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.
Information and statistical services: Economic statistics department
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Työpajankatu 13
00580 Helsinki
Finland
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
20 October 2025
2.2. Metadata last posted
20 October 2025
2.3. Metadata last update
20 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 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
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
Finland (FI)
3.8. Coverage - Time
Time series from 2021 onwards.
Based on legal units: 1996 – 2021 Changes in NACE classification caused discontinuity in the time-series in years 2002 and 2008. Also methods and renewal of statistical units caused discontinuity in the time-series in years 2013 and 2021. Based on enterprise units: 2017 onwards. Changes in the definitions of the statistical units and the number of employees and self-employed persons caused a discontinuity in the time series between years 2020 and 2021. Annual data on the statistics on business services are available on the home page of the statistics andin Statistics Finland's StatFin database starting from 2008. The statistical population for national statistics on business services and foreign affiliates in Finland was changed to cover all enterprises in connection with the statisticalreference year 2020 and the population is no longer limited to enterprises with 5 or 20 employeesdepending on the industry. For Eurostat the data for business services includes only enterprises with at least 20 employees. Comparable timeseries for business services data sent to Eurostat is from 2020 onwards. From this year the turnover data has been better in coherence with SBS data because of the use of consolidated turnover in business services. This also applies to IFATS. Also the division of the turnover data by residence of client has been estimated using administrative data instead of survey data.
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 in EUR and disseminated in million of EUR.
2023
The data refers to fiscal year. The different financial years are converted to correspond to the statistical year.
6.1. Institutional Mandate - legal acts and other agreements
Confidentiality policy is based on the basic statistical law. The statistical authority shall not disclose information that allows the statistical unit to be identified directly.
7.2. Confidentiality - data treatment
Please see Table 7.2 in the Annex at the bottom.
Confidentiality rules Primary: If a cell contains less than 3 observations or if there are dominating enterprises. Secondary: Flagging cells so that the least amount of data is lost. Software used: TauArgus. There are no plans/no possibility to reduce the confidentiality.
Finland also disseminates data for OECD. National dissemination is found online. Tailored statistics are available for charge.
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.
Specific tool (Edamis) maintained by Eurostat for validation of IFATS-series. All enterprises go through automatic data validation and enterprises with biggest errors are manually corrected. Also biggest companies are manually checked. The quality management framework of the field of statistics is the European Statistics Code of Practice (CoP). The quality criteria of Official Statistics of Finland are compatible with the European Statistics Code of Practice. Further information: Quality management | Statistics Finland (stat.fi) The quality of the structural business and financial statement statistics is examined as the data accumulate. At aggregate level, the data are compared with the previous year and the most significant changes are examined. Coherence analyses to short term statistics are also carried out. IFATS data is analysed at the same time as SBS data.
11.2. Quality management - assessment
IFATS is produces with SBS series and has same quality management.
We have comprehensive administrative data at our disposal, thus the accuracy is mostly good. Relevance of the statistic is good. If any relevant data is missing it can be ordered for charge. Timeliness is better than in most European countries: the preliminary data is published within 9 months and final data within 12 months. Coherence with other statistics is good. We use same database with other business statistics and NA. The top management of Statistics Finland has made several self-assessments in line with the EFQM model. Therehave also been external audits by e.g. the EU and IMF experts. Processes are in place to monitor thequality of the statistical process and the processes of individual statistics. Quality considerations are an integral part of the planning and evaluation of the statistical programme. The process owner of statistical production and it’s supporting group monitor the quality and steer the standardisation of work processes. Statistics Finland has an internal quality audit system. The main objectives are to evaluate the ways of working, methods and techniques. An audit is carried out by an audit team of experts who are external in the sense that they do not have any direct connection with the production process in question. About 8 audits are carried out yearly.
12.1. Relevance - User Needs
internal, reseachers, enterprises, media etc. External: Eurostat, OECD.
12.2. Relevance - User Satisfaction
not available
12.3. Completeness
We are providing all the relevant data required by European Business Statistics Regulation.
12.3.1. Data completeness - rate
Please see Table 12.3.1 in the Annex at the bottom.
IFATS is subset of SBS series. In SBS series metadata report states following: the main source of errors is non-response. Admistrative data should be very precise and it is analysed and locked 1 month before national publication. Final data lockdown date is 19th December 2024. Before Eurostat data delivery all the necessary corrections are made and if some corrections have been made they are corrected to eurostat data delivery. In my opinion IFATS data is quite precise and accurate. My assessment over IFATS data is very good. C. UCI is information is from administrative data and if not available from there it is carefully analysed using enterprise annual reports, web pages, egr and most reliable source is always chosen.
