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.
Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS covers all activities of the business economy with the exception of agricultural activities, public administration and (largely) non-market services such as education and health. Main characteristics (variables) of the SBS data category:
Business demographic variables (e.g. Number of active enterprises).
"Output related" variables (e.g. Net turnover, Value added).
"Input related" variables: labour input (e.g. Number of employees and self-employed persons, Hours worked by employees); goods and services input (e.g. Purchases of goods and services); capital input (e.g. Gross investments).
Business services statistics (BS) collection contains harmonised statistics on business services. From 2008 onwards BS become part of the regular mandatory annual data collection of SBS. The BS’s data requirement includes variable “Turnover” broken down by products and by type of residence of client.
The annual regional statistics collection includes three characteristics due by NUTS-2 country region and detailed on NACE Rev 2 division level (2-digits).
3.2. Classification system
Statistical Classification of Economic Activities in the European Community (NACE): NACE Rev.2 is used from 2008 onwards. Key data were double reported in NACE Rev.1.1 and NACE Rev.2 only for 2008. From 2002 to 2007 NACE Rev. 1.1 was used and until 2001 NACE Rev.1
The product breakdown is based on the Classification of Products by Activity (CPA) as stated in the Regulation establishing CPA 2008 and its amending Commission Regulation (EU) No 1209/2014 (from reference year 2015 onwards).
3.3. Coverage - sector
Starting reference year 2021 onwards SBS cover the economic activities of market producers within the NACE Rev. 2 Sections B to N, P to R and Divisions S95 and S96. Until 2007 the SBS coverage was limited to Sections C to K of NACE Rev.1.1 and from the reference year 2008 to 2020 data was available for Sections B to N and Division S95 of NACE Rev.2.
From 2008 reference year the data collection Business services covers NACE Rev 2 codes: J62, N78, J582, J631, M731, M691, M692, M702, M712, M732, M7111, and M7112. From 2013, as the first reference year, to 2020 information is published on NACE codes K6411, K6419 and K65 and its breakdown.
3.4. Statistical concepts and definitions
SBS constitutes an important and integrated part of the new European Business Statistics Regulation N° 2152/2019.
Statistical unit used for the compilation the SBS series is enterprise.
3.5.1. Treatment of complex enterprise
Data treatment
Sample frame based on enterprises
Sample frame based on legal units, unless a complex enterprise prefers to report the questionnaire in consolidated form for all legal units concerned.
Surveying all legal units belonging to a complex enterprise
no
Surveying all legal units within the scope of SBS belonging to a complex enterprise
no
Surveying only representative units belonging to the complex enterprise
no
Other criteria used, please specify
Mixed approach. In some cases all legal units within the scope of SBS belonging to a complex enterprise are surveyed, in some cases - depending on the structure of enterprise - only representative legal units.
Comment
The SBS team, in cooperation with colleagues from national accounts and statistical registers, continuously monitor the SBS population in order to search for units that may not fulfil the institutional independence from their parent corporations as defined by ESA and SNA. If such units are identified, they are profiled and delineated. They are then transmitted to the NSBR, which registers them as complex enterprises. At the same time, the impact of a possible consolidation of such units on the aggregated SBS outputs is assessed. If the impact is significant, the legal units that cannot be treated as separate institutional units or enterprises are treated as an integral part of the parent corporation and their accounts are consolidated with those of parents.
So far, higher tens of such entities have been identified with a significant impact, primarily on indicators other then SBS indicators. The reason is that the identified units almost never report operating income or expenses, and if they do, they are of very small amounts. On the contrary, they always report high financial income, possibly expenses and high assets, i.e. items that do not enter the calculation of SBS indicators.
3.5.2. Consolidation
Consolidation method
Consolidation carried out by the NSI
Yes, if relevant
Consolidation carried out by responding enterprise/legal unit(s)
Preferred option if responding legal units agrees.
Other methods, please specify
-
Comment
-
3.6. Statistical population
Target population: All the active enterprises (consisting of legal and natural persons) classified in Sections B to N and P to R and Division S95, S96 of NACE Rev 2 and institutional sectors of financial corporations, non-financial corporations and households (employers and own-account workers). Exceptions are housing associations and non-profit institutions classified into the institutional sector of non-financial corporations.
Frame for the identification of the population: National statistical business register.
