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.
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.
Coverage of Special Purpose Entities (SPE):
For reference year 2023, there were 4 SPEs in the NSBR: all SPEs are classified in NACE activity 64201, and in the size group by persons employed 1-9.
NSBR receives information about SPEs from the central bank (Bank of Estonia), which deals with identifying them and determines the kind of activity.
Treatment of equally shared control:
Firstly the UCI country of the legal person(s) (or the chain of control) is determined.
If an enterprise is controlled by
a) a juridical person and a natural person from different countries with equally 50% of the voting rights, and no additional information is available then the UCI is attributed to the UCI unit country of a juridical person.
b) two natural persons, one from Estonia and the other from another country with equally 50% of the voting rights, and no additional information is available then the UCI is attributed to Estonia.
c) two juridical persons, one from Estonia and the other from another country with equally 50% of the voting rights and no additional information is available, the UCI is attributed to Estonia.
d) two juridical persons from different EU Member States with equally 50% of the voting rights and no additional information is available, then the UCI is coded as equally-shared control of UCIs of more than one Member State.
e) juridical persons from EU Member State and a juridical person from non-EU Member State with equally 50% of the voting rights and no additional information is available, then the UCI is attributed to EU Member State.
Treatment of multiple minority ownership:
In case of absence of the majority ownership (three or more owners), firstly the UCI country of the legal person is determined.
Then,
a) if the total of voting rights of the Estonian owners is 50% or more and no additional information is available, the UCI is attributed to Estonia;
b) if the total of voting rights of owners from one country is more than 50% and no additional information is available, the UCI is attributed to the country.
c) if the total of voting rights of owners from different EU Member States is more than 50% and no additional information is available, the UCI is coded as equally-shared control of UCIs of more than one Member State.
d) if the total of voting rights of owners from different countries is more than 50% and owners from different EU Member States have majority and no additional information is available, the UCI is coded as equally-shared control of UCIs of more than one Member State.
e) if the total of voting rights of owners from different countries is more than 50% and owners from extra –EU Member States have majority and no additional information is available, the UCI is coded as extra EU-27 not allocated .
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
Estonia
3.8. Coverage - Time
Data are available from 2003 till 2023.
2003-2007 NACE Rev. 1.1 activity classification was in use. Starting from 2008 NACE Rev. 2 was implemented.
2003-2020 a threshold was in use – data series contained only enterprises with 20 and more persons employed (i.e. only the totally surveyed part of Estonian SBS data).
Starting from the reference year 2021, there are no more a threshold, i.e. enterprises of all size classes are included.
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 euros.
Data refers to the calendar year, which in some cases corresponds to the fiscal year.
6.1. Institutional Mandate - legal acts and other agreements
The dissemination of data collected for the purpose of producing official statistics is guided by the requirements provided in § 34 and § 35 of the Official Statistics Act.
7.2. Confidentiality - data treatment
According to the Official Statistics Act and the regulation of the Government of the Republic of Estonia, the data are published and transmitted without characteristics that permit identification of the respondents. The data have to be classified into groups of at least three persons (primary confidentiality — too few enterprises), while the share of data relating to each person in aggregate data does not exceed x% (primary confidentiality — one enterprise dominates the data, x denotes dominance limit in Statistics Estonia and its value is confidential). The criteria of dominance for turnover, gross investment in tangible goods and personnel costs was applied. To protect the primary confidential cells, the secondary confidential cells were determined by using R package sdcTable. Only the number of units is published in case of confidentiality reasons that preclude the publication of the data. The confidential data in the total database is caused by the detailed activity and employment size class breakdown. As Estonia is a small country the rate of confidential cells is considerable.
Confidentiality rules
a) Primary confidentiality rules:
Less than three enterprises or the share of data relating to each enterprise in aggregate data does not exceed x% (one enterprise dominates the data)
b) Secondary confidentiality rules:
To protect the primary confidential cells
Rate of suppressed cells
2021
2022
2023
S of required cells
25 328
22 968
25 328
S of confidential cells
6 434
6 168
6 762
% of confidential cells
25,40
26,85
26,70
S of Non-Zero cells provided
13 833
12 231
14 699
% out of non-zero cells provided
46,51
50,43
46,00
S of Non-Blank cells provided
23 262
22 968
23 262
% out of non-blank cells provided
27,66
26,85
29,07
Please see Table 7.2. in Annexes.
