Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
National Statistics Office, Lascaris, Valletta, Malta VLT 2000
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
31 October 2025
2.2. Metadata last posted
31 October 2025
2.3. Metadata last update
31 October 2025
3.1. Data description
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) refer to statistics describing the activity of foreign affiliates resident in the compiling country.
In country-level business statistics, a foreign-controlled enterprise shall mean an enterprise resident in the compiling country over which an ultimate controlling institutional unit not resident in the compiling country has control.(Table 14 of the EBS Implementing Regulation (EU) 2020/1197).
Variables on the country-level business activities in the IFATS data category:
Business activities in foreign control:
210301. Number of foreign-controlled enterprises
220501. Number of employees and self-employed persons in foreign-controlled enterprises
220701. Employee benefits expense in foreign-controlled enterprises
230301. Intramural R & D expenditure in foreign-controlled enterprises
230401. R & D personnel in foreign-controlled enterprises
240301. Total purchases of goods and services of foreign-controlled enterprises
240302. Purchases of goods and services for resale of foreign-controlled enterprises
250601. Net turnover of foreign-controlled enterprises
250701. Value of output of foreign-controlled enterprises
260201. Foreign-controlled enterprises’ gross investment in tangible non-current assets
250801. Value added of foreign-controlled enterprises
Business activities in total economy:
210101. Number of active enterprises
220101. Number of employees and self-employed persons
220301. Employee benefits expense
230101. Intramural R & D expenditure
230201. R & D personnel
240101. Total purchases of goods and services
240102. Purchases of goods and services for resale
250101. Net turnover
250301. Value of output
250401. Value added
260101. Gross investment in tangible non-current assets
Research and Development (R&D) variables are disseminated every odd year, Malta is exempt from the collection of this information under the 1% exemption rule.
3.2. Classification system
Classification systems used in the FATS are as follows:
Statistical classification of economic activities in the European Community (NACE Rev. 2) is used from 2008 onwards;
Starting from reference year 2021, all variables (excluding R&D variables) cover NACE Rev.2 Sections B to N, P to R and Divisions S95 and S96.
3.4. Statistical concepts and definitions
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) refer to statistics describing the activity of foreign affiliates resident in the compiling country.
In country-level business statistics foreign-controlled enterprise shall mean an enterprise resident in the compiling country over which an ultimate controlling institutional unit not resident in the compiling country has control.(Table 14 of the Implementing Regulation (EU) 2020/1197).
Foreign affiliate in the framework of inward FATS is an enterprise resident in one country which is under the control of an institutional unit resident in another country.
Domestic affiliate refers to an enterprise resident in the compiling country over which a UCI resident in the same compiling country has control.
Ultimate Controlling Institutional unit of a foreign affiliate (UCI) refers to the institutional unit, proceeding up a foreign affiliate’s chain of control, which is not controlled by another institutional unit.
Control is the ability to determine the general policy of the affiliate by choosing appropriate directors, if necessary. In this context, enterprise A is deemed to be controlled by an institutional unit B when B controls, whether directly or indirectly, more than half of the shareholders' voting power or more than half of the shares.
Indirect control means that an institutional unit may have control through another affiliate which has control over enterprise A.
Active enterprise is a statistical unit which at any time during the reference period was classified as an ‘enterprise’, as defined in Regulation (EEC) No 696/93, and also active during the same reference period. A statistical unit is considered to have been active during the reference period if, in said period, it either realised positive net turnover, produced outputs, had employees or spent on investments.
Employees and self-employed persons are persons who work for an observation unit on the basis of a contract of employment and receives compensation in the form of wages, salaries, fees, gratuities, piecework pay or remuneration in kind; and persons who are the sole owners or joint owners of the statistical unit in which they work. Family workers and outworkers, whose income is a function of the value of the outputs of the statistical unit, are also included.
Employee benefits expense contains all expenses arising in relation with employee benefits, recognised by the statistical unit during the reference period. These refer to all forms of consideration given by the statistical unit in exchange for service rendered by employees or for the termination of employment.
Research and experimental development (R & D) comprises creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind, culture and society – and to devise new applications of available knowledge. Expenditures on intramural R & D represent the amount of money spent on R & D that is performed within a reporting unit. Intramural R & D expenditures are all current expenditures plus gross fixed capital expenditures for R & D performed within a statistical unit during a specific reference period whatever the source of funds. R & D current expenditures include labour costs for internal R & D personnel and other current costs (costs for external R & D personnel, purchase of services.). Gross fixed capital expenditures for R & D include: acquisition of land, acquisition of buildings, acquisition of information and communication equipment, acquisition of transport equipment, acquisition of other machinery and equipment, acquisition of capitalised computer software, acquisition of other intellectual property products.