3.7. Reference area
Czech Republic
Inclusion/exclusion of the activities of Foreign Affiliates
If a foreign enterprise establishes a branch in the Czech Republic, it has the obligation to register the branch at the Register of Companies, thereby it enters the Statistical Business Register and subsequently the population of the Annual Structural Business Survey carried out by the Czech Statistical Office (CzSO). And the other way round, if an enterprise registered in the Czech Republic establishes a branch abroad, it is requested to report only unconsolidated information (i.e. data not including the activities of foreign affiliates). However, if an enterprise registered in the Czech Republic carries on business abroad, but does not establish an affiliate abroad, the results of these activities are included in the data reported to the CzSO.
3.8. Coverage - Time
2005-2022.
3.9. Base period
Not applicable.
Number of enterprises and number of local units are expressed in units.
Monetary data are expressed in millions of €.
Employment variables are expressed in units.
Per head values are expressed in thousands of € per head.
Ratios are expressed in percentages.
2022
Data refers to calendar year. If an enterprise reports the data for a fiscal year, it is recalculated to the respective calendar year.
6.1. Institutional Mandate - legal acts and other agreements
Starting with reference year 2021 two new regulations currently form the legal basis of SBS:
The Council Regulation No 58/97 has been amended three times: by Council Regulation No 410/98, Commission Regulation No 1614/2002 and European Parliament and Council Regulation No 2056/2002. As a new amendment of the basic Regulation it was decided to recast the Regulation No 58/97 in order to obtain a new "clean" legal text. In 2008 the European Parliament and Council adopted Regulation No 295/2008 and the provisions of this Regulation were applicable from the reference year 2008 to reference year 2020. Regulation No 295/2008 was amended by Commission Regulation (EU) No 446/2014.
For the detection of confidential cells we use so-called “key variables” (Net Turnover (12110) and Number of employees and self-employed persons (16110)) and then we apply the confidential pattern to the other variables.
Flag A - too few enterprises (
Flag O - the share of the individual data of one statistical unit is significantly predominant (information on the percentage of predominancy is considered confidential).
Flag D - Secondary confidential data in order to protect data flagged with A, B.
Confidential SBS data is protected against the risk of disclosure using Tau-Argus SW program.
7.2.1. Confidentiality processing
Data treatment
Confidentiality rules applied
yes
Threshold of number of enterprises (Number)
not available
Number of enterprises non confidential, if number of employments is confidential
yes
Dominance criteria applied
yes
If dominance criteria applied specify the threshold (Number)
All the data provided to Eurostat, unless marked for use as a contribution to European totals only, is provided to users through the regular publications or on request.
Microdata is provided only to the selected public authorities and wholly in conformity with the State Statistical Service Act.
Annual.
10.1. Dissemination format - News release
News releases are not used for the publication of the SBS data. The Czech Statistical Office prefers other publication formats.
10.2. Dissemination format - Publications
Paper publications and Statistical Yearbook of the Czech Republic available in paper and electronic versions (English versions, see Annex).
Time series of SBS indicators supplemented by related indicators constructed according to the national methodology are published on the website of the Czech Statistical Office.
Access to microdata is granted only to the selected public authorities and wholly in conformity with the State Statistical Service Act.
10.5. Dissemination format - other
All data from the Annual Structural Business Survey not regularly published, respecting the rules for the protection of confidential data, can be provided on request, in the detail corresponding to the SBS requirement, to all users.
10.6. Documentation on methodology
Available as part of the paper/electronic publications and time series. This documentation is available in Czech and also in English.
See methodology for services (the methodology is the same for all NACE)
The whole process of data production from questionnaires design, metadata definition, through data collection, imputation methods, primary and secondary data validation, confidentiality treatment and dissemination is in detail described in the internal documentation (Technical Projects and Statistical Metadata System) to which all interested parties have an access. If the Annual Structural Business Survey is the subject of the methodology audit, the documentation is available to auditors. This comprehensive documentation is available in the Czech language.
11.1. Quality assurance
Basic documents are published on the website of the Czech Statistical Office.
No major problems with relevance, accuracy, timeliness and punctuality, coherence and comparability.
12.1. Relevance - User Needs
Internal Users:
User: National Accounts Department. Needs: SBS data plus additional, mainly accounting, data far beyond the scope of SBS.
User: Prices Statistics Department Needs: Breakdown of Turnover by product type (CPA)
User: STS Needs: Weights of base year
User: IFATS Needs: Data referring to the foreign controlled enterprises.
