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.
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1.6. Contact email address
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1.7. Contact phone number
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1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
15 October 2025
2.2. Metadata last posted
15 October 2025
2.3. Metadata last update
15 October 2025
3.1. Data description
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) shall mean 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 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.
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);
List of 2-digit country codes (ISO 3166-1);
Currency codes (ISO 4217).
3.3. Coverage - sector
For all variables except for variables Intramural R & D expenditure, Intramural R & D expenditure in foreign-controlled enterprises, R & D personnel and R & D personnel in foreign-controlled enterprises: Market producers of NACE Sections B to N and P to R and divisions S95 and S96;
For variables Intramural R & D expenditure, Intramural R & D expenditure in foreign-controlled enterprises, R & D personnel and R & D personnel in foreign-controlled enterprises: Market producers of NACE Sections B to F.
3.4. Statistical concepts and definitions
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) shall mean 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 outward FATS is an enterprise or branch not resident in the compiling country over which an institutional unit resident in the compiling country has ultimate (direct or indirect) control.
Domestic affiliate shall mean an enterprise resident in the compiling country over which a UCI resident in the same compiling country has control.
Ultimate Controlling Institutional of a foreign affiliate (UCI) shall mean 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 units which at any time during the reference period was ‘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 realized positive net turnover or produced outputs or had employees or performed 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, recognized by the statistical unit during the reference period. Those are are 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) comprise 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, recognized in accounting as either current assets or expenses during the reference period.
Purchases of goods and services for resale in 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 is a composite indicator of net operating income, adjusted for depreciation, amortization and employee benefits, all components being recognized as such by the statistical unit during the reference period.
Gross investment in tangible non-current assets includes all additions to tangible non-current assets, recognized as such by the statistical unit during the reference period, except any increases from revaluations or reversals of previously recognized impairment losses and from reclassifications (transfers) of other tangible non-current assets.
3.5. Statistical unit
The statistical unit of FATS should be 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
For all variables except for variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to N and P to R and divisions S95 and S96;
For variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to F.
3.7. Reference area
Belgium
3.8. Coverage - Time
Data are available from 2007-2023.
3.9. Base period
Not applicable.
Number of enterprises and employment variables are recorded in absolute figures.
Monetary data of enterprises are recorded in thousands euro and disseminated in millions euro.
Data refers to the calendar year, which in some cases corresponds to the fiscal year.
6.1. Institutional Mandate - legal acts and other agreements
Annual for all variables except for variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to N and P to R and divisions S95 and S96;
Biennial (every odd-numbered year) for variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to F.
10.1. Dissemination format - News release
Not applicable as there is no news release on national level.
10.2. Dissemination format - Publications
Not applicable as there is no dissemination or publication on national level.
10.3. Dissemination format - online database
Not applicable as there is no online database on national level.
10.3.1. Data tables - consultations
No consultation of data tables.
10.4. Dissemination format - microdata access
Not applicable as there is no microdata access on national level.
10.5. Dissemination format - other
Not applicable as there is no other dissemination format on national level
10.5.1. Metadata - consultations
No consultation of metadata.
10.6. Documentation on methodology
No documentation on methodology available.
10.6.1. Metadata completeness - rate
Not available.
10.6.2. Availability of statistical metadata
Not available.
10.6.3. Web links if metadata are published electronically
Not available.
10.7. Quality management - documentation
There is no documenation on quality management on national level
11.1. Quality assurance
The quality of the aggregated data is assured.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
Users of inward FATS are: European Commission services, international organisations, ministries, chambers of commerce, trade unions, journalists, researchers etc. User needs go beyond what data compilers can provide.
12.2. Relevance - User Satisfaction
No indication of users' satisfaction with inward FATS.
12.3. Completeness
Data is complete
12.3.1. Data completeness - rate
Please see Table 12.3.1 in the Annex at the bottom.
13.1. Accuracy - overall
The overall accuracy is sufficient.
As in previous years, there are some reasons inherent to the survey which may lead to certain biases or accuracy problems:
sampling and modelling errors can occur because of the rotating model used to draw the sample (see 13.3 and 16). For small businesses that are not surveyed every year, the evolution of the various variables is estimated on the basis of the evolution of VAT data. These estimates have limits in terms of accuracy, since VAT data may be not perfectly correlated with the other variables.
some errors on the NACE codes in the business register can also lead to misclassification in the sampling procedure: if a company selected in the sample for a NACE class turns out to be misclassified, the number of companies actually surveyed for the NACE class in question inevitably falls, leading to a reduction in representativeness.
for provisional data, annual accounts, VAT data and data of the previous years are used to compute the results, which can lead to some bias. However, provisional data are not disseminated by Statistics Belgium.
