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 “Net 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 2division 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.
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 2013, as the first reference year, to 2020 information is published on NACE codes K6411, K6419 and K65 and its breakdown.
From 2008 reference year data collection BS covers NACE Rev 2 codes: J62, N78, J582, J631, M731, M691, M692, M702, M712, M732, M7111, and M7112.
3.4. Statistical concepts and definitions
SBS constitutes an important and integrated part of the new European Business Statistics Regulation N° 2152/2019.
Enterprise is the statistical unit for which statistics are ultimately compiled, according to Council Regulation (EEC) No 696 / 93 of 15 March 1993 on the statistical units for the observation and analysis of the production system in the Community and other methodological guidelines.
3.5.1. Treatment of complex enterprise
Data treatment
Sample frame based on enterprises
no
Surveying all legal units belonging to a complex enterprise
yes
Surveying all legal units within the scope of SBS belonging to a complex enterprise
yes
Surveying only representative units belonging to the complex enterprise
no
Other criteria used, please specify
Comment
3.5.2. Consolidation
Consolidation method
Consolidation carried out by the NSI
yes
Consolidation carried out by responding enterprise/legal unit(s)
no
Other methods, please specify
Comment
3.6. Statistical population
The statistical population includes all active market enterprises of Sections B-N, P-R and divisions S95, S96 of NACE Rev. 2 in the Statistical Business Register (SBR). All size classes are covered.
Since 2021 reference year the sole proprietors are included in the total values for the variables number of enterprises and number of employees and self employed persons but it not cover the other economic variables. Also data are not available by size class of enterprise due to lack of reliable information in the SBR.
The frame for identifying units for the population is the Statistical Business Register.
3.7. Reference area
The whole country.
Regional datasets on NUTS 2 level.
3.8. Coverage - Time
The length of time for which data are available is 1997 to 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.
6.1. Institutional Mandate - legal acts and other agreements
Starting with reference year 2021 two new regulations currently form the legal basis of SBS:
Regulation (EU) 2019/2152 repealing 10 legal acts in the field of business statistics (EBS Regulation), and
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.
The rules applied to treat confidential data are the following: when there are less than four units or one or two units are dominating the aggregates (more than 80% of the turnover). The value of turnover, employment and main activity at unit level are not consider as confidential data.
7.2.1. Confidentiality processing
Data treatment
Confidentiality rules applied
yes
Threshold of number of enterprises (Number)
4
Number of enterprises non confidential, if number of employments is confidential
no
Dominance criteria applied
yes
If dominance criteria applied specify the threshold (Number)
one unit or two units have more than 80% of the turnover
Secondary confidentiality applied
yes
Comment
8.1. Release calendar
The Calendar release is issued at the begining of the year on the INSSE website.
In line with the Community legal framework and the European Statistics Code of Practice, the Romanian national statistical Institute disseminates national SBS data on its website respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably.
The users are informed that the data are being released based on the dissemination calendar; the dissemination of statistical data is for all users at the same time.
Annual.
10.1. Dissemination format - News release
Press release is done on regular basis (T+11 months).
10.2. Dissemination format - Publications
Regular publications in which the data are made available to the public:
In NSI Romania, according to National Statistical legislation NIS applies the quality concepts in official statistics. NSI Romania uses statistical methods and processes in compliance with the following internationally principles and standards:
Commitment to support the credibility of official national statistics NSI quality statement;
Code of good practice of European statistics - 2017; 2011; 2005.
The following national standards and provisions are applied:
Quality Guidelines for Romanian Official Statistics;
Methodological guide for data editing.
11.2. Quality management - assessment
The quality management process covers all phases. In the data collection and data editing, various checks and validation rules are applied. Data are also validated against administrative sources. Unit and item non-responses are checked in order to be imputed from administrative sources, where available. The check and validation process is applied on different levels as follows:
At micro-data level some ratios between variables are checked to identify the significant growths or decreases compared to previous year. For the units were such phenomena is seen; either the unit is recontacted or data are checked against administrative records;
The main variables are checked against those available from administrative data sources to check for any possible errors in the data collected;
The main activity of the units are checked compared to previous year and to other statistical surveys results;
The grossed up values are checked especially for variables concerning investments, stocks and purchases;
Aggregated data at class level are level are compared to the values of the previous year. Reasons for growths or decrease should be identified; special attention is given to large units and to larger ratios.