8.1. Release calendar
National IFATS data are published once a year at the end of August.
Release dates are announced in September of the year preceding the year of data publication in release calendar on the Statistics Estonia website.
8.2. Release calendar access
Release calendar can be found at the website of Statistics Estonia.
8.3. Release policy - user access
In line with the Community legal framework and the European Statistics Code of Practice, Statistics Estonia disseminates national Inward FATS statistics on Statistics Estonia’s website respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably.
According to the Official Statistics Act, a producer of official statistics shall disseminate official statistics pursuant to the release calendar published on its website.
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
News releases are not prepared.
10.2. Dissemination format - Publications
Publications are not prepared, the data are published in the statistics database on the website only.
"EM60: FINANCIAL STATISTICS OF ENTERPRISES (WITH 20 OR MORE PERSONSEMPLOYED) BY ECONOMIC ACTIVITY AND CONTROLLING COUNTRY" by years from 2018 to 2020
and
"EM61: FINANCIAL STATISTICS OF ENTERPRISES BY ECONOMIC ACTIVITY AND CONTROLLING COUNTRY" (from 2021):
2018
2019
2020
2021
2022
2023
2024
462
500
401
217
224
117
114
10.4. Dissemination format - microdata access
Micro-data are disseminated if the data are used for scientific purposes pursuant to the provisions of § 38 of the Official Statistics Act.
10.5. Dissemination format - other
Not available
10.5.1. Metadata - consultations
Not available.
10.6. Documentation on methodology
ESMS (Euro-SDMX Metadata Structure) metadata based on the SDMX Cross-Domain Concepts is published on the Estonian Statistics website in Estonian and English:
Additional information related to FATS is published in the methodology section of the website:
ESMS (Euro-SDMX Metadata Structure) metadata based on the SDMX Cross-Domain Concepts is published on the Estonian Statistics website in Estonian and English.
10.6.3. Web links if metadata are published electronically
ESMS (Euro-SDMX Metadata Structure) metadata based on the SDMX Cross-Domain Concepts is published on the Estonian Statistics website in Estonian and English:
Additional information related to FATS is published in the methodology section of the website:
To assure the quality of processes and products, Statistics Estonia applies the EFQM Excellence Model, EU Statistics Code of Practice and the ESS Quality Assurance Framework (QAF). Statistics Estonia is also guided by the requirements provided for in § 7. „Principles and quality criteria of producing official statistics” of the Official Statistics Act.
ESMS (Euro-SDMX Metadata Structure) metadata based on the SDMX Cross-Domain Concepts is published on the Estonian Statistics website in Estonian and English. Including Financial statistics of foreign affiliates, statistical activity code - 20319, on which IFATS is based.
To assure the quality of processes and products, Statistics Estonia applies the EFQM Excellence Model, EU Statistics Code of Practice and the ESS Quality Assurance Framework (QAF). Statistics Estonia is also guided by the requirements provided for in § 7. „Principles and quality criteria of producing official statistics” of the Official Statistics Act.
11.2. Quality management - assessment
Statistics Estonia performs all statistical activities according to an international model (Generic Statistical Business Process Model – GSBPM). According to the GSBPM, the final phase of statistical activities is overall evaluation using information gathered in each phase or sub-process (this information includes, among other things, feedback from users, process metadata, system metrics and suggestions from employees). This information is used to prepare the evaluation report which outlines all the quality problems related to the specific statistical activity and serves as input for improvement actions.
The overall assessment of the quality of FATS data is good. Data quality is in accordance with principles of accuracy and reliability, timeliness and punctuality, coherence and compatibility. The main strength of the Inward FATS is the consistency with the SBS and national statistical business register data.
12.1. Relevance - User Needs
Users of Inward FATS are: European Commission services, international organisations, ministries, chambers of commerce, central bank, journalists etc.
12.2. Relevance - User Satisfaction
No consumer research has been conducted.
12.3. Completeness
Some indicators or groupings are not presented based on the 1%-rule and the derogation.
On the basis of the 1%-rule referred in the EBS Regulation, Statistics Estonia requested for exemption from transmitting the following variables:
Intramural R & D expenditure
R & D personnel
According to ex-ante assessment for FATS carried out by Eurostat, the condition has been fulfilled partially in the three years prior to the reference year. In particular, the 3-year average has been above 1% for the ‘Number of employees and self-employed persons’ in NACE Division C26 and aggregates C13 to C15 and C16 to C18 for Inward FATS.
