Methodology and Quality Update

Latest Update on Methodology and Quality

2025/07/21

Statistical Presentation

Data description

The Construction and Real Estate Activities Statistics publication is a primary source of economic indicators related to the construction and real estate sectors. It provides detailed indicators including operating revenues, operating expenditures, and compensation of employees, in addition to a number of other economic indicators. 
The Construction and Real Estate Activities Statistics are among the most prominent economic statistics that provide comprehensive insights into the structure of these activities in the Kingdom.
The construction and real estate activities survey is conducted to collect data on the main characteristics as follows:

• Economic activities practiced in establishments.
• Revenues and operating expenditures of the establishments.
• The number of employees and their compensation within the establishments.

The data is also used to provide the following economic indicators:

• Operating revenues.
• Operational expenditures.
• Employees ' compensation.
• Operating Surplus.

Classifications

The following classifications are applied in the Construction and Real Estate Activities 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.
Saudi classification of products and services – based on the Central Product Classification (CPC2.1): 
The Saudi classification of products and services – based on the Central Product Classification (CPC 2.1) issued by the United Nations Statistical Commission in 2018 – is a recognized standard for the collection and classification of products, including goods and services. This classification is used in areas such as industrial production, national accounts, international trade, and the balance of payments to support statistical standardization and facilitate comparisons.
Classifications are available on the GASTAT website:  www.stats.gov.sa

Statistical concepts and definitions

Terminologies and concepts for the Construction and Real Estate Activities Statistics:

• Establishment:

It is an economic unit with a legal entity (having a commercial register) engaged in a specific economic activity owned by an individual, a group of individuals, a company, a semi-governmental sector, or an institution.

• Main economic activity:

The main economic activity of an establishment is defined as the set of operations or services carried out by the establishment to generate income. In some cases, these activities may not result in direct financial returns, such as in charitable organizations that rely on donations. If an establishment engages in more than one economic activity, the activity that generates the highest revenue is considered the main economic activity. The classification of economic activity for establishments is based on the International Standard Industrial Classification (ISIC.4). 

• Operating revenues:

All cash revenues achieved by the establishment as a result of practicing its main economic activity or other secondary activities such as: Sale of products, provision of services, and merchandise trade. It also includes daily operating revenues, total sales, as well as revenues not related to the main activity, such as services provided to others, sale of production residues, leasing of buildings and equipment, and any other operating income.

• Operating expenditures

It is the value of goods and services actually used by the establishment during its financial year as a result of conducting its economic activity, whether purchased during the same year or withdrawn from stock from previous years.

• Compensation of Employees:

Total remuneration, in cash or kind, payable by an employer to an employee in return for work performed by the employee during an accounting period. Compensation for employees includes wages, salaries, in-kind benefits, and social contributions before any deductions, such as social insurance contributions, taxes, and similar items.

Data sources

The Construction and Real Estate Activities Statistics rely on two main data sources.
First source:
The first data source for construction and real estate activities is the construction and real estate activities survey.
 The main published indicators for construction and real estate activities from the survey source are:

• Operating revenues.
• Operational expenditures.
• Employees ' compensation.
• Operating Surplus.

Second source: 
The second data source for construction and real estate activities is administrative records.

• Ministry of Municipalities and Housing.

The main published variables from the administrative data source are:

• Building Permit Indicators.

Designing the data collection tool

The comprehensive economic survey form — covering construction and real estate activities — was carefully designed to avoid unnecessary details that could negatively affect data quality and response rates. The focus was placed on key elements to ensure the collection of accurate and relevant data directly related to the survey’s objectives, including essential items such as operating revenues, operating expenditures, number of employees, and the compensation paid to them.
The questionnaire also included a dedicated section for collecting key variables related to construction and real estate activities, specifically concerning data on construction projects.
The questionnaire was designed in a modern electronic format, incorporating a set of business rules to verify the logical consistency of the entered data, thereby ensuring its accuracy and integrity, and enhancing the reliability of the resulting outputs.

Questionnaire test (cognitive test)

The outputs of the cognitive test were based on the previous survey year 2022, and there was no need to repeat the implementation of the test for this year.

