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.
Institut National de la Statistique et des Etudes Economiques INSEE
1.2. Contact organisation unit
Département Répertoires, Infrastructures et Statistiques Structurelles Division élaboration des statistiques annuelles d'entreprise
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
Direction générale INSEE Département Répertoires, Infrastructures et Statistiques Structurelles Division élaboration des statistiques annuelles d'entreprise 88, avenue verdier, bureau 3A044
92120 Montrouge
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
2.1. Metadata last certified
28 August 2024
2.2. Metadata last posted
28 August 2024
2.3. Metadata last update
28 August 2024
3.1. Data description
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 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
Since the reference year 2017, the French SBS results are produced in enterprise, and are fully complient with the statistical unit Regulation N° 696/93.
However, the data transmitted by the French National Bank for class 64.11, 64.19 and division 65 are in legal units.
The data collection units are mainly the legal units. For the biggest groups, which are manually profiled, some data are collected at the enterprise level. For the others, automatic profiling is carried out using legal unit data only.
3.5.1. Treatment of complex enterprise
Data treatment
Sample frame based on enterprises
yes
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
yes
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)
yes
Other methods, please specify
Comment
3.6. Statistical population
The French SBS system Esane covers all market and economically consistent units, without any threshold of size, excluding financial units (save for class 64.20 and division 66) and agriculture.
The statistics produced by the Esane process are supplemented by results produced by the French National Bank for class 64.11, 64.19 and division 65.
3.7. Reference area
Only activities conducted on the French territory including overseas departments are considered.
Branches of foreign units – that is local units not constituting separate legal entities but dependent on foreign enterprises and classified as quasi-corporations in accordance with ESA –, were, until 2014, with some exceptions, automatically considered as out of scope. They are now potentially in the scope, on the condition that they have declared a fiscal form to the French tax administration for the reference year or the previous year and secondly that they have at least one employee.
3.8. Coverage - Time
1996-2022
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 refer 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.
6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
Statistical confidentiality is defined in Act no. 51-711 of 7 June 1951 (amended) on legal obligation, coordination and confidentiality in the field of statistics. Economic or financial information may not be communicated to anyone for twenty-five years, unless special dispensation is granted by the statistical confidentiality committee, given that the information will not be used for tax inspection or punitive measures.
For business statistics, cells concerning less than three enterprises and cells in which a single enterprise represents over 85% of the total value are protected since they fall under the primary confidentiality rules. Secondary confidential cells are also protected. However, the dissemination of lists extracted from the register of enterprises and establishments may mention economic activity, number of employees category and turnover size bracket.
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
Primary suppression:
Minimum frequency: n=3 (safety margin=10%)
(n,k)-dominance rule with n=1 and k=85%
6 response variables are used and suppression patterns are then used for all disseminated variables (use of shadow variable).
To take into account the dominance rule for variable with negative values, we make primary suppression first with the variable and then with its absolute value. If there is primary secret in one of the two case, then we consider there is secret
Secondary suppression:
If possible, use of modular approach
The software Tau-Argus is used to handle primary and secondary suppression
A specific file contains the hierarchical structure
Secondary cell suppression for linked tables is made simultaneously
For “special” European aggregates asked by Eurostat, it is not possible to handle directly primary and secondary protection within Tau-Argus taking into account all other “standard” aggregates. Consequently for these aggregates simple ad hoc methods are used to handle confidentiality issues.
There are different levels of detail for explanatory variables depending on the table to protect. That prevents the data protector from automating secondary suppression resolution (because we deal with microdata and batch mode in Tau-Argus – we cannot use “recode” option in batch mode).
For variables with negative values, the secondary secret is computed with an ad hoc variable for the cost, resulting from a calculation allowing to respect the total of the variable of interest, the order of the values and that there are no negative values anymore.
To reduce the number of confidential cells, we have used a minimization algorithm (Modular) and the cost function for secondary suppression is equal to the response variable (except in case of negative values).
7.2.1. Confidentiality processing
Data treatment
Confidentiality rules applied
yes
Threshold of number of enterprises (Number)
3
Number of enterprises non confidential, if number of employments is confidential
no
Dominance criteria applied
yes
If dominance criteria applied specify the threshold (Number)
85%
Secondary confidentiality applied
yes
Comment
8.1. Release calendar
Business data are published on our website between August and September N+2.
We release each year aggregated business data on our website.
Moreover, we provide to the public authorities and a limited set of registered main users information which is not publicly available .
Annual.
10.1. Dissemination format - News release
There are no specific press releases directly linked to SBS data
10.2. Dissemination format - Publications
Electronic publications are available on our website:
- Synthetic data named "chiffres clés" are disseminated in about fifty data with possibly a graph. These data are available in French and in English, but only for one year, as they are replaced with data from the following year.
- More detailed data: main aggregates, profit and loss account, balance sheet (liabilities, gross assets, accounting depreciation) , employment, investment, rates and branches data are released:
non-anomnymized microdata are available on restricted access to researchers only, after examination by the French Secret Committee, which vouches for the respect by the researchers of the statistical confidentiality.