Therefore, of the aforementioned variables, only data for NACE Division C26 and the aggregates C13–C15 and C16–C18 were transmitted.
Derogation is according to COMMISSION IMPLEMENTING DECISION (EU) 2021/1003 of 18 June 2021granting derogations to certain Member States with respect to the transmission of statistics pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council and Commission Implementing Regulation (EU) 2020/1197.
This derogation applied to the following variables for reference years 2021–2022:
Total purchases of goods and services
Purchases of goods and services for resale
Net turnover
Value of output
Value added
in the NACE Section K activities
division 66 and
groups 64.2, 64.3, 64.9.
As a result, NACE Section K and special aggregates comprising Section K did not include Division K66 and Groups K64.2, K64.3, and K64.9 for the reference years 2021–2022.
12.3.1. Data completeness - rate
Please see Table 12.3.1. in Annexes.
13.1. Accuracy - overall
The overall accuracy of the results can be assessed as good. The Inward FATS data are a subset of SBS data i.e. data compiled in the framework of the SBS surveys. Among them, non-financial enterprises survey EKOMAR has the largest by number of enterprises. The data is obtained by combining the administrative information and statistical questionnaires. For characteristics missing in administrative information model based estimate is used, also donor imputation and mean value imputation methods are applied. Modeling is primarily used to find the variables total purchases of goods and services, purchases of goods and services for resale, as well as some components to calculate the value of output and value added.
The most important sources of errors are nonresponse and modelling errors when using administrative information.
UCI information is received from statistical business register and also asked in SBS questionnaire. Data on the Internet, in the media, in annual bookkeeping reports is used. In case of contradictory information about UCI of different sources the unit is studied in detail (demographic events, websites and annual bookkeeping reports are investigated etc.).
13.1.1. Use of residual geographic codes (Extra EU-27 not allocated, etc.)
The residual geographic codes are used to a small extent, no more than 0.3%
Please see Table 13.1. in Annexes.
13.1.2. UCI Approach applied to identify the relevant population of reporting units
The Ultimate Controlling Institutional Unit (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”
UCI is identified in statistical business register based on ownership links as of December, 31.
13.1.4. Description of other method used to improve the accuracy of the UCI
IFATS uses UCI information from the national statistical business register (NSBR), the EGR (Eurogroups Register FATS Interface) is also consulted.
In the National Statistical Business Register, the UCI information is received from administrative sources and also asked in SBS questionnaire. Data on the Internet, in the media, in annual bookkeeping reports is used. In case of contradictory information about UCI of different sources the unit is studied in detail (demographic events, websites and annual bookkeeping reports are investigated etc).
13.2. Sampling error
Not applicable (census)
13.2.1. Sampling error - indicators
Not applicable.
13.3. Non-sampling error
Inward FATS data are a subset of SBS data i.e. data produced in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
Data is available for all active enterprises:
received from administrative source or
collected with the statistical questionnaire or
imputed (mean value imputation, donor imputation)
The influence of non-sampling error is small.
13.3.1. Coverage error
Inward FATS data is a subset of SBS data, i.e. data compiled as part of SBS studies. SBS data are obtained by combining administrative information and statistical questionnaires.
The most important aspects of coverage relate to the availability of administrative information, especially annual reports.
While large enterprises (20 or more persons employed) are included among those submitting statistical questionnaires, in the case of small enterprises (with less than 20 persons employed) only administrative data, mainly annual reports, are used. In the case of small enterprises, the annual report can be the only source of information about their operations (because they are not tax liable). If the annual report has not been submitted, there is no basis for their inclusion in the statistics.
13.3.1.1. Over-coverage - rate
Not available
13.3.1.2. Common units - proportion
The Inward FATS data are a subset of SBS data i.e. data collected in the framework of the SBS surveys. The data is obtained by combining the administrative information and statistical questionnaires. The main administrative source is companies’ annual reports from Commercial Register (under Ministry of Justice).
For SBS, non-financial enterprises survey EKOMAR has the largest by number of enterprises. Annual reports are used in the pre-filling of statistical questionnaires in the data collection system eSTAT.
