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.
Lamacska cesta 3/C, P. O. Box 67 l 840 00 Bratislava 4 l Slovak Republic
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
30 October 2025
2.2. Metadata last posted
30 October 2025
2.3. Metadata last update
30 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.
Coverage of Special Purpose Entities (SPE): SPE are not identified in the enterprise population.
Treatment of equally shared control: In some cases we include them into the aggregates Z7 (Equally-shared control of UCIs (ultimate controlling institutional units of a foreign affiliate) of more than one EU member state) and Z8 (Extra-EU (changing composition) not allocated) on the basis of information on residence of these UCI.
Treatment of multiple minority ownership: In exceptional cases where no partner has more than 50% of ownership or we have no information about country of residence we allocate data to SK.
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
Slovak Republic
3.8. Coverage - Time
Statistical Office of the Slovak Republic prepared the first data files on FATS for the reference year 2003 in the frame of Trasition Facility program. The data was compiled in the first shot concept and only for enterprises with 20 and more employees.
IFATS data for the reference years 2004 - 2009 were compiled using UCI concept and they include also estimation for small enterprises with less than 20 employees.
IFATS data for 2010 reference year onwards are compiled by combination of statistical surveys and administrative data (tax returns/financial statements data and social insurance data) including the data on natural persons.
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.
2023
6.1. Institutional Mandate - legal acts and other agreements
Right to collect data in general is governed by the Slovak National Council law No 540/2001(Digest) on the State statistics as amended and supplemented by further regulations. The obligation to provide data is stated in the Statistical Law and its provisions (Programme of State Statistical Surveys), which is fixed for a 3-year period.
The Statistical Office of the Slovak Republic is responsible for the protection of confidential data obtained and guarantees their use exclusively for statistical purposes. In accordance with the Act on State Statistics No. 540/2001 Coll. §2g and §30, the Statistical Office of the SR may not publish confidential statistical data, but only information resulting from the aggregation of confidential statistical data, which does not allow direct or indirect identification of the reporting unit. Statistical Office of the SR has introduced principles and procedures for the protection of confidential data in internal directives and instructions. The directive on the protection of confidential statistical data regulates the method of management and implementation of activities related to ensuring the protection of confidential statistical data in the Statistical Office of the Slovak Republic. The methodological instruction of the Statistical Office of the Slovak Republic regulates specific methods and parameter values used in the protection of confidential statistical data of individual statistical surveys and data sets.
The primary and secondary confidentiality data protection is applied manually bearing in mind the minimum data protection treatment and finally validated by the Eurostat validation software based on the set up rules.
8.1. Release calendar
The full set of IFATS variables is transmitted to Eurostat. In a case of an inquiry from users they are advised to consult Eurostat website.
8.2. Release calendar access
Not applicable
8.3. Release policy - user access
In line with the Community legal framework and the European Statistics Code of Practice, Statistical Office of the Slovak Republic disseminates national IFATS statistics on Eurostat website respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably.
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
The full set of IFATS variables is transmitted to Eurostat.
10.2. Dissemination format - Publications
please consult concept 10.1
10.3. Dissemination format - online database
Not applicable
10.3.1. Data tables - consultations
not applicable
10.4. Dissemination format - microdata access
Micro-data are not disseminated.
10.5. Dissemination format - other
The full set of IFATS variables is transmitted to Eurostat annually 20 months after the reference year. The IFATS data are provided to Eurostat in order to be used in European aggregates and to be released as national data.
Statistical questionnaires including methodological guidelines and explanations of variables and methodological explanations within the Glossary of the statistical terms are published on the web portal of the Statistical Office of the SR. Each publication contains methodological explanations and a contact for the information service of the Statistical Office of the SR.
10.6.1. Metadata completeness - rate
All relevant metadata elements required by the EBS Regulation are provided.
Following internal project documentation exists for the compilation of statistical outputs in Slovak language:
technical projects within the Integrated Statistical Information System;
methodological guidelines for applying mathematical-statistical methods for statistical surveys;
methodological guidelines for quality indicators of statistical outputs and statistical processes.