Other users: Innovation statistics, R&D statistics
External Users:
Users: Czech National Bank, Ministry of Industry and Trade (MIT) Needs: Microdata from the Annual Structural Business Survey
Ad hoc requests: ministries and other public administration institutions, universities (especially microdata access requirements)
12.2. Relevance - User Satisfaction
Regular consultations with some of our main users are organised.
12.3. Completeness
All the SBS series provided to Eurostat are complete.
13.1. Accuracy - overall
Taking into account the available administrative data, the high response rate, imputation method chosen and the multi-stage validation system the overall quality can be assessed as favourable. The possible source of potential errors is the lack of information related to the smallest units in the population, what might result, among others, in the high misclassification of statistical units in the Statistical Business Register. The potential bias is, however, small with limited effect on the overall accuracy of estimates.
The preliminary results may be biased since at the time of its transmission to Eurostat not all questionnaires nor administrative data are available. However, we consider the potential bias to be relatively low.
13.2. Sampling error
Sampling error is monitored regularly and it is small. The coefficients of variation (CVs) are calculated and for the indicators agreed by the SBS and BD WG provided to Eurostat via eDAMIS.
CVs are calculated for indicators:
220101 Number of employees and self-employed persons
250101 Net turnover
250401 Value added
Detailed methodology on Variance estimation is included in the separate file (see Annex).
The potential non-sampling error that is considered to be small may result from:
Relatively high degree of misclassification particularly of the smallest units (natural persons and legal persons without employees, which are not VAT payers).
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 - not VAT payers - without employees)
The methods used for taking into account the unit non-response:
The imputation procedures dealing with unit and item non-response are based on:
the available administrative data (selected indicators from balance sheet and profit and loss statement; approximation of total revenues from the VAT data; number of social insurance policyholders);
the data available from the other surveys (especially annual Labour Cost Survey; quarterly business structural survey; PRODCOM);
the annual structural business data from the previous reference periods.
The quality of administrative data does not allow to be directly used in the imputation procedures. Therefore, prior to their 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 is reported in thousands, while profit and loss statement data in million) or consistency errors (assets do not equal the liabilities, revenues minus expenses do not equal the profit/loss, etc.). Moreover, the process for the verification of administrative data for a subsequent use, includes also the procedures for the imputation of missing or erroneous administrative data.
After the verification, the administrative data and other relevant data enter the process of the imputation. The very basic principle of the imputation process as such is based on the average share of an estimated variable and a variable available from the administrative or other external sources (hereafter referred as the explanatory variable) calculated from the surveyed units that provided CzSO with correctly completed questionnaire belonging to the same stratum as a non-respondent unit or a unit not included in the sample. For the estimation of the estimated variable the average share is applied to the explanatory variable available for the non-respondent unit or the unit not included in the sample.
In the initial stages of the imputation process, the explanatory variables are indicators available from the administrative or other external sources. In the next stages, a previously imputed variable can become the explanatory variable for the estimation of other variables.
The measures taken for minimising the unit non-response:
Average unit non-response is taken into account when designing the sample.
The questionnaire consists of several individual parts. Each part of the questionnaire is focused on one or more areas (e.g. cost/expenses, revenues and assets; investment; financial assets and liabilities; breakdown of turnover by products; selected indicators broken down by residence of clients; selected indicators broken down by regions; etc.). The individual parts can be combined so that we can tailor different versions of the questionnaire for different groups of respondents according to their size/importance. As a consequence the biggest enterprises complete the version of the questionnaire consisting of all (or most) parts, while the smaller ones those versions consisting of only selected parts. There are altogether more than 500 different versions of the questionnaire. Quite a high level of personification enables us to lower the burden on especially small respondents and at the same time it contributes to the minimising of the unit non-response as every sampled unit completes only the minimum information necessary for the statistical production.
Every respondent can choose one of the three ways of questionnaire completion: 1) web based questionnaire 2) interactive PDF form of the questionnaire or 3) the paper form of the questionnaire.
If a unit is selected for the sample of one survey, it cannot be selected for any sample of the other surveys unless it is classified to the stratum where all the units are sampled. This method known as negative coordination of the samples contributes to minimising the burden on especially small units. Moreover, it indirectly helps to increase the response rates of the individual surveys since it reduces the risk of non-response due to overburden of respondents.
Every non-respondent unit is contacted successively by phone or e-mail and then repeatedly by registered letter sent in most cases to so called data box. The data box is an electronic storage site, intended for delivery of official documents and for communication with public authority bodies.