Non-financial enterprises that submitted a statistical questionnaire EKOMAR and had also submitted an annual report (%)
2021
90,3
2022
93,5
2023
92,3
13.3.1.3. Misclassification errors
Economic indicators come from SBS surveys, UCI country information from the National Statistical Business Register (NSBR).
In the course of additional data processing, the UCI country information is checked for enterprises with larger numbers of persons employed if
a) the UCI country is different compared to last year
b) it is a new enterprise.
UCI country errors can be related to mistakenly using UBO country instead of UCI. Also in the case of long control chains, by mistakenly using an intermediate controlling country.
13.3.1.4. Under- and over-coverage problems
Not available
13.3.2. Measurement error
Not available
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
The inward FATS data are compiled from SBS surveys (survey for non-financial enterprises, surveys for insurance companies, surveys for financial enterprises).
Please see Table 13.3.3. in Annexes.
13.3.3.2. Item non-response - rate
Please see Table 13.3.3. in Annexes.
13.3.4. Processing error
Statistics Estonia uses the web-based electronic data collection system eSTAT. eSTAT gives to data provider a possibility before submission of questionnaire to check the correctness of data and correct the errors. There are mostly arithmetical checks - completeness, internal consistency, plausibility checks.
The data processing information system VAIS is used for further data processing. Data editing continues, using additional arithmetic checks and if the data is available, comparisons with the data of the previous period.
13.3.5. Model assumption error
For characteristics missing in administrative information model based estimate is used. Modeling is primarily used to find the variables total purchases of goods and services, purchases of goods and services for resale, as well as some components to calculate the value of output and value added.
The possible occurrence of errors is related to the choice of the most suitable data source for modeling (eg previous year data, base period data, data of the different size group).
14.1. Timeliness
IFATS statistics are calculated annually for reference year T.
Data collection takes place at t+6 months after the end of the reference period (SBS data).
Data transmission to Eurostat takes place at t+20 months.
Data dissemination at national level takes place at t+20 months.
14.1.1. Time lag - first result
t+20 months
14.1.2. Time lag - final result
t+20 months
14.2. Punctuality
Time lag between the actual delivery of the data and the target date when it should have been delivered - 0 days.
14.2.1. Punctuality - delivery and publication
Inward FATS 2023 data were transmitted to Eurostat on August 31 (t+20 months).
Inaccuracies were identified in the research and development indicators – IM_RND_EXPN and RND_PER – for the NACE groupings C13–C15, C16–C18, and Division C26. The entire table was updated and resent on 4 September 2025 (i.e. 4 days after the deadline). Corrections were made to the R&D indicators for these NACE sectors where the counterpart countries were W1, W2, B6, D6, DE, FI, NO, SE, and US.
The table "EM061: FINANCIAL STATISTICS OF ENTERPRISES BY ECONOMIC ACTIVITY AND CONTROLLING COUNTRY" was published in the statistics database, which is on the Estonian statistics website, on the date specified in the publication calendar, August 30 (t+20 months).
15.1. Comparability - geographical
Not applicable
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
The length of the time series is 2003-2023.
During this period
different versions of the NACE,
threshold based on the number of persons employed,
the 1% rule
have been used.
15.2.1. Length of comparable time series
Length of time series: 2003-2023
Length of comparable time series:
2003-2007,
2008-2020,
2021-2022,
2023-onvards.
15.2.2. Reasons and differences in concepts and measurement methods for breaks in time series
2003-2007 NACE Rev. 1.1 activity classification was in use. Starting from 2008 NACE Rev. 2 was implemented.
For 2003-2020 inward FATS, a threshold was in use – data series contained only enterprises with 20 and more persons employed (i.e. only the totally surveyed part of Estonian SBS data).
Starting from the reference year 2021, there are no more a threshold, i.e. enterprises of all size classes are included.
Some indicators or groupings are not presented based on the derogation or the 1% rule.
For the reference years 2021–2022, NACE Section K and special aggregates comprising NACE Section K did not include Division K66 and Groups K64.2, K64.3, and K64.9.
Based on the 1% rule, R&D variables were not included, except for NACE Division C26 and the aggregates C13–C15 and C16–C18.
15.3. Coherence - cross domain
Inward FATS data is a subset of SBS data i.e. variable values are the same in both data set. The main stratification indicators - UCI country, kind of activity, employment size class - are obtained from the National Statistics Business Register (NSBR).
This has created coherence between IFATS, SBS and NSBR.