R & D personnel in a statistical unit include all persons engaged directly in R & D, whether employed by the statistical unit or external contributors fully integrated into the statistical unit’s R & D activities, as well as those providing direct services for the R & D activities (such as R & D managers, administrators, technicians and clerical staff).
Total purchases of goods and services contains all amount of goods and services purchased by the statistical unit, recognised in accounting as either current assets or expenses during the reference period.
Purchases of goods and services for resale are purchases of goods for resale to third parties without further processing. It also includes purchases of services by ‘invoicing’ service companies, i.e. those whose turnover is composed not only of agency fees charged on a service transaction (as in the case of estate agents) but also the actual amount involved in the service transaction, e.g. transport purchases by travel agents.
Net turnover consists of all income arising during the reference period in the course of ordinary activities of the statistical unit, and is presented net of all price reductions, discounts and rebates granted by it.
Value of output represents the value of the total output of the statistical unit, generated during the reference period.
Value added represents the value a business adds through its production process. It reflects the net contribution of a business to the economy and is equivalent to the combined Gross operating surplus and Employee benefits expense.
Gross investment in tangible non-current assets includes all additions to tangible non-current assets, recognised as such by the statistical unit during the reference period, except any increases from revaluations or reversals of previously recognised impairment losses and from reclassifications (transfers) of other tangible non-current assets.
A Special Purpose Entity (SPE) in a country is a registered entity with very few or no employees, limited physical presence and negligible physical production in the host economy. SPEs are owned or controlled by non-resident entities. Data from Structural Business Statistics (SBS) do not include SPEs. Consequently, when compiling Inward FATS (IFATS), SPEs are similarly excluded.
When an enterprise is jointly controlled by multiple entities, the dominant country is identified by summing the shares from the shareholders resident in that country. If the respective country has a share ownership rate of over 50%, it is tagged as the UCI. If the share of ownership across more than one country is equal, the information on the residency of the executive directors and public data are used to help determine the UCI. If the UCI country is unable to be determined, the UCI is coded Z12 for shared control within the EU, and D09 for shared control outside the EU.
The ownership of shareholders is analysed to see if a collective group from one country holds 50% or more of the shares. If no dominant group from a single country is identified, control is then determined using publicly available data.
3.5. Statistical unit
Until the reference year 2020, IFATS data were reported at legal unit level. Starting from reference year 2021, IFATS data are being reported at the enterprise statistical unit level.
The statistical unit of FATS is the enterprise as defined in line with the Regulation (EEC) No 696/93 on the statistical units for the observation and analysis of the production system in the Community.
3.6. Statistical population
All variables except R&D variables, cover NACE Rev.2 Sections B to N, P to R and Divisions S95 and S96.
The statistical population is equivalent to the SBS population, consisting of all operational business and branches while excluding companies registered in Malta whose production activities are carried out entirely abroad.
Starting from reference year 2021, there are no cut-off thresholds being applied. This mirrors the same policy adopted in the SBS.
3.7. Reference area
IFATS data cover the active resident enterprises within the geographical boundaries of the Maltese islands.
3.8. Coverage - Time
IFATS data cover years 2009 through 2023.
Starting from reference year 2016, Malta implemented a new processing methodology for IFATS. This included the eliminations of additional cut-off thresholds to ensure alignment with SBS aggregates. Starting from reference year 2021, as SBS removed the €7,000 turnover threshold, IFATS simultaneously adjusted accordingly. Alongside this modification, the EBS regulation was introduced and the 'Enterprise' Statistical Unit was adopted. As a result, both SBS and IFATS now include all active enterprises.
3.9. Base period
Not applicable
The number of enterprises and employment variables are recorded in units.
Monetary data for enterprises are recorded in thousands of Euros.
2023
6.1. Institutional Mandate - legal acts and other agreements
Confidentiality is one of the major principles guiding the activities of the NSO.
Article 40 of the MSA Act stipulates the restrictions on the use of information while and in the Article 41,stipulated the prohibition of disclosure of information. Further, Section IX of the Act (Offences and Penalties) lays down the measures to be taken in case of unlawful exercise of any officer of statistics regarding confidentiality of data. No cases of breaches in the law have been recorded to date.
Since its inception, the NSO has been committed to ensure the confidentiality of all collected data, using it solely for statistical purposes in accordance with established laws. The identity of data providers is protected, and any data that could lead to the identification of individuals or entities is not shared with third parties. .