Bias:
If characteristics of the non-respondent units significantly differed from those of respondent units, the estimated part of the population could be biased. In addition, a certain bias can be caused by the high misclassification of the smallest units (especially natural persons) in the Statistical Business Register.
The potential bias is, however, small with limited effect on the overall accuracy of estimates.
14.1. Timeliness
Deadline for data-collection: 25 April 2023
Deadline for post-collection phase: 31 January 2024
Deadline for the Annual Structural Business Survey termination: February 2024
Dissemination of SBS data: 30 June 2024
14.2. Punctuality
No delay.
15.1. Comparability - geographical
As regards NUTS classification, data is fully comparable.
15.2. Comparability - over time
2005 - 2020, 2021-2022
15.2.1. Time series
Time series
First reference year available (calendar year)
2005
Calendar year(s) of break in time series
2021
Reason(s) for the break(s)
1) A modification of the estimation method in the case of Labour indicators.
2) A revision of the input data of a significant respondent from the field of electricity production in the case of Output and performance and Purchases indicators.
Length of comparable time series (from calendar year to calendar year)
2005-2020, 2021-2022
Comment
The break concerns the following GIA indicators: Number of employees and self-employed persons (220101), Wages and salaries (220302), Net turnover (250101), Value of output (250301), Valued added (250401), Gross operating surplus (250501), Gross margin on goods for resale (250201), Total purchases of goods and services (240101), Purchases of goods and services for resale (240102), Purchases of energy products (240105), Payments to subcontractors (240106)
The modification of the estimation method in case of Labour indicatoros has a systematic nature and thus affected all NACE activities and especially those with a high share of micro, small and medium-sized enterprises.
The revision of Output and performance and Purchases indicators is of a local nature. It thus affected only section D of the NACE classification and all aggregates containing section D.
15.3. Coherence - cross domain
Number of enterprises in the business register - Business register contains units that are from the administrative point of view active, however, as far as statistics is concerned they are not active (e.g. units that were established, but have not started their activity yet, units that finished their activity but have not been erased from the register yet etc.). In this respect, it is important to underline that business statistics consider a unit to be active only if there is an administrative “trace”, i.e. the unit is VAT payer or statistics have information on the unit from the income tax return or on its employees from the Czech Social Security Administration.
Value added (VA) of National Accounts (NA):
There are numerous methodological and conceptual differences between VA of National Accounts and VA of Business Statistics. The inclusion of the non-observed economy in NA can be given as an example. Generally, however, the cross-domain coherence between SBS and NA data is considered favourable.
Evolution of turnover and persons employed from short term statistics:
Minor inconsistencies in the evolution of turnover - resulting from the fact that when STS data are compiled, the accounting data are considered provisional - can be observed.
The data is fully compatible with Business Demography.
15.4. Coherence - internal
Fully consistent.
Cost and burden are regularly monitored for the whole Annual Structural Business Survey (ASBS) covering requirements far beyond the SBS requirements.
On the basis of the ASBS burden model, it was estimated the burden resulting from the SBS regulation (NACE BTSXO_S94). Number of respondents (irrespective of response) for whole ASBS: 35 836. Average time to complete the questionnaire: 10,08 hours, of which 2,5 hours for items entering the computation of SBS indicators. The burden resulting from the SBS regulation: 89,6 thousand person-hours.
At present, unfortunately we are not able to make a reliable estimation of the costs resulting from the SBS Regulation using ASBS costs model.
17.1. Data revision - policy
When compiling the final data for the year Y - usually in February Y+2, if needed, data for Y-1 can be revised.
17.2. Data revision - practice
Usually, preliminary and final data are estimated in the same way.The only difference is that at the time when preliminary data are compiled, neither all surveyed data nor all administrative data are available. The data for 2022 is an exception in this regard.The revisions described in the chapter 15. Coherence and comparability were applied to the final data only.
Relative Mean Absolute Revisions (RMAR) of preliminary data versus published final data is calculated by Eurostat to ensure the comparability among countries. Relative Mean Absolute Revisions (RMAR) of preliminary data versus published final data were 0,0626 in case of variable 250101 (Net Turnover) and 0,0190 in case of variable 220101 (Number of employees and self-employed persons).