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.
13.1.2. UCI Approach applied to identify the relevant population of reporting units
The UCI approach is applied to identify the relevant statistical units.
13.1.3. Update date (or frequency of updates) of the information regarding the country of the UCI by the “source administration”
Not available.
13.1.4. Description of other method used to improve the accuracy of the UCI
The EGR is the main source for determining the UCI of a unit (from the reference year 2023).
13.2. Sampling error
The population and data comes from Statbel. They gave us the following explanation about the sampling and sampling error: SBS is a non-exhaustive survey: we operate on a sample basis, particularly for smaller companies. The companies for which there is no data are, almost without exception, companies that were not included in this year's sample. The rest are companies that were selected but never returned their completed forms
13.2.1. Sampling error - indicators
Coefficients of variation are calculated and transferred in different files. The coefficients of variation are calculated using the POULPE macro in SAS. The aspects of the survey taken into account are the sample design (stratified simple random sampling), non-response correction and calibration.
The sampling error can be considered small, in 95% of the cases, the coefficient of variations are smaller than 10%.
13.3. Non-sampling error
See more detailled information in 13.3.3 non response error
13.3.1. Coverage error
No coverage error as we only receive target data.
13.3.1.1. Over-coverage - rate
No overcoverage as we only get the target population from the national statistical office.
13.3.1.2. Common units - proportion
No common units as we get our data directly from the national statistical office
13.3.1.3. Misclassification errors
No misclassification errors
13.3.1.4. Under- and over-coverage problems
No under- and over-coverage problems
13.3.2. Measurement error
No measurement error.
13.3.3. Non response error
Unit non-response occurs when not all the reporting units in the sample participate in the survey.
Item non-response occurs when a respondent provides some, but not all, of the information requested or if the information reported is unusable (note that entirely unusable questionnaires are already counted in the unit non-response).
The following methods are applied to take into account unit non-response:
imputation: ratio imputation or hot deck imputation
reweighting
Furthermore, the following measures are taken to minimize non-response:
The survey is compulsory (Belgian Royal Decree of 18 July 2008)
Three reminder letters are sent
Telephone calls and visit are made to large enterprises
In order to calculate the non-response we took only the active and eligible enterprises into account (out-of-scope enterprises have been excluded). We weighted the unit non response rate with the number of persons employed. The overall weighted non-response rate is 2.41 %. Compared to the unweighted non-response rate of 14.46% this means that larger enterprises (in terms of employment) report better. In the overall contest, we evaluate this non-response rate as low.
For reference year 2023 the smaller entities from the industry and trade sectors have been estimated using data on the same units from other sources. The use of past survey data and recent administrative data from several sources can introduce some bias but this is minimized through plausibility controls and checks. Moreover, the estimation method concerns smaller enterprises. Therefore, we assume that the overall effect on the accuracy of the estimates is limited.
The survey unit non-response may be not random. The potential bias is minimized by using imputations (if possible) for the non-responding enterprises. Moreover, the survey unit non-response is low, especially for the larger units. So we believe there is only a small potential bias resulting from survey non-response.
Errors in the business register can have an effect on sampling and on sampling weights. The exact impact on SBS results is unknown. Errors in addresses of statistical units in the business register also causes a coherence problem between national and regional results. The sum of the regional results is not identical to the national value, but the difference is small in most cases.
1% of the units initially included in the sample are deemed to be out of scope. These units are identified on basis of administrative data or after contact during the survey.
13.3.3.1. Unit non-response - rate
See Table 13.3.3 in the Annex at the bottom.
13.3.3.2. Item non-response - rate
See Table 13.3.3 in the Annex at the bottom.
13.3.4. Processing error
No processing errors
13.3.5. Model assumption error
No model assumption errors
14.1. Timeliness
IFATS statistics are calculated annually for reference year T.
Data collection takes place at T+16 months after the end of the reference period.
Data transmission to Eurostat takes place at T+20 months.
Data dissemination at national level doens't take place.
14.1.1. Time lag - first result
Not available
14.1.2. Time lag - final result
Not available.
14.2. Punctuality
The deadlines of dissimenation to Eurostat were respected.
14.2.1. Punctuality - delivery and publication
Data was transmitted to Eurostat on 8 August 2025, 22 days before the deadline on 31 August 2025.