15.3.1. Coherence - sub annual and annual statistics
Not applicable
15.3.2. Coherence - National Accounts
Not available
15.3.3. Coherence – National Statistical Business Register (NSBR)
IFATS uses UCI, kind of activity and employment information from the national statistical business register (NSBR).
15.3.4. Coherence – Structural Business Statistics (SBS)
The Inward FATS data are a subset of SBS data - no inconsistency.
15.3.5. Coherence – R & D
The 1% rule applies to R&D variables. If, the rule does not apply, the data from R&D survey are used - no inconsistency.
15.3.6. Coherence – Foreign Direct Investment (FDI)
Not available
15.3.7. Coherence – EuroGroups Register (EGR)
IFATS uses UCI information from the national statistical business register (NSBR). There may be inconsistencies between NSBR and EGR. NSBR uses EGR to verify the information on GGH and GDC country but not always can data from EGR be accepted. In some cases data in NSBR is more up-to-date.
15.4. Coherence - internal
No inconsistencies
There are no separate questionnaires for Inward FATS data collection. Only the UCI country variable, which is in the non-financial enterprises’ questionnaire (EKOMAR), is directly related to the respondent burden of Inward FATS.
Inward FATS data are a subset of SBS data i.e. data collected in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS. Data from the statistical business register and data collected with the non-financial enterprises survey questionnaire (EKOMAR) are used to determine the UCI country.
Irregular revisions are unplanned and are made to correct significant errors.
17.2.1. Data revision - average size
Mean Absolute Percentage Error (MAPE)
2019
0
2020
0
2021
0
2022
0
Please see Table 17.2.1 in Annexes.
18.1. Source data
Inward FATS data are a subset of SBS data i.e. data collected in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
There is a system for extracting data about the UCI unit country from the Business Registers’ Enterprise Groups Register and adding the information to enterprises in the SBS population (to the SBS variables).
18.1.1. Methodological approach
Dependence on:
SBS — 100% (economic information, except R&D variables),
Business Register (for statistical purposes) — 100% (UCI information).
Legal Business Register, annual bookkeeping reports were used to update the information in Business Registers’ Enterprise Groups Register
18.1.2. Use of cut-off thresholds
For 2003-2020 inward FATS, a threshold was applied – the data series contained only enterprises with 20 and more persons employed (i.e. only the totally surveyed part of Estonian SBS data).
Starting from the reference year 2021, the threshold is no longer applied, i.e. enterprises of all size classes are included.
18.2. Frequency of data collection
Annual.
18.3. Data collection
Statistics Estonia uses the web-based electronic data collection system eSTAT, thereof for SBS surveys. eSTAT enables submission of statistical reports on-line, thereof pointing to unanswered questions and errors made upon completing a report.
Source to define your population:
0% census survey
0% sample survey
100% Structural Business Statistics (SBS)
0% Foreign Direct Investment (FDI)
0% 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
100% Structural Business Statistics (SBS)
0 % Foreign Direct Investment (FDI)
0 % 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: ...)
To obtain SBS data on non-financial enterprises (NACE B- S excluding K), several questionnaires (EKOMAR) are used, which are slightly modified according to the enterprise’s principal activity. As an example, a questionnaire and instructions for construction enterprises in pdf form ekomar-f41-2023-year.
For insurance companies (NACE 651), annual and quarterly statistical questionnaires are used. By combining the data collected through these questionnaires, SBS indicators are derived. Annual questionnaire in pdf form: Insurance 2023. year, quarterly questionnaire in pdf form: Insurance 2023. quarter
The pdf questionnaires are for information only.
To collect data from enterprises, Statistics Estonia uses the web-based electronic data collection system eSTAT - environment for electronic data submission. In eSTAT statistical questionnaires are prefilled with data from annual reports (annual financial statements). Variables not available in administrative source are added by data providers. eSTAT gives to data provider a possibility before submission of questionnaire to check the correctness of data and correct the errors. There are mostly arithmetical checks - completeness, internal consistency, plausibility checks.
For enterprises that do not have to submit statistical questionnaires, data from annual reports are used or, if they are not available, data are imputed.
18.4. Data validation
Inward FATS data are a subset of SBS data i.e. data produced in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
Statistics Estonia uses the web-based electronic data collection system eSTAT which gives to data provider a possibility before submission of report to check the correctness of data and correct the errors. There are mostly arithmetical checks.