18.1. Source data
TYPE OF SOURCE: Sample survey combined with administrative sources
Following sources were used for the compilation of the SBS data:
Annual Structural Business Survey- by far the most important statistical source - surveyed are legal persons, market producers, classified in the institutional sector S.11 with a few exceptions, e.g. excluded are enterprises with the principal activity NACE 01, non-profit institutions classified in the sector S.11 or housing associations, on the contrary included are certain types of enterprises classified in the sector S.12.
A group of Annual Structural Surveys focused on financial and insurance activities
Annual Structural Survey of non-profit institutions, housing cooperatives and other selected institutions
Annual Labour Costs Survey - some data referring to number of persons employed, employee benefits expense, wages and salaries and social security costs is estimated exploiting information from the Annual Labour Costs Survey.
Quarterly business statistics survey - an auxiliary source used in the imputation.
PRODCOM survey
Administrative data:
Selected information from the income tax returns
VAT data
Number of social insurance policyholders and the basis of social security insurance assessment
SURVEY (corresponds to Annual Structural Business Survey):
A random stratified sampling is combined with an intentional sampling of statistically significant units.
The units classified in the institutional sector 14 are not sampled. The required data are estimated solely on the basis of the available administrative data.
Administrative data:
Kind of administrative data available: micro data
Population:
Income tax data - entire population
VAT data - VAT payers
Number of social insurance policyholders and the basis of social security insurance assessment - employers
Frequency:
Income tax data is provided to CzSO in three batches (T+7 months, T+9 months and T+12 months).
VAT data is available on a monthly (monthly payers)/quarterly (quarterly payers) basis.
Number of social insurance policyholders and the basis of social security insurance assessment are available monthly.
Administrative data, especially Tax income data, is subject to revisions.
FRAME
The sample of the Annual Structural Business Survey is drawn every year from the Statistical Business Register (SBR).
SBR is updated continually throughout the year. The principal and secondary activities are identified using the top-down method and variables value added, number of employees or turnover.
18.1.1. Data sources overview
Data sources overview
Survey data
yes
VAT data
yes
Tax data
yes
Financial statements
yes
Other sources, please specify
Czech National Bank for sector 12
Comment
-
18.2. Frequency of data collection
Annual data collection.
18.3. Data collection
Annual Structural Business Survey named P5-01: surveyed are legal persons, market producers, classified in the institutional sector S.11 with a few exceptions, e.g. excluded are enterprises with the principal activity NACE 01, non-profit institutions classified in the sector S.11 or housing associations, on the contrary included are certain types of enterprises classified in the sector S.12 (Financial Corporations).
Every respondent can choose one of the three ways of questionnaire completion: 1) web-based questionnaire 2) interactive PDF form of the questionnaire or 3) paper form of the questionnaire (currently almost unused).
There are several types of verification checks built-in the web-based and interactive PDF form of the questionnaire classified into the two types: interactive and batch checks and four categories: errors (Occurrence of the phenomenon is not possible), anomalies (Occurrence of the phenomenon is possible, but unlikely. The phenomenon must be commented. If found out by a statistician, it must be always verified by contacting the respective unit), non-response (The respective cell of the form is not filled in, even though according to the available information it should be) and information (Occurrence of the phenomenon is possible, but unlikely. Respondent should comment the phenomenon. If found out by the statistician, it does not have to be always verified. Decision whether it should be verified or not is up to consideration of the statistician responsible for data verification).
The web based questionnaire contains all defined checks, interactive PDF form only selected ones. Notwithstanding the way of the questionnaire completion, every questionnaire is verified by the internal verification application – the off-line version of the on-line web application for the questionnaires' completion.
Part of the data verification process is also their confrontation with available administrative data.
After the initial verification the data is sent to a central database for further processing. In the central database the surveyed data together with administrative and other external data enters the imputation procedures in order to be grossed up to the whole population. Subsequently, it is analysed and checked by the branch responsible experts.
The cycle - collection of the questionnaires, their verification, grossing up to the whole population and analysis and verification of the data concerning the whole population - is repeated several times. Particularly when there are new input data (from the survey or administrative sources).
The partner organizations provide CZSO with the administrative data in the form of extracts from the internal databases.
18.4. Data validation
See 18.3 Data collection.
18.5. Data compilation
The method of imputation/grossing-up: Estimates were based on the theory of superpopulation model of regression estimates. Simply speaking for regression estimates, the subject of the random variable is not variable Yi, but it is the remainder (random error) of the regression model.