11.1. Quality assurance
The Quality policy is defined and publicly accessible in the Quality Declaration and Quality Policy documents. The Quality Declaration expresses the basic ideas and commitments of the President and top management of the Statistical Office of the Slovak Republic for the Quality Policy as well as increasing efficiency and effectiveness of the integrated management system of the Statistical Office of the SR.
Quality policy is based on the mission of the Statistical Office of the Slovak Republic to provide high quality and objective statistical products and services by keeping confidentiality of statistical data and by minimising burden on interested parties using effectively existing resources with the aim to support improvement of the information and intellectual capital of our customers. In this way we want to contribute to reduce risks and improve effectiveness in their decision making processes and so to support the sustainable development of the Slovak Republic as the part of EU.
The Quality manual describes the documented procedures of the quality system that are used for implementation and continuous improvement of the quality management system in Statistical Office of the SR. It contains a description of the quality management system and the fulfilment of requirements ISO 9001 standards. Application of the manual in practice ensures that all activities that have an impact on the quality of the products created are planned, managed, reviewed, evaluated and meet requirements. It is available only in slovak.
Quality manual
The European Statistics Code of Practice is the basis of the common quality framework of the European Statistical System. It is a self-regulatory tool and it is based on 16 Principles covering the institutional environment, statistical processes and statistical outputs. A set of indicators of best practices and standards for each of the Principles provides guidelines and benchmarks for reviewing the implementation of the Code of Practice, thus increasing transparency within the European Statistical System.
Coverage, reference period, data collection, control and data processing are in line with the Eurostat methodological guidelines. The data collection process is conducted in the Integrated statistical information system called ISIS. SOSR creates technical projects of the statistical surveys describing data collection and its evaluation, including a description of statistical controls and algorithms within the integrated ISIS. The data collection process is ensured by the regional offices of the SOSR during the phase of electronic data collection, ensure using statistical controls and algorithms the data collection process itself. Data validation is done during the data collection, processing and validation of relevant data by the SOSR experts. A data comparison is done with previous periods. Statistics are available in the system to evaluate the quality of the completed questionnaires, the number of questionnaires with errors or outliers, the number of reminders etc. SOSR also performs internal methodical audits. Evaluation of statistical surveys and methodological audits including the analysis of the results are integrated into the existing quality management system.
12.1. Relevance - User Needs
In general, The requirement to conduct consultations with users of statistical information is stipulated in the Act on State Statistics itself. Consultations during the preparation of state statistical surveys take place within the framework of the preparation of the Program of State Statistical Surveys (PSSZ). PSSZ is a generally binding legal regulation compiled by the Statistical Office of the SR in collaboration with ministries, other central authorities and state organizations and contains statistical surveys organized and carried out by the Statistical Office of the SR, ministries, other central authorities and state organizations. Statistical Office of the SR publishes the Program of state statistical surveys by decree in the Collection of Laws of the Slovak Republic. The Coordinating Council for State Statistics ensures the fulfilment of the tasks of the Statistical Office of the SR. Key users of specific statistical products are listed in the Marketing Plan, e.g. international organizations - Eurostat, OECD, UN and national institutions, e.g. National Bank of Slovakia, ministries, professional associations, enterprises etc. The IFATS data are disseminated in line with the EBS requirements to Eurostat.
12.2. Relevance - User Satisfaction
Since the 2009, SOSR carries out satisfaction surveys of customers with their products and services at two-year intervals. The goal of surveys is to determine customer satisfaction with the products and services of the SOSR, to obtain information about users, their interest and opinion on provision and quality of statistical products and services. The facts obtained are a valuable resource for the direction of other activities of the SOSR. One of the main goals defined in the Development Strategy. The goal of the SOSR is to systematically increase the value of the institution and its recognition at the national and international level. The office also monitors the fulfilment of the stated goal with the help of indicators of the credibility of the SOSR and the rate of use of the information provided by the public.
Credibility survey
Satisfaction survey
12.3. Completeness
All required complete IFATS data are provided.