In data processing phase (using data processing information system VAIS) the data editing continues by using a lot of arithmetical — completeness, internal consistency, plausibility — checks. The data are also compared with similar data from annual reports, short-term statistics, PRODCOM on unit and aggregated level.
In addition, additional checks have been created at the level of enterprises using R software, which also create reports in Excel form for enterprises with errors and warnings.
At the aggregate data level - the field of activity - the data is compared with the previous year. For this purpose, a solution for making reports based on R and Excel has been created. Appeared errors are corrected before publication in VAIS, warnings are either corrected or a reasonable explanation is found.
Before transmission to Eurostat, data tables are checked using EDAMIS (Electronic Data Files Administration and Management Information System) both individually and between tables (inter-series checks).
In the course of additional data processing, the UCI country information is checked for enterprises with larger numbers of persons employed if
the UCI country is different compared to last year;
it is a new enterprise.
18.5. Data compilation
Inward FATS data are a subset of SBS data i.e. data produced in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
Starting from reference year 2019 SBS data is available for all active enterprises at individual level.
The methodology to obtain the data for non-financial enterprises (survey EKOMAR) is combining the statistical questionnaire and administrative information. For imputation the available information from administrative source i.e. in annual reports are used. For characteristics missing in annual reports model based estimate is used. In case of absence of annual reports also donor imputation and mean value imputation methods are applied.
All insurance companies (NACE 65) are surveyed.
Methodology for obtaining financial service and auxiliary to financial services activities’ enterprises is statistical questionnaire combined with administrative information. Data on central banking (NACE 6411) are received from the annual report. Data on other monetary intermediation (NACE 6419) are received from Bank of Estonia. For other financial service and auxiliary to financial services activities’ enterprises data on received from statistical surveys and from administrative source i.e. in annual reports are used.
18.5.1. Imputation - rate
Sources of data, including imputation:
Source
Number of enterprises
Non-financial enterprises (NACE B-S, excluding K and O)
Annual reports (administrative data)
90,5%
Statistical questionnaire
2,6%
Previous year data
0,1%
Data from another statistical survey
0,0%
Donor imputation
0,0%
Combined method
0,6%
Mean value imputation
6,2%
Financial enterprises (NACE K641)
Administrative data
100%
Financial enterprises (NACE K642, 643, 649, 66)
Annual reports (administrative data)
100%
Insurance (NACE K651)
Statistical questionnaire
100%
Pension funds (NACE K653)
Annual reports (administrative data)
100%
18.5.2. Use of a method to deal with non-response (both unit and item non-response)
For imputation the available information from administrative source i.e. in annual reports is used. For characteristics missing in annual reports model based estimate is used.
In case of absence of annual reports also donor imputation and mean value imputation methods are applied.
18.5.3. Share of estimated values
IFATS main variables according to the sources:
Source
Number of enterprises
Number of employees and self-employed persons
Net turnover
Non-financial enterprises (NACE B-S, excluding K and O)
Annual reports (administrative data)
90,5%
46,5%
34,9%
Statistical questionnaire
2,6%
48,4%
60,7%
Previous year data
0,1%
0,6%
0,4%
Data from another statistical survey
0,0%
0,0%
0,0%
Donor imputation
0,0%
0,0%
0,1%
Combined method
0,6%
0,5%
1,1%
Mean value imputation
6,2%
4,0%
2,7%
Financial enterprises (NACE K641)
Administrative data
100%
100%
100%
Financial enterprises (NACE K642, 643, 649, 66)
Annual reports (administrative data)
100%
100%
100%
Insurance (NACE K651)
Statistical questionnaire
100%
100%
100%
Pension funds (NACE K653)
Annual reports (administrative data)
100%
100%
100%
18.6. Adjustment
Inward FATS data are a subset of SBS data i.e. data produced in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
SBS data refer to a calendar year (or in some exceptional cases, a 12-month period beginning or ending in the reporting 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
22 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.
Coverage of Special Purpose Entities (SPE):
For reference year 2023, there were 4 SPEs in the NSBR: all SPEs are classified in NACE activity 64201, and in the size group by persons employed 1-9.
NSBR receives information about SPEs from the central bank (Bank of Estonia), which deals with identifying them and determines the kind of activity.