12.1. Relevance - User Needs
The main internal users are the national accounts department, the STS department and other statistical departments in the NSI. Other internal users are: media, researchers and businesses.
External users are: Eurostat, UN and other international organisations.
12.2. Relevance - User Satisfaction
General user satisfaction is carried out on a multi-annual basis.
12.3. Completeness
All the requested variables are compiled and disseminated. Data are compiled also by size class, NUTS and CPA as requested by the regulation.
13.1. Accuracy - overall
The accuracy of the data is considered as very good. The main sources of error are linked with the non-response. A complex data editing process is applied at micro-level for the data editing carried out on a continuous basis throughout the production process as mentioned under the heading 11. Quality management.
13.2. Sampling error
The survey units are drawn by stratified simple sample random sampling of legal unit. Neyman allocation is applied (in the sampling frame of units) in order to optimise the accuracy of the estimation of the total turnover at class level. For the large enterprises all legal units within this enterprise are surveyed. For the large enterprises the data at enterprise level are compiled using manually profiled approach. Automatic algorithms are applied to obtain consolidated data at the enterprise level, based on the data collected at the legal unit level.
13.3. Non-sampling error
The sources of non-sampling errors are due mainly to the following cases:
Not available information in their administrative records;
NACE misclassifications.
In order to assure a satisfactory level of response, the respondends are informed that the survey reply is mandatory and financia. Moreover, the non-respondent units are recontacted several times by sending emails or phone calls. A special attention is paid to large enterprises.
For the non-responses we are using the administrative data. In case admin data are not available the final weighting rates are adjusted with the non-reponse rate.
14.1. Timeliness
Preliminary SBS data are transmitted to Eurostat 10 months after the end of the reference period.
Full set of SBS data is transmitted to Eurostat at T+18 months.
At national level preliminary SBS results are published T+11 months while final data are published T+18 after transmission to Eurostat and T+19 on the NSI statistical database.
14.2. Punctuality
Data 2022 reference year have been delivered on 28th of June 2024.
15.1. Comparability - geographical
Same statistical concepts applied in the entire national territory.
15.2. Comparability - over time
Length of comparable time series 2018-2022 according to enterprise definition.
15.2.1. Time series
Time series
First reference year available (calendar year)
2018
Calendar year(s) of break in time series
no
Reason(s) for the break(s)
statistical unit
Length of comparable time series (from calendar year to calendar year)
2018-2022
Comment
15.3. Coherence - cross domain
The coherence between SBS data and the Business Demography is improved since 2021 by including in the SBS data on the sole proprietors concerning variables number of units and employment. Additional checks are carried out to insure the coherence between STS and SBS for the variables turnover and employment.
15.4. Coherence - internal
The aggregates are consistent with their main sub-aggregates.
A dedicated survey for measuring cost and burden is not carried out.
17.1. Data revision - policy
Statistical data are revised when there are errors. Some type of revisions are applied: planned revisions, severe revisions due to errors.
17.2. Data revision - practice
The reasons for revising the data transmitted to Eurostat (preliminary versus final data and revising final data) are mainly related to availability of data sources.
18.1. Source data
The data source is statistical survey combined with administrative sources.
The sample design is stratified based on following stratifications criteria: NACE activity code, size class according to employment.
The main administrative data source used are the annual financial statements and social security. A number of variables are derived directly from the administrative sources and some others are calculated on those sources. Annual financial statements are used for monetary variables while social security data are used for employment variables.
Data sources used for the imputation in case of non-response are the same: financial statements of the enterprises and social security. The data source used for calibration are the financial statements (turnover).
We have access to micro data with good frequency. We are receiving several stages which insure a good completeness.
The frame is based on financial statement data which feeds the Statistical Business Register (SBR).
