comparable both nationally and internationally.

Comparability - over time 

The survey was first launched in 2016 as an annual survey. It was then suspended for development purposes, and data collection resumed after the transformation in 2023:
•      2018-2019
The survey period was then changed to a quarterly basis before it was suspended.
•    Q1 of 2023:
Data collection resumed after the transformation and integration with the Short-Term Business Statistics Survey, including the questionnaire, sample, and data collection process.

Coherence- Cross domain

The data is consistent, as data consistency was verified across the different classification levels in accordance with ISIC4. It was ensured that the data classified at the first level (Short-Term Business Statistics Survey) is aligned with the detailed data available at the second level (Wholesale and Retail Trade Statistics Survey). These procedures help ensure integration and coherence across classification levels, thereby enhancing the reliability of the data and the quality of the resulting analysis, while ensuring that the results are free from inconsistencies.

Coherence- Sub-annual and annual statistics 

Not applicable, as wholesale and retail trade statistics are published only on a quarterly basis.

Coherence- National Accounts 

The data is consistent, as the survey data is used to estimate the Gross Domestic Product (GDP) for the national accounts.

Coherence- Internal 

The estimates of the Wholesale and Retail Trade Statistics for the reference period are fully internally consistent, as they are all based on the same accurate dataset and 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 10.1. The press releases can be viewed on the website of GASTAT at the link:
https://stats.gov.sa/news

Publications

GASTAT issues the Wholesale and Retail Trade Statistics publications and reports regularly in accordance with a pre-approved dissemination plan, and they are published on the Authority’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 Wholesale and Retail Trade Statistics are available on:
Wholesale and Retail Trade Statistics

Online database

The data is published on the statistical database:
Statistical database

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.
Different types of microdata files 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 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

•    European Short-Term Business Statistics Methodological Guide (2021 Edition):
The methodological manual of European short-term business statistics​​​​​​​
•    System of National Accounts 2008:
National Accounts System

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 from the SME survey are presented in the right tables in order to summarise and 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 the 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: (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 Wholesale and Retail Trade 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 Wholesale and Retail Trade 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 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).