All NSO employees, upon joining, are made aware of confidentiality rules and requirements. As stipulated by the MSA Act, each staff member takes an oath of secrecy before starting their work.
The NSO has an internal policy concerning anonymisation and pseudo-anonymisation. This policy ensures that the data the office collects and shares is protected. It offers guidelines to NSO staff on applying appropriate data protection methods. This policy covers all data, irrespective of its format, managed by the NSO.
At European level:
Regulation (EC) No 223/2009 of the European Parliament and of the Council European statistics (recital 24 and Article 20(4) of 11 March 2009 (OJ L 87, p.164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
Please see Table 7.2 in the Annex at the bottom.
Primary confidentiality is applied to prevent the disclosure of sensitive business information. It is flagged in two main cases:
`Too few enterprises', - when the number of business units is less than ;
Dominance (p% rule) – when the contribution of a single enterprise is large enough that the value of another enterprise can be estimated within 10% accuracy (p=10).
Secondary confidentiality is applied to protect data that have been flagged as primary confidential. Additional cells are suppressed to ensure that the values flagged as primary confidential cannot be derived from other published data.
Starting from reference year 2021, the NSO introduced a new policy to reduce the use of confidential flags. Suppression is not applied to core variables of companies when the same data is publicly accessible through audited financial statements.
Furthermore, variables relating to the number of employees and number of enterprises are considered non-confidential, as these figures are already disseminated through other public sources.
The NSO publishes and disseminates news releases as 1100 hrs as scheduled in the ‘Upcoming News Release’ calendar. The calendar is available on the NSO website and provides a three-month outlook, ( covering the current month and the next two months). This calendar is sometimes subject to changes.
8.2. Release calendar access
The News release calendar can be accessed through the following link: News release calendar.
8.3. Release policy - user access
In line with the Community legal framework and the European Statistics Code of Practice, the NSO disseminates national IFATS statistics objectively, professionally and transparently.
An internal dissemination policy is in place to ensure that official statistics are released in an impartial, independent and timely manner, and made available simultaneously to all users.
The NSO's primary channel for the dissemination of official statistics is the NSO website. Tailored requests for statistical information may also be submitted through the NSO website.
Annually at T+20 for all variables, except for R&D variables which are disseminated every odd year.
Work processes and procedures for the compilation of IFATS are documented in a standardised reporting template and aligned to the General Statistics Business Process Model (GSBPM). The model covers all phases of the statistical production process, from the initial stages of identifying the required statistics and scope of the survey, to the final stages of dissemination and evaluation.
The GSBPM ensures that the compilation of IFATS is conducted in a structured and coherent manner. It supports standardised documentation, facilitates the integration of data and metadata, and provides a framework for maintaining and improving data quality throughout all stages of statistical production, including data cleaning, validation, and preparation for analysis. The GSBPM report is available and may be accessed by all NSO employees.
The 2023 Edition of the European Business Statistics Compilers Manual for Foreign Affiliates Statistics provides important guidelines for the changeover to the EBS regulation starting from the reference year 2021.
10.6.1. Metadata completeness - rate
Information about all required metadata concepts (and sub-concepts thereof) are provided.
10.6.2. Availability of statistical metadata
The Single Integrated Metadata Structure (SIMS) for IFATS is available electronically on the NSO website.
10.6.3. Web links if metadata are published electronically
The metadata can be found in the following link: Metadata
10.7. Quality management - documentation
Concepts related to metadata and quality are available on NSO Metadata. For each reference year, in compliance with Eurostat's requirements, a quality report on IFATS is transmitted through the ESS Metadata Handler two months of the deadline.
In alignment with the ESS Code of Practice (ESS CoP) standards, The NSO established a comprehensive internal Quality Management Framework (QMF). This framework is supported by a document detailing general quality guidelines that apply across all statistical domains. While ensuring methodological soundness remains an integral part of the QMF, the document also addresses various institutional aspects.
11.1. Quality assurance
Since IFATS data is correspond to SBS values, all quality control measures applied to complete SBS data are also reflected in the IFATS results. Additional quality assurance specific to IFATS includes the comparison and assessment of changes in the UCI of individual enterprises by the IFATS coordinator. Additional quality assurance measures include the distribution analysis of key variables by continent, along with the documentation of explanations for any significant changes.
Final data is processed using the inbuilt data validation tool - Input Hall to validate the accuracy of the information provided and to ensure that it has been compiled in accordance with the specified requirements.