The influence of non-sampling error is small. The unit non-response are imputed based on last years data or nearest neighbour with distance measure. In Business Services data unit non-response is taken into account by grossing up the data. The recorded unit non-response rate: Low The bias of the estimate: Small bias Coverage error: Almost none Out of scope units: For the reference year 2021 the business Register annual Quality Control Survey covered 1417 legal units. The response rate was 61,5 percent. Based on the survey results 3 percent were found to be misclassified (5-digit level). The statistics on Business Services do not describe service production comprehensively due to the employee limitations of the respondent group. The product distributions of enterprises in the stratum with the smallest number of employees but fewer than five persons and not belonging to the inquiry group may differ from the product distributions of enterprises belonging to the respondent group of the stratum, and this may cause inaccuracy in the estimated product distribution of the industry if the turnover of these enterprises accounts for a large share of the industry's turnover.
A significant factor affecting the reliability of the Business Services statistics is the ability of the respondents to break down turnover according to the CPA classification. Efforts have been made to manage this risk by specifying the classification and the descriptions of the categories.
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
UCI concept is used. UCI information is administrative data and it is collected from annual reports, enterprise's web pages and EGR if no other source.
13.1.3. Update date (or frequency of updates) of the information regarding the country of the UCI by the “source administration”
UCI is updated annually. Last update of UCI is 19th December 2024.
13.1.4. Description of other method used to improve the accuracy of the UCI
If UCI is not found from administrative source data is update from enterprises web pages, annual reports etc.
13.2. Sampling error
Not relevant because total data is available for variables.
13.2.1. Sampling error - indicators
not relevant
13.3. Non-sampling error
IFATS is subset of SBS series. SBS metadata report states following:
The influence of non-sampling error is small. The unit non-response are imputed based on last years data or nearest neighbour with distance measure. In Business Services data unit non-response is taken into account by grossing up the data. The recorded unit non-response rate: Low The bias of the estimate: Small bias Coverage error: Almost none Out of scope units: For the reference year 2021 the business Register annual Quality Control Survey covered 1417 legal units. The response rate was 61,5 percent. Based on the survey results 3 percent were found to be misclassified (5-digit level). The statistics on Business Services do not describe service production comprehensively due to the employee limitations of the respondent group. The product distributions of enterprises in the stratum with the smallest number of employees but fewer than five persons and not belonging to the inquiry group may differ from the product distributions of enterprises belonging to the respondent group of the stratum, and this may cause inaccuracy in the estimated product distribution of the industry if the turnover of these enterprises accounts for a large share of the industry's turnover.
A significant factor affecting the reliability of the Business Services statistics is the ability of the respondents to break down turnover according to the CPA classification. Efforts have been made to manage this risk by specifying the classification and the descriptions of the categories.
13.3.1. Coverage error
almost none
13.3.1.1. Over-coverage - rate
not available
13.3.1.2. Common units - proportion
not available
13.3.1.3. Misclassification errors
Not relevant. Minor misclassified error on 5 digit level - not relevant on IFATS.
13.3.1.4. Under- and over-coverage problems
almost none
13.3.2. Measurement error
not applicable
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).
13.3.3.1. Unit non-response - rate
not applicable
13.3.3.2. Item non-response - rate
Not applicaple
13.3.4. Processing error
not applicable
13.3.5. Model assumption error
not applicable
14.1. Timeliness
IFATS statistics are calculated annually for reference year T.
Data collection takes place at t+… months after the end of the reference period.
Data transmission to Eurostat takes place at t+20 months.
Data dissemination at national level takes place at t+12 months.
14.1.1. Time lag - first result
not applicable
14.1.2. Time lag - final result
national dissemination t + 12 (Statistical year 2025 due to NACE classification reneval t + 13-15), eurostat t + 20
14.2. Punctuality
data is transmitted on time
14.2.1. Punctuality - delivery and publication
data is transmitted on time
15.1. Comparability - geographical
Not applicable
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
timeseries 2023
15.2.1. Length of comparable time series
Length of time series: 2021-2023
Length of comparable time series: 2021-2023
15.2.2. Reasons and differences in concepts and measurement methods for breaks in time series
IFATS is subset of SBS series and in SBS metadata report states following.