12.3.1. Data completeness - rate
Please see Table 12.3.1 in the Annex at the bottom.
13.1. Accuracy - overall
The overall accuracy of the results can be assessed as good. The Inward FATS data are a subset of the structural business statistics data. The IFATS data is compiled by combining administrative information and statistical questionnaires. The technical project of data processing is part of Integrated statistical information system (ISIS). This project includes a description of all logical data controls at the microdata level performed during electronic data collection. The electronic questionnaire and information system ISIS itself provides many arithmetic and logical checks between variables, which we distinguish between serious and informative. Data collection is provided by the office of the Statistical Office of the SR in regions. After the deadline for submission of the statistical questionnaire, the reporting units that did not respond are contacted again to fulfil their legal obligation. In case of serious errors in the form, this form is not accepted and with the help of experts from the regional office its correctness is ensured so that it can enter into the data processing. Automatic validation checks during data collection and informative checks are incorporated with the aim to follow logical checks, reducing the rate of partial non-responses, anomalies and outliers. The purpose of this process is to minimize errors already in the data collection itself and subsequently during data processing. The basic step in the process of calculating unit non-response is the analysis of the population with regard to the state of activity of the reporting units. For this purpose, we use a specific classification of responses and non-responses codes. Individual codes describe active and inactive units and are assigned to each reporting unit. Subsequently, we determine the population of active units entering the data processing. After the deadline for submission of the statistical questionnaire, the reporting units that did not respond are contacted again to fulfil their legal obligation. For estimates of self-employed persons is beeing using a model approach on administrative data based. Most errors are directly consulted at regional offices with the reporting units. Therefore it is possible the overall accuracy to consider as good.
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 Approach is applied to identify the relevant population of enterprises using the information from the National Business Register ( NSBR quality report ) and EGR. The relevant UCI on the corporate concept are identified by the mean of an manual data validation and the information from the EGR.
EGR-FATS quality indicators for the reference year 2023 comparing the completenes s and accuracy of IFATS/EGR indicators:
CODE
DESCRIPTION
INDICAROR
OUTPUT.IFATS.1
Completeness of EGR = (B+C)/(B+C+D)
0.9842
OUTPUT.IFATS.2
Accuracy of UCI in EGR = (B)/(B+C)
0.9842
OUTPUT.IFATS.3
Completeness of EGR for employment = comparison of employment of units in OUTPUT.IFATS.1
0.9820
OUTPUT.IFATS.4
Completeness of IFATS from EGR perspective = (B+C)/(B+C+A)
0.9332
13.1.3. Update date (or frequency of updates) of the information regarding the country of the UCI by the “source administration”
Data files for IFATS are compiled on the basis of annual Structural Business Statistics surveys data organized by Statistical Office of the SR and administrative data.
13.1.4. Description of other method used to improve the accuracy of the UCI
Statistical Office of the SR uses the EGR as an additional data source and also administrative data and publicly available information for the compilation of the IFATS. Manual data validation of data in EGR on units whether they are active or inactive is crucial. EGR Final Frame data are used for the validation and imputation of the relevant enterprises UCI for the reference year data.
13.2. Sampling error
Sampling errors are not relevant and are not calculated. The values for all in surveys non-included enterprises/ non-responding enterprises are based on administrative data - either on tax data (annual reports - turnover, value added) or on Social Insurance data. Only for a very small number of enterprises a model based imputation has to be provided . For the samples data there is no grossing up procedure and administrative data are used for 'mass imputation'.
13.2.1. Sampling error - indicators
Sampling errors are not relevant and are not calculated.
13.3. Non-sampling error
Overall non- sampling error is assumed to be small. Most important aspects of non-sampling errors are considered as very low. The bias associated with traditional survey sampling is significantly reduced cause of using of administrative sources extensively, especially on the higher levels of aggregations. Methods to detect the non-correct variable´s values include all logical data controls, data editions and corrections at the microdata level during and/or after the data collection.