Statistical population

The statistical population for the comprehensive economic survey consists of all establishments engaged in economic activities in the Kingdom of Saudi Arabia within the 2023 business frame. This frame serves as the list containing all units of the target population for this survey and other economic surveys conducted by the General Authority for Statistics, including the construction and real estate activities survey. 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 to construct various economic samples. The sampling frame is considered a list of all establishments meeting the survey conditions specified by the owning administration.

Sample Design

The sample was designed with a two-stage stratified 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. In order to obtain more accurate results compared to a simple random sample of the same size, and to provide a sufficient number of establishments at publishable levels, the stratification was applied across three levels as follows:  

• Stratification at the fourth-level classification of economic activity (ISIC4).
• Stratification at the level of administrative regions.
• 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 study domain level (economic activity at the fourth-level of the International Standard Industrial Classification of All Economic Activities, ISIC4), with the sample size determined for each stratum h (study domain).
Parameters used in estimating the sample size

• Total number of establishments from the frame at the fourth level of ISIC4.
• The arithmetic mean and variance at the fourth level of ISIC4 for the indicator of the total number of employees (based on data from the previous survey cycle)  .
• The design effect at the fourth level of ISIC4 for the indicator of the total number of employees (based on data from the previous survey cycle). 
• The response rate at the fourth level of ISIC4 is based on data from the previous survey cycle. With the specification of an assumed acceptable minimum threshold, as the survey will be conducted using a hybrid approach combining telephone and field data collection.
• Allowed relative margin of error.
• A confidence level was used in estimating the total number of establishments\ (1-\alpha)=0.95.

The sample size for each study domain at the fourth level of ISIC4 was determined using the following equation:

Whereas:

The output from calculating the sample size for each study domain at the fourth level of ISIC4 was allocated to establishment size categories and then to administrative regions using the Probability Proportional to Size (PPS) allocation method. This allocation method reduces the variance in weighting factors, thereby decreasing the variance in estimates, and increasing the design efficiency. Additionally, an acceptable minimum sample size threshold was set at the study domain level of the fourth level of ISIC4 to ensure a sufficient number of observations for publishing accurate indicator estimates at the dissemination level. Moreover, all medium and large establishments were included in the sample with a 100% probability due to their importance.
The calculations mentioned above produced a total survey sample size of 96,677 establishments, distributed as shown in the tables below. The sample size for construction and real estate activities reached 18,197 establishments.

Table1: Survey sample distribution at the division level:

Statistical unit (sampling unit)

The statistical unit in the Construction and Real Estate Activities Statistics is the establishment.

Data collection

Data for construction and real estate activities are collected through:

• Computer-assisted Interview (CAPI).
• Computer-assisted telephone Interviews (CATI). 
• Online computer-assisted Interviews (CAWI). 

Data collection from administrative records:
In coordination with the relevant departments of the authority responsible for survey implementation and data collection management, the administrative data for the Construction and Real Estate Activities Statistics Publication are obtained and stored in the authority’s databases. This occurs after verification and review processes using approved statistical methods and recognized quality standards, with reference back to the data source in case errors are detected or observations on the data arise.

Data collection frequency 

Annual.

Reference area

The Construction and Real Estate Activities Statistics covers all (13) administrative regions of the Kingdom of Saudi Arabia (Riyadh, Makkah, Al-Madinah, Qassim, Eastern, Asir, Tabuk, Hail, Northern Borders, Jazan, Najran, Al-Baha, and Al-Jouf).

Reference period (time reference)

References period to the variables or dataset as following:
The data for construction and real estate activities is collected during the specified period by contacting establishments within the targeted survey sample and completing the survey form. Survey data is usually attributed to the fiscal year preceding the data collection period.

Base period

Not applicable.

Measurement unit

• Most results are measured in thousands of riyals (such as: Operating revenues, operating expenditures, employee compensation, and operating surplus).
• Some indicators are measured by numbers (such as: Number of building permits by administrative regions.
• Some results are measured as a percentage (such as: The percentage distribution of building permits by type of building permit).

Time coverage

The results are available for the years 2021 to 2023.

Publication frequency

Annual.