Statistical Finland has renewed and harmonized the statistical units used in SBS, IFATS and BD statistics from year 2021 onwards. Limitations concerning the operating time and size of enterprises have been removed from the definition of statistical units. Previously, only enterprises having operated for at least six months in the statistical reference year and whose turnover, number of personnel, investments or balance sheet exceeded the statistical limit were included in the statistics.The statistics now include all market-based enterprises that have had turnover, personnel, other operating income, investments, or balance sheet during the statistical reference year. The total number of enterprises will increase by around 50 per cent. But the effect of the new statistical units on variables other than the number of enterprises is mainly quite marginal. The new statistical units increased the turnover of the statistics as a whole by under 0.5 per cent. The data calculated with thenew statistical units is available on Statistics Finlands data base from 2018 onwards.
The data on the number of personnel in the statistics have been calculated with a new method from year 2021 onwards. The renewal decreases the number of personnel in fte by around 136 000 persons (9,0 %) calculated with data for 2020. There is no back-casted data for the new estimates. A comparable time series on the statistics on service industry commodities is nationally available forthe time period 2008 to 2019. The statistical population in national statistics was changed to cover all enterprises in connection with the statistical reference year 2020 and the population is no longer limited to enterprises with 5 or 20 employees depending on the industry. Turnover data are not collected with the CPA classification in other sources. Comparable timeseries for business services data sent to Eurostat is from 2020 onwards. From this year the turnover data has been better incoherence with SBS data because of the use of consolidated turnover in business services. Also the division of the turnover data by residence of client has been estimated using administrative data instead of survey data.
15.3. Coherence - cross domain
IFATS is subset of SBS series. Coherence is good. There are differences between IFATS and RD statistics. In IFATS weights was not used due to data matrix is rather complex and weighting data would have been impossible.
15.3.1. Coherence - sub annual and annual statistics
Not applicable
15.3.2. Coherence - National Accounts
IFATS is subset of SBS and in SBS metadata reports states that value added is from national accounts.
15.3.3. Coherence – National Statistical Business Register (NSBR)
Coherence between NSBR is good.
15.3.4. Coherence – Structural Business Statistics (SBS)
coherence is good.
15.3.5. Coherence – R & D
There are uncoherence between R&D and ifats. Difference in R&D figures between R&D statistics and iFATS statistics is due to different treatment of weights .
15.3.6. Coherence – Foreign Direct Investment (FDI)
not applicable
15.3.7. Coherence – EuroGroups Register (EGR)
Only small enterprises might have uncoherence between EGR and administative source. Uncoherence is not significant.
15.4. Coherence - internal
The aggregates are always consistent with their main sub-aggregates
IFATS is subset of sbs series. In sbs metadata report states following:
We use administrative data for most of SBS variables. We did a burden measuring survey for enterprises who are part of our financial statement survey in 2018: 900 enterprises answered
the average time spend to answer was 188 minutes (median was 120 minutes)
29 % of the enterprises answering to the survey used over 3 hours to answer
55 % thought that the survey was very burdensome
17.1. Data revision - policy
Different versions of administrative data cause revisions. In general revisions are small/moderate if compared to the known use of data. Revisions to the data after the final dissemination are made only if major error are found.
17.2. Data revision - practice
All the revisions are due to revised source data.
17.2.1. Data revision - average size
Revisions are only made if error is significant and usually at the last next national dissemination date.
18.1. Source data
IFATA is subset of sbs series.
Business register, a direct inquiry, Financial supervisory authority, VAT data and Tax Authority administrative data. Administrative data from Tax Administration provides financial statements data for all enterprises (main source). The BR provides information on principal activity and number of personnel. The direct inquiry for other than Business Services data is a census which covers all enterprises with more than 60 employees. Some enterprises with more than 10 employees are also included in sample survey. The direct inquiry data are mainly collected for the national data needs (more detailed data on certain variables/items for the calculation of national accounts).
Data source soverview Survey data yes VAT data yes Tax data yes Financial statements yes Other sources, please specify: Financial supervisory authority data Comment Main data source is Business tax data.We use survey data only for specific variables missing from the administrative data.
18.1.1. Methodological approach
The data for the statistics on foreign affiliates in Finland are compiled on the basis of the structural business and financial statements statistics by selecting subsidiaries in foreign ownership from it. The data contained in the structural business and financial statements statistics are processed as follows:
Processing of business tax data The quality of the Finnish Tax Administration data is verified programmatically. The data are revised automatically by means of mass editing and imputing. Values missing from the data are replaced in the first instance with data for earlier years, and in the second instance, with data on enterprises in the same category in terms of turnover and number of personnel. Errors and outliers are corrected either by means of logical editing or by removing outliers. Minor turnover errors (less than five per cent) are scaled.