The potential non-sampling error that is considered to be very small may result from:
Relatively high degree of misclassification particularly of the smallest units (natural persons and legal persons without employees).
Non-response however, it is not considered to be serious problem.
Relatively frequent modifications of the content or/and the extent of the administrative sources.
The lack of information related to the smallest units (especially natural persons without employees).
13.3.1. Coverage error
The Coverage error is mainly manifested by the imperfection of the Business Register. The coverage error is very small. The completeness of the Business Register is considered to be satisfying and high. Since the Business Register is regularly updated and supplemented, the coverage error is kept at a not very small level. In the same way, the processed administrative data has a very high linkage rate to the Business register (more than 99%) and minimal occurrence of duplicate listings.
13.3.1.1. Over-coverage - rate
Not applicable
13.3.1.2. Common units - proportion
Most of the survey units are also available in administrative sources. The obligation to file a tax return follows from the law, so the common units proportion for this source is almost 100%. Social insurance data include data on enterprises with employees as well as on self-employed persons.
13.3.1.3. Misclassification errors
Misclassification errors are very cause of statistical units in the Business register are regularly updated for correct size classes and economic activities.
13.3.1.4. Under- and over-coverage problems
Coverage errors are very small because the completeness of the Business Register is considered to be very good. Therefore any upsurge of coverage errors are not deemed to be a big problem. A relatively higher degree of misclassification particularly arise in the field of smallest units (natural persons and legal persons without employees).
13.3.2. Measurement error
Measurement errors in this survey based on administrative sources occur only very random and they do not result in a systematic bias. Most of these errors are searched by formal and logical checks.
13.3.3. Non response error
Overall non-response in the surveys is very small. Only unit-response is relevant, higher non- response has been observed in smaller unit.
The rate of non-response is displayed in the Table 13.3.3 in the Annex at the bottom.
13.3.3.1. Unit non-response - rate
As weighted non-response characteristics used is number of employees and self-employed persons. The weighted response rates are considered high (around approximately from 85% to 100% depending on the variable and NACE and size groups). Relatively high degree of non-response is particularly in the segment of smallest units.
See Table 13.3.3 in the Annex at the bottom.
13.3.3.2. Item non-response - rate
Item non response is negligible, the data is checked using logical checks during data collection, units that do not comply the checks are re-contacted, therefore, and it can be assumed that the Item non-response rate is close to zero.
Therefore, for the item – no response See Table 13.3.3 in the Annex at the bottom.
13.3.4. Processing error
Errors during data processing are insignificant. Prior to data use in the statistical processing they must be verified by the procedures detecting and correcting the errors, e.g. errors in order of the data (e.g. balance sheet data, a profit and lost statement data) or consistency errors.
Most of important variables from the response report are subjected the logical and formal checks and corrections. So these errors are minimalized already in this data collection in order to be correct. Therefore the count of responses with the potential erroneous values is negligible.
13.3.5. Model assumption error
For the most important key indicators, a model approach is not necessary, they are available directly from administrative sources, or from survey. For this reason, the model assumption error has not applied yet.
14.1. Timeliness
IFATS statistics are calculated annually for reference year T.
Data collection in statistical questionnaires and validation takes place at T+4-8 months after the end of the reference period.
14.1.1. Time lag - first result
Not relevant
14.1.2. Time lag - final result
Data transmission to Eurostat takes place at T+20 months.
14.2. Punctuality
The data collection from the statistical questionnaires and validation deadline of the reported SBS variables is T+8 months.
14.2.1. Punctuality - delivery and publication
Restricted from publication
15.1. Comparability - geographical
All regions of the Slovak Republic are covered by the survey.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not available
15.2. Comparability - over time
Please consult concept 15.2.1.
15.2.1. Length of comparable time series
The length of time series is 2003 - 2023.
Length of comparable time series:
2010 - 2020
2021 - 2023
15.2.2. Reasons and differences in concepts and measurement methods for breaks in time series
Statistical Office of the Slovak Republic prepared the first data files on FATS for the reference year 2003 in the frame of Trasition Facility program. The data was compiled in the first shot concept and only for enterprises with 20 and more employees. IFATS data for the reference years 2004 - 2009 are compiled using UCI concept. They include also estimation for small enterprises with less than 20 employees.