Treatment of equally shared control:
Firstly the UCI country of the legal person(s) (or the chain of control) is determined.
If an enterprise is controlled by
a) a juridical person and a natural person from different countries with equally 50% of the voting rights, and no additional information is available then the UCI is attributed to the UCI unit country of a juridical person.
b) two natural persons, one from Estonia and the other from another country with equally 50% of the voting rights, and no additional information is available then the UCI is attributed to Estonia.
c) two juridical persons, one from Estonia and the other from another country with equally 50% of the voting rights and no additional information is available, the UCI is attributed to Estonia.
d) two juridical persons from different EU Member States with equally 50% of the voting rights and no additional information is available, then the UCI is coded as equally-shared control of UCIs of more than one Member State.
e) juridical persons from EU Member State and a juridical person from non-EU Member State with equally 50% of the voting rights and no additional information is available, then the UCI is attributed to EU Member State.
Treatment of multiple minority ownership:
In case of absence of the majority ownership (three or more owners), firstly the UCI country of the legal person is determined.
Then,
a) if the total of voting rights of the Estonian owners is 50% or more and no additional information is available, the UCI is attributed to Estonia;
b) if the total of voting rights of owners from one country is more than 50% and no additional information is available, the UCI is attributed to the country.
c) if the total of voting rights of owners from different EU Member States is more than 50% and no additional information is available, the UCI is coded as equally-shared control of UCIs of more than one Member State.
d) if the total of voting rights of owners from different countries is more than 50% and owners from different EU Member States have majority and no additional information is available, the UCI is coded as equally-shared control of UCIs of more than one Member State.
e) if the total of voting rights of owners from different countries is more than 50% and owners from extra –EU Member States have majority and no additional information is available, the UCI is coded as extra EU-27 not allocated .
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.
Estonia
Data refers to the calendar year, which in some cases corresponds to the fiscal year.
The overall accuracy of the results can be assessed as good. The Inward FATS data are a subset of SBS data i.e. data compiled in the framework of the SBS surveys. Among them, non-financial enterprises survey EKOMAR has the largest by number of enterprises. The data is obtained by combining the administrative information and statistical questionnaires. For characteristics missing in administrative information model based estimate is used, also donor imputation and mean value imputation methods are applied. Modeling is primarily used to find the variables total purchases of goods and services, purchases of goods and services for resale, as well as some components to calculate the value of output and value added.
The most important sources of errors are nonresponse and modelling errors when using administrative information.
UCI information is received from statistical business register and also asked in SBS questionnaire. Data on the Internet, in the media, in annual bookkeeping reports is used. In case of contradictory information about UCI of different sources the unit is studied in detail (demographic events, websites and annual bookkeeping reports are investigated etc.).
Number of enterprises and employment variables are recorded in absolute figures.
Monetary data of enterprises are recorded in thousands euros.
Inward FATS data are a subset of SBS data i.e. data produced in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
Starting from reference year 2019 SBS data is available for all active enterprises at individual level.
The methodology to obtain the data for non-financial enterprises (survey EKOMAR) is combining the statistical questionnaire and administrative information. For imputation the available information from administrative source i.e. in annual reports are used. For characteristics missing in annual reports model based estimate is used. In case of absence of annual reports also donor imputation and mean value imputation methods are applied.
All insurance companies (NACE 65) are surveyed.
Methodology for obtaining financial service and auxiliary to financial services activities’ enterprises is statistical questionnaire combined with administrative information. Data on central banking (NACE 6411) are received from the annual report. Data on other monetary intermediation (NACE 6419) are received from Bank of Estonia. For other financial service and auxiliary to financial services activities’ enterprises data on received from statistical surveys and from administrative source i.e. in annual reports are used.
Inward FATS data are a subset of SBS data i.e. data collected in the framework of the SBS surveys (non-financial enterprises survey EKOMAR, surveys for insurance companies, surveys for financial service and auxiliary to financial services activities enterprises) are used to produce IFATS.
There is a system for extracting data about the UCI unit country from the Business Registers’ Enterprise Groups Register and adding the information to enterprises in the SBS population (to the SBS variables).
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+6 months after the end of the reference period (SBS data).
Data transmission to Eurostat takes place at t+20 months.
Data dissemination at national level takes place at t+20 months.
Not applicable
The length of the time series is 2003-2023.
During this period
different versions of the NACE,
threshold based on the number of persons employed,