Every five to seven years, the NSO participates in a Peer Review exercise, during which an expert assesses the compliance of its operations with principles of the ESS CoP. Peer Reviews are part of the European Statistical System (ESS) strategy to implement the ESS CoP. Each NSI is expected to provide information as requested by a standard self-assessment questionnaire. Following this an expert team visits the office to meet NSI representatives and main stakeholders. Peer reviews result in a compliance report and a list of recommended improvements and actions which need to be followed up by the NSI. The most recent Peer Reviews was carried out in 2022.
11.2. Quality management - assessment
Work processes for the compilation of IFATS follow the procedures documented in the GSBPM. The IFATS coordinator monitors and verifies shifts in UCIs from one year to the next, using information from other available sources. Significant changes in variables per continent is compared to previous years are also reviewed to ensure that increases or decreases in values are accurate and valid. In addition, it is ensured that the UCI 2-digit country codes follow the ISO 3166-1 classification.
12.1. Relevance - User Needs
The main users of IFATS include the European Commission, Eurostat, internal and local organisations, ministries, the chamber of commerce, trade unions, journalists, researchers and students who are interested in the control patterns of the Maltese Economy.
12.2. Relevance - User Satisfaction
The last User Satisfaction Survey, held in 2022, aimed to collect information about key users' satisfaction with the statistical output.
The NSO maintains records on the number of News Releases and publications disseminated through its website, the users receiving statistical products, as well as the number of requests that are processed every year.
News Releases and tailor-made statistical outputs were assessed in terms of quality, timeliness, and on their ability to meet users' needs.
12.3. Completeness
Under the new regulation, the IFATS data mandate aligns with the SBS domain in terms of characteristics, geographical coverage and activity breakdown. R&D data is not available for Malta due to their exemption based on the 1% exemption rule where the R&D variables are less than 1% of the European Community total.
12.3.1. Data completeness - rate
Please see Table 12.3.1 in the Annex at the bottom.
Accuracy is based on local administrative data on ownership, ordinary shares, Ultimate Beneficial Owners (UBO), and executive directors complemented by, the EuroGroups Register,audited financial statements and data from previous years. Each year, individual profiles are carried out covering at least up to the 60th cumulative percentile for the total Value Added, Net Turnover, and Persons Employed, and at least up to the 80th cumulative percentile for the total Gross Investments in Tangible Non-Current Assets.
13.1.1. Use of residual geographic codes (Extra EU-27 not allocated, etc.)
Please see Table 13.1 in the Annex at the bottom.
When the residency of the UCI cannot be identified through local administrative sources, comprehensive online searches are conducted. In most cases, this process allows the residency of the UCI for the reference year to be determined. As a reult residual geographical codes are rarely applied, since most issues are resolved and the UCI is attributed to a specific country.
13.1.2. UCI Approach applied to identify the relevant population of reporting units
The UCI approach is applied by harmonising all enterprises within the same enterprise group, ensuring that all group companies and subsidiaries are assigned the same UCI and avoiding the allocation of different UCIs within a single group. Identification relies primarily on local administrative data on ownership and control. Where ownership is unclear, the UBO concept is applied. Remaining uncertain cases are further checked through online research to ensure correct identification of reporting units.
13.1.3. Update date (or frequency of updates) of the information regarding the country of the UCI by the “source administration”
Enterprise group structures are generated annually using data from the Malta Business Registry (MBR). The MBR provides detailed information on the 'immediate ownership' of each legal unit, which is then analysed to identify the ultimate parent company for each legal unit within the group. This data is typically received at the end of the reference year, in December, and processed over the following two months. This process ensures that administrative ownership information is effectively utilised to compile IFATS accurately, supporting both reliability and completeness of enterprise structure reporting.
13.1.4. Description of other method used to improve the accuracy of the UCI
Historical information on UCIs, together with data from the EGR and the Groups Register, is systematically integrated into the IFATS workflow to ensure comparability across reference years. A priority ranking is applied to guarantee that the most significant enterprises are profiled individually for their UCI. The selection of companies for profiling follows established criteria, focused on the significance of core variables. This approach ensures that, profiling continues sequentially until a cumulative coverage threshold is reached. This approach ensures that for each reference year, the most substantial enterprises are profiled collectively to represent at least 60% of the Persons employed, 70% of Net turnover an Value added, and 80% of Gross investment in tangible non-current assets . Any changes observed in UCIs compared with the previous years are checked and validated, with the reasons documented by the IFATS coordinator.