15.1. Comparability - geographical
The same statistical concepts are applied across entire national territory.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
Data are comparable between 1996 and 2007 and between 2008 and 2017. Until 2007, NACE Rev.1 is used. From 2008 onwards, results are computed according to NACE Rev.2. Until reference year 2017, the enterprise statistical unit was the legal unit.
As of reference year 2018, we started using the statistical unit enterprise, in line with the Belgian business register. Before this, the legal unit was used as statistical unit.
For reference year 2021, we produced on legal unit level as we got our R&D data from the Belgian Science Policy Office. They provided the data on statistical legal unit level instead of enterprise level.
For reference year 2022, we produced on enterprise level. We have thus a break in time for reference year 2021.
From reference year 2023, we use EGR as a main source for the determining the population. We have thus a break in time for reference year 2023.
15.2.1. Length of comparable time series
Length of time series: 2008-2023:
2008-2017;
2018-2020;
2021;
2022;
2023.
15.2.2. Reasons and differences in concepts and measurement methods for breaks in time series
As of reference year 2018, we started using the statistical unit enterprise, in line with the Belgian business register. Before this, the legal unit was used as statistical unit.
For reference year 2021, we produced on legal unit level as we got our R&D data from the Belgian Science Policy Office. They provided the data on statistical legal unit level instead of enterprise level.
For reference year 2022, we produced on enterprise level. We have thus a break in time for reference year 2021.
From reference year 2023, we use EGR as a main source for the determining the population. We have thus a break in time for reference year 2023.
15.3. Coherence - cross domain
There may also be discrepancies between SBS and other surveys: the reason for this lies in NACE coding errors. As mentioned in 13.1, companies selected from the SBS sample as belonging to a NACE sector may report another main activity. These "assignment errors" imply adjustments in the results and in their weight in the universe: statistical calibration, specific to each sample. Discrepancies with another survey (e.g. LFS) are therefore inevitable.
Comparison of variable Net Turnover (250101) with turnover statistics based on VAT declarations. Some inconsistencies due to difference in definitions and in methods.
15.3.1. Coherence - sub annual and annual statistics
Not applicable as there are no sub annual FATS statistics
15.3.2. Coherence - National Accounts
SBS is the result of a survey. SBS and the national accounts may also diverge, since the national accounts are based in part on administrative sources.
15.3.3. Coherence – National Statistical Business Register (NSBR)
No incoherence as we get our data from the National Statistical Business Register.
15.3.4. Coherence – Structural Business Statistics (SBS)
No incoherence.
15.3.5. Coherence – R & D
No incoherence, FATS R&D characteristics are supplied from R&D statistics.
15.3.6. Coherence – Foreign Direct Investment (FDI)
No incoherence.
15.3.7. Coherence – EuroGroups Register (EGR)
Not available.
15.4. Coherence - internal
Regional results do not add up to national results because some local units have no address in our business register and can therefore not be allocated to a NUTS-group.
Not available.
17.1. Data revision - policy
No revision policy is presently applied.
17.2. Data revision - practice
Not applicable.
17.2.1. Data revision - average size
No data revision of FATS.
18.1. Source data
The main data source used to identify UCI is EGR. The statistical business register is our main source for economic data.
18.1.1. Methodological approach
The information about the UCI is from EGR. The economic data is SBS data is collected by the Belgian NSI. For information concerning the SBS sample design, please contact the Belgian NSI.
We link several sources to obtain information:
EGR for the UCI (geographical breakdown) and population.
Information from national accounts for the data on financial sectors (econonomic information).
Information from the Belgian Science Policy Office for the R&D data (economic information).
SBS for all other data and information (geographical breakdown & economic information).
18.1.2. Use of cut-off thresholds
SBS is a non-exhaustive survey: we operate on a sample basis, particularly for smaller companies. We asked about the cut-off treshold, but are still waiting for answer from National Statistical Office.
18.2. Frequency of data collection
Annual.
18.3. Data collection
Source to define your population:
0 % census survey;
0 % sample survey;
0 % Structural Business Statistics (SBS);
0 % Foreign Direct Investment (FDI);
100 % EuroGroups Register (EGR);
0 % Statistical Business Register (SBR);
0 % Administrative sources;
0 % Private data sources;
0 % Publicly available sources;
0 % Other data sources (indication of the sources: ...).