Statistical processing

Error detection

Data is reviewed and matched to ensure their accuracy and precision in a way that suits their nature to give the presented statistics quality and accuracy. An example of this is the use of the IQR methodology (Interquartile Range), which is a widely applied and globally practiced method for identifying outliers.
The calculation is done:

• First quartile (Q1 / 25%): The median of the lower half of the dataset.
• Third quartile (Q3 / 75%): The median of the upper half of the dataset.

The interquartile range measures the spread of the middle 50% of the data to highlight values that are significantly different from the central tendency of the dataset.
The boundaries for outliers are determined as follows:

• Lower Bound: First quartile - 1.5 * Interquartile range (IQR).
• Upper Bound: Third quartile + 1.5 * Interquartile range (IQR).

Variables are identified as outliers if:

• The variable is below the lower bound.
• The variable is above the upper bound.

After identifying outliers, the Business, Investment, and International Trade Statistics team analyzes and evaluates the outliers in the averages by comparing the mean and median across specific data set characteristics, using appropriate statistical measures and critical assessment of the outliers.
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 Business, Investment, and International Trade Statistics Department through modern technologies and software designed for this purpose.

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 building permits.

Imputation and calibration

Imputation (for non-response cases or incomplete datasets): 
The approach used for Imputation in Construction and Real Estate Activities Statistics, whether for establishments with incomplete responses or missing data for specific variables. Reinterviews are allowed to obtain missing respondent data or to address cases of non-response. Missing or non-response data are then addressed by evaluating them according to a scientific methodology to estimate the results, based on several considerations including historical data series, an acceptable range of missing data, and estimates derived from class-level data.

Seasonal adjustments

Not applicable.

Adjustment of preliminary results 

Not applicable.

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 Construction and Real Estate Activities results:

• National accounts.

External users and beneficiaries of the Construction and Real Estate Activities results:

• Government entities.
• Regional and international organizations.
• Research institutions.
• private sector

The disseminated key variables 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) 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, 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 on the electronic questionnaire for health and safety at work statistics 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 

The General Authority for Statistics is committed to applying the approved international standards for publishing statistics, including the timeliness standard issued by the European Statistical System. It announces and clarifies the publication dates of statistics through its official website via the statistical calendar. The authority adheres to the announced schedules, and in case of any delay, updates will be provided accordingly.

Punctuality 

Publication takes place in accordance with published release dates for the Construction and Real Estate Activities in 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

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

The data can be compared locally at the level of administrative regions for some indicators, such as the indicator (number of building permits by administrative regions). Other indicators are issued at an aggregate level without geographic breakdown by regions.

Comparability - over time 

The annual results for 2023 have been released. To ensure continuity of the time series and meet user needs, estimates for previous periods (2021–2022) were produced using the backcasting method.

Coherence- Cross domain

The data is consistent, as consistency was verified across different classification levels according to ISIC4. The data classified at the second level (Comprehensive Economic Survey) was checked against detailed data available at the fourth level (Construction and Real Estate Activities Statistics). These procedures help ensure integration and coherence between classification levels, enhancing the reliability of the data and the quality of the analyses based on it, while ensuring the results are free from 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 Construction and Real Estate Activities 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 publishes the Construction and Real Estate Activities reports and publications on its official website. GASTAT is keen to publish its results in a way that serves all types of users, including releases in various formats that contain publication tables, data graphs, indicators, metadata, methodology, and questionnaires, all available in both English and Arabic.
The results of the Construction and Real Estate Activities are available at:
https://www.stats.gov.sa/statistics

On-line database

Not available.

Microdata accessibility

Not available.

References and standards

The Construction and Real Estate Activities Statistics are based on the following international standards:

• European Statistical System quality and metadata handbook, European Union Statistical Office: https://ec.europa.eu/eurostat/web/european-statistical-system/news
• System of National Accounts 2008: https://www.stats.gov.sa/ar/1467
• United Nations Statistics Division UNSD: https://unstats.un.org/UNSDWebsite
• International recommendations on construction statistics, United Nations:  SeriesM_47rev1E.pdf  

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 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: ‌(name, address, contact number, identity number etc.) or indirectly (by combining different - especially rare - characteristics of respondents) such as: (age, occupation, education etc.).

Dissemination policy

Statistical calendar

The Construction and Real Estate Activities 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 Construction and Real Estate Activities 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).