13.2. Sampling error
As IFATS data is based on the population of Enterprises included in the SBS, the margin of error for IFATS mirrors that of the SBS. There are no distinct sampling methods specific to IFATS.
13.2.1. Sampling error - indicators
Not applicable
13.3. Non-sampling error
Non-sampling errors identified in the SBS automatically flow into IFATS as the SBS data serves as the primary data source for IFATS. Sources that may give rise to this error include NACE misclassifications and insufficient UCI data.
13.3.1. Coverage error
The same target population as in SBS is used.
13.3.1.1. Over-coverage - rate
Not applicable
13.3.1.2. Common units - proportion
Not applicable
13.3.1.3. Misclassification errors
Since the IFATS population is entirely derived from SBS data, any errors in classifying units to the incorrect class would have been addressed prior to the start of the IFATS process. The accuracy of IFATS depends on the quality of the original SBS classifications, since any misclassifications of units would have been addressed during the SBS process. The accuracy of IFATS therefore depends on the quality of the undelrying SBS classifications, as any remaining errors will be carried over into IFATS
13.3.1.4. Under- and over-coverage problems
Not applicable
13.3.2. Measurement error
Not applicable
13.3.3. Non response error
For performance values, IFATS relies entirely on SBS reults and is not based on a survey. Since 2021 pursuant to the EBS regualtion, the SBS and IFATS populations, the SBS population was extended to include NACE Section K and NACE Sections P-S excluding Divisions S94. IFATS work processes involve enterprise-by-enterprise profiling using administrative data, eliminating the need for a survey and non response errors.
IFATS statistics are transmitted annually to Eurostat at T+20 months after the end of the reference year.
14.1.1. Time lag - first result
First results are transmitted to Eurostat 20 months after the end of the reference year (T+20).
14.1.2. Time lag - final result
Revised and final data is voluntarily transmitted to Eurostat 32 months after the end of the reference year (T+32) following the annual review of the SBS. This practice is in line with Malta’s revisions policy, which ensures that any updates or corrections identified during the SBS review are incorporated into the IFATS results.
14.2. Punctuality
The transmission of IFATS 2023 was completed on time, fully meeting the T+20 months target date.
14.2.1. Punctuality - delivery and publication
Timely in accordance with the regulated deadline.
15.1. Comparability - geographical
Not applicable
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
IFATS data are fully comparable from 2016 to 2020. Changes in methodology and NACE coverage from 2021 onwards mean that later years are not comparable with this period.
15.2.1. Length of comparable time series
The full length of time series available for IFATS is from: 2009 to 2023.
Length of comparable time series: 2016 - 2020 2021 - onwards (not comparable with 2016-2020)
15.2.2. Reasons and differences in concepts and measurement methods for breaks in time series
2016
Malta introduced a new IFATS processing methodology, and removed specific cut-off thresholds to ensure consistency with SBS aggregates.
2021
SBS eliminated the €7,000 turnover threshold; IFATS adjusted accordingly.
Regulation (EU) 2019/2152 (EBS Regulation) replaced the old FATS regulation (Regulation (EC) No 716/2007) .
NACE coverage was extended.
The ‘Enterprise’ Statistical Unit was adopted, ensuring all active enterprises are included.
15.3. Coherence - cross domain
IFATS data is harmonised to align consistently with both SBS and Business Demography (BD), ensuring a unified and coherent statistical approach across these domains.
15.3.1. Coherence - sub annual and annual statistics
Not applicable
15.3.2. Coherence - National Accounts
Not applicable
15.3.3. Coherence – National Statistical Business Register (NSBR)
IFATS target population is fully harmonised with that of the SBS. The number of active enterprises and count of employees and self-employed persons are coherent with those recorded in the active NSBR.
15.3.4. Coherence – Structural Business Statistics (SBS)
IFATS data values are fully aligned with SBS ensuring consistency., Confidential cells in IFATS mirror those of SBS, however, the confidentiality count is higher in IFATS due to a more detailed breakdown of data by country of UCI.
15.3.5. Coherence – R & D
Not applicable
15.3.6. Coherence – Foreign Direct Investment (FDI)
IFATS data is not harmonised with FDI data due to different concepts.
15.3.7. Coherence – EuroGroups Register (EGR)
The difference between IFATS and EGR data primarily arises in the identification of the UCIs due to differences in methodological. While IFATS, where data is available, chooses the natural person as the UCI, the EGR identifies the UCI at the enterprise level, stopping when the respective enterprise is no longer controlled by another institutional unit. Even if a domestic group is ultimately owned by a non-resident natural person, it is still excluded, as the EGR focuses on company-to-company ownership structures. At the end of the IFATS process, the final UCIs by business unit are provided to the EGR coordinator in the Unit responsible of the National Statistical Business Register.