Two different imputation methods are in use. Donor imputation is used when the enterprise is included in the statistical frame, but no data are available in the material provided by the Finnish Tax Administration. In such cases, the data are obtained from enterprises of a similar size operating in the same industry. The second method is used when no tax data on the enterprise can be obtained for the statistical year in question, but the data for the previous year are available. In such cases, the data are imputed by using changes in turnover in the periodic tax data as a weighting coefficient.
Own inquiry Sample responses are processed manually together with the business tax data for each enterprise separately, using the image archive of the Finnish Patent and Registration Office.
Checking of the additional data on financial statements is guided by internal production application rules. Using approved data as a basis, industry-specific coefficients are calculated for turnover specifications and expenditure specifications. The coefficients are used to produce corresponding data for the entire group of enterprises. All enterprises in the random sample that have received only a small number of penalty points are approved en masse. Some of them are returned to manual checking.
18.1.2. Use of cut-off thresholds
IFATS is subset of SBS. In sbs metadata report states following:
For the Business Services data sent to Eurostat, the threshold of 20 persons employed is applied. For domestic dissemination a threshold of 5 or 20 persons employed is used depending on Nace branch.The reason for this is that the threshold of 20 excludes a significant proportion of turnover in some branches. Our aim is to cover at least 80% of turnover for each branch by bringing the threshold down to 5 persons when necessary.
18.2. Frequency of data collection
Annual
18.3. Data collection
Administrative data:
Direct access to an administrative data base. Part of the administrative data are sent to StatisticsFinland. Scoring model is introduced to detect and evaluate errors.
Source to define your population:
… % census survey
… % sample survey
100 % Structural Business Statistics (SBS)
… % Foreign Direct Investment (FDI)
… % EuroGroups Register (EGR)
… % Statistical Business Register (SBR)
100 % Administrative sources
… % Private data sources
… % Publicly available sources
… % Other data sources (indication of the sources: ...)
Economic data obtained using:
… % census survey
… % sample survey
… % Structural Business Statistics (SBS)
… % Foreign Direct Investment (FDI)
… % EuroGroups Register (EGR)
… % Statistical Business Register (SBR)
… % Administrative sources
… % Private data sources
… % Publicly available sources
… % Other data sources (indication of the sources: ...)
18.4. Data validation
Validation of format and file structure checks. This validation is made right after extraction the data from administrative data base. The same prosedure is applied to the survey data.
18.5. Data compilation
IFATS is subset of sbs series. SBS metadata report states following.
Imputation methods: Tax data is treated automatically using mass editing and imputation techniques. The errors and outliers are edited in following order: Logical edits, Outlier detection, Small errors (<5%) from turnover are re-scaled. Two types of imputation methods are used in the SBS data. First type is donor imputation which is applied for unit non-response in tax data. The data is imputed using last-years data, VAT-data or nearest neighbour imputation with distance measure. Unit non-response includes those units that have not sent their accounting data to Tax Authority: Second step is item non-response. Item non-response refer to mass imputation of the variables included in direct inquiry and not received fromTax Authority. Primary method used is regression imputation with outlier detection and weighting if necessary. Survey data is mainly checked manually. It forms the basis for imputation process of some of the variables. Tax data and survey data is compiled together thus forming our structural business data. For Business Services data: The effect of non-response is corrected by calculating the non-response correction coefficient for each stratum based on the numbers of the responding enterprises. When the data are raised to the whole population, enterprises' turnover data are picked again from the same database of Statistics Finland that is used in the compilation of other business statistics. The enterprise-specific sample weight is multiplied by the stratum-specific non-response correction weight calculated in the first stage, which produces a preliminary weighting coefficient for the enterprise. The turnover data raised with this weighting coefficient are summed by stratum and the sums are compared with the stratum sums selected from the database. Based on these differences,the weighting coefficients are still corrected so that the sums match and correspond with the data of the population, that is, the annual data of Statistics Finland's structural business and financial statement statistics. After this, the enterprises' turnover data are divided to the CPA product categories they have given and are summed by industry, after which the product distribution of the industry can be formed.
18.5.1. Imputation - rate
not available
18.5.2. Use of a method to deal with non-response (both unit and item non-response)
The effect of non-response is corrected by calculating the non-response correction coefficient for each stratum based on the numbers of the responding enterprises.