Modification of RATIO estimators (or Superpopulation model) was applied in the CZSO and used for estimation of expected values for all unique units with no response or not in the sample in corresponding stratum in the frame. Additivity of estimated values was preserved at all level breakdowns by stratification variables. A regression estimator using model with one or two auxiliary variables (without an intercept) was applied for mass imputation. Weights were calibrated subject to totals of two auxiliary variables for all active units in the corresponding stratum. Given the difference of the indicators measured, seven different weights were calculated. The variable number of units at the end of the year was combined with one of the auxiliary variables:
Number of social insurance policyholders
Total revenues from tax income statement
Total assets
Tangible fixed assets
Intangible assets
Basis of social security insurance assessment
The auxiliary variable to calculate regression coefficients are given below:
Number of social insurance policyholders
Revenues from tax income statement
Statistical Business register (SBR) data as of the date of sampling (generation of samples) were the source of values for auxiliary variables.
Initial weights were calculated from SBR data both as inverse values of probabilities with which a unit would have been included in the sample in a given stratum. The adjustment of the weights to final values for the calculation of estimates takes into account non-activity of units, non-responses and shifts between CZ-NACE divisions (resulting from differences between the BR and actual information found by the statistical survey). Then weighted least squares method was applied in each stratum. The regression coefficients are then used to impute all surveyed variables for non-respondent units or units not in the sample. Different regression models are applied to different group of variables (e.g. turnover based variables, employees based variables).
For the strata with inadequate number of correctly filled in questionnaires, data from neighbour strata were employed to obtain estimates via regression model (so called “borrowing strength”).
As regards estimates for detailed breakdown, they were computed as an aggregate of unique unit estimated values.
Further relevant information can be found in the chapter 13.3 Non-sampling error.
18.6. Adjustment
We applied a correction in case the reference period differs from the calendar year.
No other comments.
Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS covers all activities of the business economy with the exception of agricultural activities, public administration and (largely) non-market services such as education and health. Main characteristics (variables) of the SBS data category:
Business demographic variables (e.g. Number of active enterprises).
"Output related" variables (e.g. Net turnover, Value added).
"Input related" variables: labour input (e.g. Number of employees and self-employed persons, Hours worked by employees); goods and services input (e.g. Purchases of goods and services); capital input (e.g. Gross investments).
Business services statistics (BS) collection contains harmonised statistics on business services. From 2008 onwards BS become part of the regular mandatory annual data collection of SBS. The BS’s data requirement includes variable “Turnover” broken down by products and by type of residence of client.
The annual regional statistics collection includes three characteristics due by NUTS-2 country region and detailed on NACE Rev 2 division level (2-digits).
11 June 2025
SBS constitutes an important and integrated part of the new European Business Statistics Regulation N° 2152/2019.
Statistical unit used for the compilation the SBS series is enterprise.
Target population: All the active enterprises (consisting of legal and natural persons) classified in Sections B to N and P to R and Division S95, S96 of NACE Rev 2 and institutional sectors of financial corporations, non-financial corporations and households (employers and own-account workers). Exceptions are housing associations and non-profit institutions classified into the institutional sector of non-financial corporations.
Frame for the identification of the population: National statistical business register.
Czech Republic
Inclusion/exclusion of the activities of Foreign Affiliates
If a foreign enterprise establishes a branch in the Czech Republic, it has the obligation to register the branch at the Register of Companies, thereby it enters the Statistical Business Register and subsequently the population of the Annual Structural Business Survey carried out by the Czech Statistical Office (CzSO). And the other way round, if an enterprise registered in the Czech Republic establishes a branch abroad, it is requested to report only unconsolidated information (i.e. data not including the activities of foreign affiliates). However, if an enterprise registered in the Czech Republic carries on business abroad, but does not establish an affiliate abroad, the results of these activities are included in the data reported to the CzSO.
2022
Data refers to calendar year. If an enterprise reports the data for a fiscal year, it is recalculated to the respective calendar year.
Taking into account the available administrative data, the high response rate, imputation method chosen and the multi-stage validation system the overall quality can be assessed as favourable. The possible source of potential errors is the lack of information related to the smallest units in the population, what might result, among others, in the high misclassification of statistical units in the Statistical Business Register. The potential bias is, however, small with limited effect on the overall accuracy of estimates.
The preliminary results may be biased since at the time of its transmission to Eurostat not all questionnaires nor administrative data are available. However, we consider the potential bias to be relatively low.