15.4. Coherence - internal
IFATS data is coherent with SBS in terms of data values and with BD regarding the number of active enterprises and the count of employees and self-employed persons.
NSO benefits from access to administrative data sources that help in accurately identifying the UCI of each enterprise reducing the burden on companies. The most significant cost for the NSO lies in evaluating these administrative data sources, maintaining the EGR and ensuring consistency in group structures from year to year. It typically consumes the time of two-full time equivalent staff members for around two months to individually examine each enterprise group with financial statements from the MBR database and other sources to identify the UCI, with any changes being verified by the IFATS coordinator.
IFATS does not rely on a separate survey, as SBS data serves as its primary source. Consequently, there is no burden on respondents during the IFATS compilation process. Efforts are made during the SBS data collection phase to obtain the necessary information on branches operating in Malta. However, the legal disclosure requirements for activities in Malta are quite limited for branches, which may place an additional burden on respondents to provide estimates and increase the costs incurred during the follow-up stages. The SBS team continuously seeks ways to reduce the burden on its respondents during the data collection phase.
17.1. Data revision - policy
The SBS Unit's revision policy aims to improve the accuracy of SBS results for Eurostat and users by accessing a wider range of source data and ensuring better alignment between National Accounts and SBS statistics. This revision typically occurs one year after the target date and is a voluntary step taken to strengthen overall data quality. The same revision process is applied to the IFATS domain to maintain its consistency with the SBS domain. Following this policy, data up to 2022 is considered finalised while (IFATS) data linked with reference year 2023 will be revised in August 2026.
IFATS data are scheduled for review at T+32 months, after which they are transmitted to Eurostat. Once this review is complete, the data is considered final.
Malta follows a schedule for reviewing data every T+32 months, ensuring alignment with the SBS revised data scheduled at T+30 months. There is typically a brief delay between the transmission of datasets from Malta and their subsequent publication by Eurostat on Eurobase. As such, the most recent datasets sent for review from Malta may not yet be available on Eurobase.
The revisions made to the data often lead to very minor deviations from the initial results, typically of less than 1% of total economy aggregate Gross value added (GVA).
18.1. Source data
Economic information is retrieved from SBS records while geographical breakdowns are obtained from a range of administrative sources such as the MBR, publicly available sources, EGR, and the Groups register. In addition, online information is also used to complement and validate these sources, providing further details where necessary.
18.1.1. Methodological approach
The IFATS workflow integrates information from previous IFATS reference years, EGR and Groups register. Once these data sources are consolidated into a single framework, a priority sorting is applied to ensure that the most important enterprises are profiled first. Changed in UCIs compared with previous IFATS data are documented, while also validating any discrepancies relative to EGR and Groups register.
After the most important units have been profiled, a selection of additional enterprises for profiling is determined by specific criteria that focus on the core variables. This ensures that, for each reference year, profiling covers enterprises contributing to at least 60% of Persons employed, 70% of both Net turnover and Value added, and 80% of Gross investment in tangible non-current assets. These profiling tasks are carried out by a team of statistical officers, while any changes from previous years are verified and documented by the IFATS coordinator.
The UCI approach is harmonised across all enterprises within the same enterprise group. This guarantees that all group members are assigned the same UCI.
18.1.2. Use of cut-off thresholds
In line with the recommendations set out in the compilers manual, no cut-off thresholds are applied in the compilation of IFATS for Malta.
18.2. Frequency of data collection
Not applicable
18.3. Data collection
Most of the UCIs are determined from the financial statements providing the most direct and reliable source. In cases where the financial statements are not available or UCI data is not available, data from MBR shareholders and information on the UBO are considered. Additionally, data from EGR and historical UCI data is incorporated to allocate the correct UCI. Where UCIs cannot be determined from these sources, remaining uncertain cases are further investigated through online research.
All economic data is obtained from SBS results.
18.4. Data validation
Validations are carried out on UCIs to identify if there are any changes from previous years or from EGR data. The IFATS coordinator validates any changes. Consistency checks are applied to verify that the economic data obtained from SBS aligns with that of IFATS and that UCI details are also consistent with previous years' IFATS results.
The final transmission tables are validated through Eurostat's data validation tool – Input Hall and audited for their structure (STRUVAL) and content (CONVAL) as per FATS regulation. Any warnings are explained while any errors must be corrected prior to the transmission of the IFATS data tables to Eurostat.