IFATS data for 2010 - 2020 reference years are compiled by combination of statistical surveys and administrative data (annual tax returns/financial statements data and social insurance data) including the data on natural persons.
Since the reference year 2021 a new Regulation (EU) 2019/2152 (EBS Regulation) replaced the old FATS regulation introducing the extension in coverage (NACE).
15.3. Coherence - cross domain
The overall comparability is considered to be good and fully coherent with the SBS data.
15.3.1. Coherence - sub annual and annual statistics
Not applicable
15.3.2. Coherence - National Accounts
Methodological and conceptual differences between National Accounts and Business Statistics based on the ESA2010 and EBS Regulation are considered as not significant.
15.3.3. Coherence – National Statistical Business Register (NSBR)
Conceptual differences in terms of population included in the Statistical Business Register vs. population of active enterprises in IFATS and SBS and BD. The information from the Statistical Business Register is used for the IFATS data compilation.
15.3.4. Coherence – Structural Business Statistics (SBS)
Fully coherent.
15.3.5. Coherence – R & D
Fully coherent.
15.3.6. Coherence – Foreign Direct Investment (FDI)
Not available
15.3.7. Coherence – EuroGroups Register (EGR)
For the reference year 2023, the EGR is used as a source of the information in greater extent along with the manual UCI allocation.
15.4. Coherence - internal
All IFATS aggregates are consistent with their main sub-aggregates and the SBS aggregates.
Statistical Office of the SR regularly monitors the cost and burden of reporting units. As part of the optimization of statistical surveys, it takes measures aimed at reducing their burden e.g. by personalised pre-filling of selected variables in statistical questionnaires, reducing the frequency of selected surveyed variables and using administrative data resources if they are available in the required quality and at the specified time.
The cost and burden measurement at the level of European Statistical Products is in competence of the Resources Directors Group within Eurostat.
17.1. Data revision - policy
The Revision policy regulates the general rules and procedures applied in revisions at the Statistical Office of the SR. The same revision policy applies to national and international users. In accordance with the Revision policy, the reason of the revision is always indicated. The Revisions policy as well as the Revisions calendar is available to users on the web portal of the Statistical Office of the Slovak Republic.
Policy and calendar of revisions of the Statistical Office of the SR.
Statistical Office of the SR distinguishes the following revisions:
From the content point of view
incorporation of better quality data based on a more complete source, including replacing imputations with collected data
incorporation of better quality data based on a more complete source, including replacing imputations with collected data
correction of data as a result of updating seasonal factors and changing the base period
data modification based on more accurate methodology (in concepts, definitions and classifications) and changes in statistical methods performing corrections in source data and calculations.
In terms of time, Statistical Office of the SR divides the revisions into.
ordinary revisions are revisions without significant modifications of the methodologies. These are usually more significant data corrections, including large values obtained from new sources. They are carried out periodically on precisely set up dates, to update data, until the next publication of the data
annual revisions are revisions that are made when all monthly and quarterly data are available and more detailed results from annual surveys are already available
extraordinary and major revisions are revisions of definitive data due to significant methodological changes resulting from revision of methodologies, changes in procedures and statistical-mathematical calculation methods or data corrections. An extraordinary revision may result (e.g. by changing the definition) in break in time series data comparability.
17.2. Data revision - practice
The main source of information for routine revisions are new or revised data from reporting units.
17.2.1. Data revision - average size
Please consult annex concept 17.2.