Number of enterprises and number of local units are expressed in units.
Monetary data are expressed in millions of €.
Employment variables are expressed in units.
Per head values are expressed in thousands of € per head.
Ratios are expressed in percentages.
The method of imputation/grossing-up: Estimates were based on the theory of superpopulation model of regression estimates. Simply speaking for regression estimates, the subject of the random variable is not variable Yi, but it is the remainder (random error) of the regression model.
Modification of RATIO estimators (or Superpopulation model) was applied in the CZSO and used for estimation of expected values for all unique units with no response or not in the sample in corresponding stratum in the frame. Additivity of estimated values was preserved at all level breakdowns by stratification variables. A regression estimator using model with one or two auxiliary variables (without an intercept) was applied for mass imputation. Weights were calibrated subject to totals of two auxiliary variables for all active units in the corresponding stratum. Given the difference of the indicators measured, seven different weights were calculated. The variable number of units at the end of the year was combined with one of the auxiliary variables:
Number of social insurance policyholders
Total revenues from tax income statement
Total assets
Tangible fixed assets
Intangible assets
Basis of social security insurance assessment
The auxiliary variable to calculate regression coefficients are given below:
Number of social insurance policyholders
Revenues from tax income statement
Statistical Business register (SBR) data as of the date of sampling (generation of samples) were the source of values for auxiliary variables.
Initial weights were calculated from SBR data both as inverse values of probabilities with which a unit would have been included in the sample in a given stratum. The adjustment of the weights to final values for the calculation of estimates takes into account non-activity of units, non-responses and shifts between CZ-NACE divisions (resulting from differences between the BR and actual information found by the statistical survey). Then weighted least squares method was applied in each stratum. The regression coefficients are then used to impute all surveyed variables for non-respondent units or units not in the sample. Different regression models are applied to different group of variables (e.g. turnover based variables, employees based variables).
For the strata with inadequate number of correctly filled in questionnaires, data from neighbour strata were employed to obtain estimates via regression model (so called “borrowing strength”).
As regards estimates for detailed breakdown, they were computed as an aggregate of unique unit estimated values.
Further relevant information can be found in the chapter 13.3 Non-sampling error.
TYPE OF SOURCE: Sample survey combined with administrative sources
Following sources were used for the compilation of the SBS data:
Annual Structural Business Survey- by far the most important statistical source - surveyed are legal persons, market producers, classified in the institutional sector S.11 with a few exceptions, e.g. excluded are enterprises with the principal activity NACE 01, non-profit institutions classified in the sector S.11 or housing associations, on the contrary included are certain types of enterprises classified in the sector S.12.
A group of Annual Structural Surveys focused on financial and insurance activities
Annual Structural Survey of non-profit institutions, housing cooperatives and other selected institutions
Annual Labour Costs Survey - some data referring to number of persons employed, employee benefits expense, wages and salaries and social security costs is estimated exploiting information from the Annual Labour Costs Survey.
Quarterly business statistics survey - an auxiliary source used in the imputation.
PRODCOM survey
Administrative data:
Selected information from the income tax returns
VAT data
Number of social insurance policyholders and the basis of social security insurance assessment
SURVEY (corresponds to Annual Structural Business Survey):
A random stratified sampling is combined with an intentional sampling of statistically significant units.
The units classified in the institutional sector 14 are not sampled. The required data are estimated solely on the basis of the available administrative data.
Administrative data:
Kind of administrative data available: micro data
Population:
Income tax data - entire population
VAT data - VAT payers
Number of social insurance policyholders and the basis of social security insurance assessment - employers
Frequency:
Income tax data is provided to CzSO in three batches (T+7 months, T+9 months and T+12 months).
VAT data is available on a monthly (monthly payers)/quarterly (quarterly payers) basis.
Number of social insurance policyholders and the basis of social security insurance assessment are available monthly.
Administrative data, especially Tax income data, is subject to revisions.
FRAME
The sample of the Annual Structural Business Survey is drawn every year from the Statistical Business Register (SBR).
SBR is updated continually throughout the year. The principal and secondary activities are identified using the top-down method and variables value added, number of employees or turnover.
Annual.
Deadline for data-collection: 25 April 2023
Deadline for post-collection phase: 31 January 2024
Deadline for the Annual Structural Business Survey termination: February 2024
Dissemination of SBS data: 30 June 2024
As regards NUTS classification, data is fully comparable.