18.5.3. Share of estimated values
not available
18.6. Adjustment
The accounting year is not necessarily same as the calendar year. Corrections are made to convert accounting year data to calendar year data if the accounting year is longer than calendar year.
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
20 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 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.
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.
Finland (FI)
2023
The data refers to fiscal year. The different financial years are converted to correspond to the statistical year.
IFATS is subset of SBS series. In SBS series metadata report states following: the main source of errors is non-response. Admistrative data should be very precise and it is analysed and locked 1 month before national publication. Final data lockdown date is 19th December 2024. Before Eurostat data delivery all the necessary corrections are made and if some corrections have been made they are corrected to eurostat data delivery. In my opinion IFATS data is quite precise and accurate. My assessment over IFATS data is very good. C. UCI is information is from administrative data and if not available from there it is carefully analysed using enterprise annual reports, web pages, egr and most reliable source is always chosen.
The influence of non-sampling error is small. The unit non-response are imputed based on last years data or nearest neighbour with distance measure. In Business Services data unit non-response is taken into account by grossing up the data. The recorded unit non-response rate: Low The bias of the estimate: Small bias Coverage error: Almost none Out of scope units: For the reference year 2021 the business Register annual Quality Control Survey covered 1417 legal units. The response rate was 61,5 percent. Based on the survey results 3 percent were found to be misclassified (5-digit level). The statistics on Business Services do not describe service production comprehensively due to the employee limitations of the respondent group. The product distributions of enterprises in the stratum with the smallest number of employees but fewer than five persons and not belonging to the inquiry group may differ from the product distributions of enterprises belonging to the respondent group of the stratum, and this may cause inaccuracy in the estimated product distribution of the industry if the turnover of these enterprises accounts for a large share of the industry's turnover.
A significant factor affecting the reliability of the Business Services statistics is the ability of the respondents to break down turnover according to the CPA classification. Efforts have been made to manage this risk by specifying the classification and the descriptions of the categories.
Number of enterprises and employment variables are recorded in absolute figures.
Monetary data of enterprises are recorded in thousands in EUR and disseminated in million of EUR.
IFATS is subset of sbs series. SBS metadata report states following.
Imputation methods: Tax data is treated automatically using mass editing and imputation techniques. The errors and outliers are edited in following order: Logical edits, Outlier detection, Small errors (<5%) from turnover are re-scaled. Two types of imputation methods are used in the SBS data. First type is donor imputation which is applied for unit non-response in tax data. The data is imputed using last-years data, VAT-data or nearest neighbour imputation with distance measure. Unit non-response includes those units that have not sent their accounting data to Tax Authority: Second step is item non-response. Item non-response refer to mass imputation of the variables included in direct inquiry and not received fromTax Authority. Primary method used is regression imputation with outlier detection and weighting if necessary. Survey data is mainly checked manually. It forms the basis for imputation process of some of the variables. Tax data and survey data is compiled together thus forming our structural business data. For Business Services data: The effect of non-response is corrected by calculating the non-response correction coefficient for each stratum based on the numbers of the responding enterprises. When the data are raised to the whole population, enterprises' turnover data are picked again from the same database of Statistics Finland that is used in the compilation of other business statistics. The enterprise-specific sample weight is multiplied by the stratum-specific non-response correction weight calculated in the first stage, which produces a preliminary weighting coefficient for the enterprise. The turnover data raised with this weighting coefficient are summed by stratum and the sums are compared with the stratum sums selected from the database. Based on these differences,the weighting coefficients are still corrected so that the sums match and correspond with the data of the population, that is, the annual data of Statistics Finland's structural business and financial statement statistics. After this, the enterprises' turnover data are divided to the CPA product categories they have given and are summed by industry, after which the product distribution of the industry can be formed.
IFATA is subset of sbs series.
Business register, a direct inquiry, Financial supervisory authority, VAT data and Tax Authority administrative data. Administrative data from Tax Administration provides financial statements data for all enterprises (main source). The BR provides information on principal activity and number of personnel. The direct inquiry for other than Business Services data is a census which covers all enterprises with more than 60 employees. Some enterprises with more than 10 employees are also included in sample survey. The direct inquiry data are mainly collected for the national data needs (more detailed data on certain variables/items for the calculation of national accounts).
Data source soverview Survey data yes VAT data yes Tax data yes Financial statements yes Other sources, please specify: Financial supervisory authority data Comment Main data source is Business tax data.We use survey data only for specific variables missing from the administrative 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+… months after the end of the reference period.
Data transmission to Eurostat takes place at t+20 months.
Data dissemination at national level takes place at t+12 months.