18.1. Source data
Combination of exhaustive survey and sample survey combined with information from administrative data sources
Exhaustive annual survey of large enterprises - Questionnaire Roc 1-01
legal units with 20 and more employees registered in the Statistical Business Register
legal units with less than 20 employees registered in the Statistical Business Register:which were statistically important (the decision about including them into survey of large enterprises was done by expert of particular branch statistics, e.g.
responsible for branch statistics etc.)
or of which turnover exceeds 5 million €
Annual survey of small enterprises (sample) - Questionnaire Roc 2-01
legal units with less than 20 employees registered in the Statistical Business Register that the turnover of which does not exceed 5 million €
Following administrative data sources are used for the compilation of the SBS data:
Selected information from the income tax returns
Tax declarations
Social insurance data
Data on self employed persons are included in SBS data files starting with the data transmission of preliminary 2010 SBS data files. We use the basic information on structures and relations of particular variables from small sample survey for small entrepreneurs to make estimations of missing data in administrative source for this population.
The relevant UCI identified by the mean of an manual data validation and the information from the EGR Final Frame and from the administrative data sources publicly available.
18.1.1. Methodological approach
Combination of exhaustive survey and sample survey combined with information from administrative data sources.
Please consult concept 18.1
18.1.2. Use of cut-off thresholds
No cut-off thresholds.
18.2. Frequency of data collection
Annual
18.3. Data collection
Source to define your population:
100 % Structural Business Statistics (SBS)
Economic data obtained using:
100 % Structural Business Statistics (SBS)
18.4. Data validation
The data entry, data completeness and statistical control are organised by specialised regional offices of the Statistical Office of the SR. Data validation is done during the data collection, processing and validation of relevant data by the Statistical Office of the SR experts. A data comparison is done with previous periods.
Statistical Office of the SR distinguishes between two levels of data checks during the electronic data collection:
Formal checks, which are realised in the process of data entry automatically; (compatible with Validation level 0 and 1)
Informal checks aim of which is to control the complexity and relations among the variables ((compatible with Validation level from 2 to 5)
According to the importance there are classified 2 basic types of checks:
I – Informative checks- this check gives the additional information, which is important for the following process of corrections. It informs also about some inconsistencies in the state of fulfilment of the questionnaire, about item non-response, exceeding stated limits etc.
Z – Check of great importance - it is mostly check indicating the exact error and it must be always corrected or explained
Most of the errors are directly consulted with the reporting units by our regional offices via telephone contacts, emails etc.
18.5. Data compilation
Since 2021 for the sample data there is no grossing up procedure and models based on survey data and administrative data are used for 'mass imputation'. The main models used are based on ratio etimators. To obtain basic information about the structures and relationships of individual variables in small entrepreneurs, various available administrative sources are used to estimate missing data for this population.
18.5.1. Imputation - rate
Since 2021 for the sample SBS data there is no grossing up procedure and models based on survey data and administrative data are used for 'mass imputation'. The main models used are based on ratio etimators. To obtain basic information about the structures and relationships of individual variables in small entrepreneurs, various available administrative sources are used to estimate missing data for this population.
18.5.2. Use of a method to deal with non-response (both unit and item non-response)
Foreign Affiliates Statistics (FATS) measure the commercial presence through affiliates in foreign markets.
Inward foreign affiliates statistics (IFATS) shall mean statistics describing the activity of foreign affiliates resident in the compiling country.
In country-level business statistics foreign-controlled enterprise shall mean an enterprise resident in the compiling country over which an ultimate controlling institutional unit not resident in the compiling country has control.(Table 14 of the EBS Implementing Regulation (EU) 2020/1197).
Variables on the country-level business activities in the IFATS data category:
Business activities in foreign control:
210301. Number of foreign-controlled enterprises
220501. Number of employees and self-employed persons in foreign-controlled enterprises
220701. Employee benefits expense in foreign-controlled enterprises
230301. Intramural R & D expenditure in foreign-controlled enterprises
230401. R & D personnel in foreign-controlled enterprises
240301. Total purchases of goods and services of foreign-controlled enterprises
240302. Purchases of goods and services for resale of foreign-controlled enterprises
250601. Net turnover of foreign-controlled enterprises
250701. Value of output of foreign-controlled enterprises
260201. Foreign-controlled enterprises’ gross investment in tangible non-current assets
250801. Value added of foreign-controlled enterprises
Business activities in total economy:
210101. Number of active enterprises
220101. Number of employees and self-employed persons
220301. Employee benefits expense
230101. Intramural R & D expenditure
230201. R & D personnel
240101. Total purchases of goods and services
240102. Purchases of goods and services for resale
250101. Net turnover
250301. Value of output
250401. Value added
260101. Gross investment in tangible non-current assets
30 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): SPE are not identified in the enterprise population.