18.5. Data compilation
The initial economic data for IFATS compilation is sourced from SBS, including NACE section K. From reference year 2021onwards, a separate approach for Section K's economic data was no longer needed , as economic data has been available from the SBS dataset. This data is then supplemented with information on the past UCIs assigned at micro-level, EGR, and other relevant sources.
18.5.1. Imputation - rate
Not applicable
18.5.2. Use of a method to deal with non-response (both unit and item non-response)
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) refer to statistics describing the activity of foreign affiliates resident in the compiling country.
In country-level business statistics, a foreign-controlled enterprise shall mean an enterprise resident in the compiling country over which an ultimate controlling institutional unit not resident in the compiling country has control.(Table 14 of the EBS Implementing Regulation (EU) 2020/1197).
Variables on the country-level business activities in the IFATS data category:
Business activities in foreign control:
210301. Number of foreign-controlled enterprises
220501. Number of employees and self-employed persons in foreign-controlled enterprises
220701. Employee benefits expense in foreign-controlled enterprises
230301. Intramural R & D expenditure in foreign-controlled enterprises
230401. R & D personnel in foreign-controlled enterprises
240301. Total purchases of goods and services of foreign-controlled enterprises
240302. Purchases of goods and services for resale of foreign-controlled enterprises
250601. Net turnover of foreign-controlled enterprises
250701. Value of output of foreign-controlled enterprises
260201. Foreign-controlled enterprises’ gross investment in tangible non-current assets
250801. Value added of foreign-controlled enterprises
Business activities in total economy:
210101. Number of active enterprises
220101. Number of employees and self-employed persons
220301. Employee benefits expense
230101. Intramural R & D expenditure
230201. R & D personnel
240101. Total purchases of goods and services
240102. Purchases of goods and services for resale
250101. Net turnover
250301. Value of output
250401. Value added
260101. Gross investment in tangible non-current assets
Research and Development (R&D) variables are disseminated every odd year, Malta is exempt from the collection of this information under the 1% exemption rule.
31 October 2025
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) refer to statistics describing the activity of foreign affiliates resident in the compiling country.
In country-level business statistics foreign-controlled enterprise shall mean an enterprise resident in the compiling country over which an ultimate controlling institutional unit not resident in the compiling country has control.(Table 14 of the Implementing Regulation (EU) 2020/1197).
Foreign affiliate in the framework of inward FATS is an enterprise resident in one country which is under the control of an institutional unit resident in another country.
Domestic affiliate refers to an enterprise resident in the compiling country over which a UCI resident in the same compiling country has control.
Ultimate Controlling Institutional unit of a foreign affiliate (UCI) refers to the institutional unit, proceeding up a foreign affiliate’s chain of control, which is not controlled by another institutional unit.
Control is the ability to determine the general policy of the affiliate by choosing appropriate directors, if necessary. In this context, enterprise A is deemed to be controlled by an institutional unit B when B controls, whether directly or indirectly, more than half of the shareholders' voting power or more than half of the shares.
Indirect control means that an institutional unit may have control through another affiliate which has control over enterprise A.
Active enterprise is a statistical unit which at any time during the reference period was classified as an ‘enterprise’, as defined in Regulation (EEC) No 696/93, and also active during the same reference period. A statistical unit is considered to have been active during the reference period if, in said period, it either realised positive net turnover, produced outputs, had employees or spent on investments.
Employees and self-employed persons are persons who work for an observation unit on the basis of a contract of employment and receives compensation in the form of wages, salaries, fees, gratuities, piecework pay or remuneration in kind; and persons who are the sole owners or joint owners of the statistical unit in which they work. Family workers and outworkers, whose income is a function of the value of the outputs of the statistical unit, are also included.
Employee benefits expense contains all expenses arising in relation with employee benefits, recognised by the statistical unit during the reference period. These refer to all forms of consideration given by the statistical unit in exchange for service rendered by employees or for the termination of employment.
Research and experimental development (R & D) comprises creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind, culture and society – and to devise new applications of available knowledge. Expenditures on intramural R & D represent the amount of money spent on R & D that is performed within a reporting unit. Intramural R & D expenditures are all current expenditures plus gross fixed capital expenditures for R & D performed within a statistical unit during a specific reference period whatever the source of funds. R & D current expenditures include labour costs for internal R & D personnel and other current costs (costs for external R & D personnel, purchase of services.). Gross fixed capital expenditures for R & D include: acquisition of land, acquisition of buildings, acquisition of information and communication equipment, acquisition of transport equipment, acquisition of other machinery and equipment, acquisition of capitalised computer software, acquisition of other intellectual property products.