The variable used for identifying principal and secondary activities is the turnover.
We are updating the principal activity based on the stability rules that we are applying by keeping the same code for two consecutive years. The SBR is updated similar as SBS. A new sample is drawn every year.
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
Comment
18.2. Frequency of data collection
Annual data collection.
18.3. Data collection
For the part of the data collected in the statistical survey, paper questionnaire and electronic (Excel questionnaires) are used. The electronic questionnaires contain a number of quality/consistency checks.
In case of non-responses the actions taken are to re-contact the units.
For the part which is derived from administrative sources data are extracted from the database that is provided by the Taxation Authority.
18.4. Data validation
The validation process consist of different steps:
- Checking the format and file structure;
- Checking the data at record level; the compleatness of the data. The main indicators (employment, turnover etc) are validated. Checks bewteen variables are also applied (for examples employment versus wages and salaries, incomes versus expenditures, investments);
- Checks for similar variables between other business statistics domains or employment statistics;
- Checks over time of data both at record level and aggregated level (NACE class);
- Checks at the unit level of main indicators (turnover, employment, investments) between data collected in the statistical survey and those available in the administrative data sources.
18.5. Data compilation
The non-response is treated using imputation methods. For the missing data different sources or methods are used to impute the data:
1. imputing and compiling the data based on administrative sources;
2. imputing the missing data using different algorithms (compiling based on the existing data at unit level);
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 “Net 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 2division level (2-digits).
12 August 2024
SBS constitutes an important and integrated part of the new European Business Statistics Regulation N° 2152/2019.
Enterprise is the statistical unit for which statistics are ultimately compiled, according to Council Regulation (EEC) No 696 / 93 of 15 March 1993 on the statistical units for the observation and analysis of the production system in the Community and other methodological guidelines.
The statistical population includes all active market enterprises of Sections B-N, P-R and divisions S95, S96 of NACE Rev. 2 in the Statistical Business Register (SBR). All size classes are covered.
Since 2021 reference year the sole proprietors are included in the total values for the variables number of enterprises and number of employees and self employed persons but it not cover the other economic variables. Also data are not available by size class of enterprise due to lack of reliable information in the SBR.
The frame for identifying units for the population is the Statistical Business Register.
The whole country.
Regional datasets on NUTS 2 level.
2022.
Data refers to calendar year.
The accuracy of the data is considered as very good. The main sources of error are linked with the non-response. A complex data editing process is applied at micro-level for the data editing carried out on a continuous basis throughout the production process as mentioned under the heading 11. Quality management.
• 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 non-response is treated using imputation methods. For the missing data different sources or methods are used to impute the data:
1. imputing and compiling the data based on administrative sources;
2. imputing the missing data using different algorithms (compiling based on the existing data at unit level);
3. imputing data from other statistical data.
The data source is statistical survey combined with administrative sources.
The sample design is stratified based on following stratifications criteria: NACE activity code, size class according to employment.
The main administrative data source used are the annual financial statements and social security. A number of variables are derived directly from the administrative sources and some others are calculated on those sources. Annual financial statements are used for monetary variables while social security data are used for employment variables.
Data sources used for the imputation in case of non-response are the same: financial statements of the enterprises and social security. The data source used for calibration are the financial statements (turnover).
We have access to micro data with good frequency. We are receiving several stages which insure a good completeness.
The frame is based on financial statement data which feeds the Statistical Business Register (SBR).
The variable used for identifying principal and secondary activities is the turnover.
We are updating the principal activity based on the stability rules that we are applying by keeping the same code for two consecutive years. The SBR is updated similar as SBS. A new sample is drawn every year.
Annual.
Preliminary SBS data are transmitted to Eurostat 10 months after the end of the reference period.
Full set of SBS data is transmitted to Eurostat at T+18 months.
At national level preliminary SBS results are published T+11 months while final data are published T+18 after transmission to Eurostat and T+19 on the NSI statistical database.
Same statistical concepts applied in the entire national territory.
Length of comparable time series 2018-2022 according to enterprise definition.