Treatment of equally shared control: In some cases we include them into the aggregates Z7 (Equally-shared control of UCIs (ultimate controlling institutional units of a foreign affiliate) of more than one EU member state) and Z8 (Extra-EU (changing composition) not allocated) on the basis of information on residence of these UCI.
Treatment of multiple minority ownership: In exceptional cases where no partner has more than 50% of ownership or we have no information about country of residence we allocate data to SK.
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.
Slovak Republic
2023
The overall accuracy of the results can be assessed as good. The Inward FATS data are a subset of the structural business statistics data. The IFATS data is compiled by combining administrative information and statistical questionnaires. The technical project of data processing is part of Integrated statistical information system (ISIS). This project includes a description of all logical data controls at the microdata level performed during electronic data collection. The electronic questionnaire and information system ISIS itself provides many arithmetic and logical checks between variables, which we distinguish between serious and informative. Data collection is provided by the office of the Statistical Office of the SR in regions. After the deadline for submission of the statistical questionnaire, the reporting units that did not respond are contacted again to fulfil their legal obligation. In case of serious errors in the form, this form is not accepted and with the help of experts from the regional office its correctness is ensured so that it can enter into the data processing. Automatic validation checks during data collection and informative checks are incorporated with the aim to follow logical checks, reducing the rate of partial non-responses, anomalies and outliers. The purpose of this process is to minimize errors already in the data collection itself and subsequently during data processing. The basic step in the process of calculating unit non-response is the analysis of the population with regard to the state of activity of the reporting units. For this purpose, we use a specific classification of responses and non-responses codes. Individual codes describe active and inactive units and are assigned to each reporting unit. Subsequently, we determine the population of active units entering the data processing. After the deadline for submission of the statistical questionnaire, the reporting units that did not respond are contacted again to fulfil their legal obligation. For estimates of self-employed persons is beeing using a model approach on administrative data based. Most errors are directly consulted at regional offices with the reporting units. Therefore it is possible the overall accuracy to consider as good.
Number of enterprises and employment variables are recorded in absolute figures.
Monetary data of enterprises are recorded in thousands Euros.
Since 2021 for the sample data there is no grossing up procedure and models based on survey data and administrative data are used for 'mass imputation'. The main models used are based on ratio etimators. To obtain basic information about the structures and relationships of individual variables in small entrepreneurs, various available administrative sources are used to estimate missing data for this population.
Combination of exhaustive survey and sample survey combined with information from administrative data sources
Exhaustive annual survey of large enterprises - Questionnaire Roc 1-01
legal units with 20 and more employees registered in the Statistical Business Register
legal units with less than 20 employees registered in the Statistical Business Register:which were statistically important (the decision about including them into survey of large enterprises was done by expert of particular branch statistics, e.g.
responsible for branch statistics etc.)
or of which turnover exceeds 5 million €
Annual survey of small enterprises (sample) - Questionnaire Roc 2-01
legal units with less than 20 employees registered in the Statistical Business Register that the turnover of which does not exceed 5 million €
Following administrative data sources are used for the compilation of the SBS data:
Selected information from the income tax returns
Tax declarations
Social insurance data
Data on self employed persons are included in SBS data files starting with the data transmission of preliminary 2010 SBS data files. We use the basic information on structures and relations of particular variables from small sample survey for small entrepreneurs to make estimations of missing data in administrative source for this population.
The relevant UCI identified by the mean of an manual data validation and the information from the EGR Final Frame and from the administrative data sources publicly available.
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 in statistical questionnaires and validation takes place at T+4-8 months after the end of the reference period.
All regions of the Slovak Republic are covered by the survey.