Economic data obtained using:
0 % census survey;
0 % sample survey;
91,1 % Structural Business Statistics (SBS);
0 % Foreign Direct Investment (FDI);
0 % EuroGroups Register (EGR);
0 % Statistical Business Register (SBR);
8,9 % Administrative sources;
0 % Private data sources;
0 % Publicly available sources;
0 % Other data sources (indication of the sources: ...).
18.4. Data validation
Not available.
18.5. Data compilation
First The National Statistical Office compile the IFATS population from EGR population. Then we get the economic data for this population from them (SBS data), except for the R&D variables. The economic information on the R&D variables we get from the Belgian Science Policy Office (Belspo)
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) shall mean 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 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.
15 October 2025
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) shall mean 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 outward FATS is an enterprise or branch not resident in the compiling country over which an institutional unit resident in the compiling country has ultimate (direct or indirect) control.
Domestic affiliate shall mean an enterprise resident in the compiling country over which a UCI resident in the same compiling country has control.
Ultimate Controlling Institutional of a foreign affiliate (UCI) shall mean 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 units which at any time during the reference period was ‘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 realized positive net turnover or produced outputs or had employees or performed 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, recognized by the statistical unit during the reference period. Those are are 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) comprise 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, recognized in accounting as either current assets or expenses during the reference period.
Purchases of goods and services for resale in 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 is a composite indicator of net operating income, adjusted for depreciation, amortization and employee benefits, all components being recognized as such by the statistical unit during the reference period.
Gross investment in tangible non-current assets includes all additions to tangible non-current assets, recognized as such by the statistical unit during the reference period, except any increases from revaluations or reversals of previously recognized impairment losses and from reclassifications (transfers) of other tangible non-current assets.
The statistical unit of FATS should be 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.
For all variables except for variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to N and P to R and divisions S95 and S96;
For variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to F.
Belgium
Data refers to the calendar year, which in some cases corresponds to the fiscal year.
The overall accuracy is sufficient.
As in previous years, there are some reasons inherent to the survey which may lead to certain biases or accuracy problems:
sampling and modelling errors can occur because of the rotating model used to draw the sample (see 13.3 and 16). For small businesses that are not surveyed every year, the evolution of the various variables is estimated on the basis of the evolution of VAT data. These estimates have limits in terms of accuracy, since VAT data may be not perfectly correlated with the other variables.
some errors on the NACE codes in the business register can also lead to misclassification in the sampling procedure: if a company selected in the sample for a NACE class turns out to be misclassified, the number of companies actually surveyed for the NACE class in question inevitably falls, leading to a reduction in representativeness.
for provisional data, annual accounts, VAT data and data of the previous years are used to compute the results, which can lead to some bias. However, provisional data are not disseminated by Statistics Belgium.
Number of enterprises and employment variables are recorded in absolute figures.
Monetary data of enterprises are recorded in thousands euro and disseminated in millions euro.
First The National Statistical Office compile the IFATS population from EGR population. Then we get the economic data for this population from them (SBS data), except for the R&D variables. The economic information on the R&D variables we get from the Belgian Science Policy Office (Belspo)
The main data source used to identify UCI is EGR. The statistical business register is our main source for economic data.
Annual for all variables except for variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to N and P to R and divisions S95 and S96;
Biennial (every odd-numbered year) for variables 230101 (Intramural R & D expenditure), 230301 (Intramural R & D expenditure in foreign-controlled enterprises), 230201 (R & D personnel) and 230401 (R & D personnel in foreign-controlled enterprises): Market producers of NACE Sections B to F.
IFATS statistics are calculated annually for reference year T.
Data collection takes place at T+16 months after the end of the reference period.
Data transmission to Eurostat takes place at T+20 months.
Data dissemination at national level doens't take place.
The same statistical concepts are applied across entire national territory.
Data are comparable between 1996 and 2007 and between 2008 and 2017. Until 2007, NACE Rev.1 is used. From 2008 onwards, results are computed according to NACE Rev.2. Until reference year 2017, the enterprise statistical unit was the legal unit.
As of reference year 2018, we started using the statistical unit enterprise, in line with the Belgian business register. Before this, the legal unit was used as statistical unit.
For reference year 2021, we produced on legal unit level as we got our R&D data from the Belgian Science Policy Office. They provided the data on statistical legal unit level instead of enterprise level.
For reference year 2022, we produced on enterprise level. We have thus a break in time for reference year 2021.
From reference year 2023, we use EGR as a main source for the determining the population. We have thus a break in time for reference year 2023.