R & D personnel in a statistical unit include all persons engaged directly in R & D, whether employed by the statistical unit or external contributors fully integrated into the statistical unit’s R & D activities, as well as those providing direct services for the R & D activities (such as R & D managers, administrators, technicians and clerical staff).
Total purchases of goods and services contains all amount of goods and services purchased by the statistical unit, recognised in accounting as either current assets or expenses during the reference period.
Purchases of goods and services for resale are purchases of goods for resale to third parties without further processing. It also includes purchases of services by ‘invoicing’ service companies, i.e. those whose turnover is composed not only of agency fees charged on a service transaction (as in the case of estate agents) but also the actual amount involved in the service transaction, e.g. transport purchases by travel agents.
Net turnover consists of all income arising during the reference period in the course of ordinary activities of the statistical unit, and is presented net of all price reductions, discounts and rebates granted by it.
Value of output represents the value of the total output of the statistical unit, generated during the reference period.
Value added represents the value a business adds through its production process. It reflects the net contribution of a business to the economy and is equivalent to the combined Gross operating surplus and Employee benefits expense.
Gross investment in tangible non-current assets includes all additions to tangible non-current assets, recognised as such by the statistical unit during the reference period, except any increases from revaluations or reversals of previously recognised impairment losses and from reclassifications (transfers) of other tangible non-current assets.
A Special Purpose Entity (SPE) in a country is a registered entity with very few or no employees, limited physical presence and negligible physical production in the host economy. SPEs are owned or controlled by non-resident entities. Data from Structural Business Statistics (SBS) do not include SPEs. Consequently, when compiling Inward FATS (IFATS), SPEs are similarly excluded.
When an enterprise is jointly controlled by multiple entities, the dominant country is identified by summing the shares from the shareholders resident in that country. If the respective country has a share ownership rate of over 50%, it is tagged as the UCI. If the share of ownership across more than one country is equal, the information on the residency of the executive directors and public data are used to help determine the UCI. If the UCI country is unable to be determined, the UCI is coded Z12 for shared control within the EU, and D09 for shared control outside the EU.
The ownership of shareholders is analysed to see if a collective group from one country holds 50% or more of the shares. If no dominant group from a single country is identified, control is then determined using publicly available data.
Until the reference year 2020, IFATS data were reported at legal unit level. Starting from reference year 2021, IFATS data are being reported at the enterprise statistical unit level.
The statistical unit of FATS is the enterprise as defined in line with the Regulation (EEC) No 696/93 on the statistical units for the observation and analysis of the production system in the Community.
All variables except R&D variables, cover NACE Rev.2 Sections B to N, P to R and Divisions S95 and S96.
The statistical population is equivalent to the SBS population, consisting of all operational business and branches while excluding companies registered in Malta whose production activities are carried out entirely abroad.
Starting from reference year 2021, there are no cut-off thresholds being applied. This mirrors the same policy adopted in the SBS.
IFATS data cover the active resident enterprises within the geographical boundaries of the Maltese islands.
2023
Accuracy is based on local administrative data on ownership, ordinary shares, Ultimate Beneficial Owners (UBO), and executive directors complemented by, the EuroGroups Register,audited financial statements and data from previous years. Each year, individual profiles are carried out covering at least up to the 60th cumulative percentile for the total Value Added, Net Turnover, and Persons Employed, and at least up to the 80th cumulative percentile for the total Gross Investments in Tangible Non-Current Assets.
The number of enterprises and employment variables are recorded in units.
Monetary data for enterprises are recorded in thousands of Euros.
The initial economic data for IFATS compilation is sourced from SBS, including NACE section K. From reference year 2021onwards, a separate approach for Section K's economic data was no longer needed , as economic data has been available from the SBS dataset. This data is then supplemented with information on the past UCIs assigned at micro-level, EGR, and other relevant sources.
Economic information is retrieved from SBS records while geographical breakdowns are obtained from a range of administrative sources such as the MBR, publicly available sources, EGR, and the Groups register. In addition, online information is also used to complement and validate these sources, providing further details where necessary.
Annually at T+20 for all variables, except for R&D variables which are disseminated every odd year.
IFATS statistics are transmitted annually to Eurostat at T+20 months after the end of the reference year.
Not applicable
IFATS data are fully comparable from 2016 to 2020. Changes in methodology and NACE coverage from 2021 onwards mean that later years are not comparable with this period.