10.5. Dissemination format - other
The data are sent to Eurostat, to be used in European aggregates and to be released also as national data
10.6. Documentation on methodology
Methodology is available on the Website:
Documentation about the statistical process Esane, definitions of variables:
A national quality report on 2022 Esane results will be available by the end of 2024 . This report will be available in French.
11.1. Quality assurance
A continuous quality control process is performed on the Esane system (French SBS system). Each year, the different sub-processes – the handling of restructuring, the data collection of the survey, the data editing process of the survey data, the data editing process of the administrative data, the consistency monitoring process between the different sources, and the final output editing step – are reviewed with a view toward ongoing improvement. The documentation and the training related to each sub-process are adjusted accordingly.
In addition to the quality report mentionned in §10.7 and to the process review mentioned in §11.1, a quality approach involving our main internal users and coordinated by the Quality Unit of the French NSI is conducted.
Quality is evaluated as medium.
12.1. Relevance - User Needs
We have regular consultations with some of our main users: National accounts, technical ministries for quantifying policy measures, professional organizations.
The national data are more detailed (level of nomenclature, and additional variables) compared to SBS. The data available in the fiscal source are implemented with more details than asked for by SBS; results are also given at the NAF level (French version of the NACE), which is more detailed.
12.2. Relevance - User Satisfaction
We have not organised a punctual or a regular survey related to the public users' satisfaction.
The users are very interested by the results, especially at detailed levels.
The satisfaction of our main internal users is regularly assessed, by regular meetings and through the quality approach previously mentioned.
An internal mission of the General Inspectorate has been conducted to estimate the needs satisfaction degree of early users.
12.3. Completeness
Some variables are unvalaible or have been estimated :
Number of employees and self-employed persons : approximated with number of paid hours, excluding some parts of financial section. Those for which Banque de France is responsible for.
Gross investment in intangible non-current assets, other than goodwill : not available.
Expenses on services provided through agency workers: partial data only, as it come from ESA survey which does not cover the all SBS scope.
Purchases of energy products :
from EICEC survey for section B and C
for section F, it is approximated as we don't have the information in ESA survey
not available for sections D and E.
Investment in purchased software: not available.Gross investment in machinery and equipment and Gross investment in land: provision estimated as exact data is not available. Not available the previous years.
Gross investment in construction and improvement of buildings : provision estimated as exact data is not available. Includes investments on existiing buildings.
Gross investment in the acquisition of existing buildings: no data.
13.1. Accuracy - overall
As in all statistical process involving a survey, the results of the Esane system can be affected by sampling errors, coverage errors, non-response and measurement errors.
However, as we will see in the following paragraphs, in principle, none of these potential sources of errors leads to a significant bias on the results.
The French business register has no under coverage problems, and the use of external administrative information allows us to deal with the problem of over coverage.
A complex data editing process – based on selective editing combined with micro-editing for the data editing carried out on a continuous flow basis during the production process supplemented by a final output editing process – aims to reduce as much as possible the significant measurement errors.
Imputation procedures – imputation by historical information, failing that by class imputation means or medians – and reweighting procedures are used to deal with missing units/items, both in survey and administrative data. We try also to minimise the non-response in the survey, thanks to the mandatory character of the survey and to a strict follow-up procedure.
Finally, the use of a complex adjustment procedure – involving the non-response adjustment steps already mentioned, a winsorization procedure and a calibration on margins based on administrative data – and calculating aggregates by simple sum using jointly survey and administrative data tends to reduce as much as possible the non-response bias and to improve the accuracy of the statistics on the main variables of interest.
The change in method from a specific estimator to a simple sum leads to zero variance. However the new estimators are biased (although we try to reduce this bias - see above).
13.2. Sampling error
Data transmitted are mainly produced with administrative data. France has therefore exhaustive data for Number of active enterprises, Number of employees and self-employed persons, Value added and Net turnover.
Few variables are only provided from the survey. Surveys are also used to correct some administrative data but the percentage of these corrections is very low and concerns only cases with outliers. As a consequence also the following metadata quantitative indicators are exhaustive: Sample coverage, Sample size, Sample ratio, Weighted response rate and Unweighted response rate.
Starting with the reference year 2016, the survey is drawn by stratified simple sample random sampling of enterprises. Except for the biggest groups, which are manually profiled and for which data are directly collected at the enterprise level, data are still collected on legal units, with the following rule: when an enterprise is selected, then all legal units within this enterprise will be surveyed (so, from the legal unit point of view, the sample design can be seen as a two-stage cluster sampling). Automatic algorithms allow then to obtain consolidated data at the enterprise level, based on the data collected at the legal unit level. A Neyman allocation under local precision constraints is applied (in the sampling frame of enterprises) in order to optimise the accuracy of the estimation of the total turnover, both at the global level and by activities (with enterprises concepts).
Few months after the drawing of the sample, the delineation of the enterprises are updated thanks to the application of the weight share method (See Fizzala EESW 2019)
Sample survey is combined with administrative sources.
The use of a complex adjustment procedure – involving the non-response adjustment steps detailed in §13.3, a winsorization procedure to deal with outliers and a calibration on margins based on administrative data – and the calculation of aggregates (by simple sum) using jointly survey and administrative data tends to reduce as much as possible the non-response bias and to improve the accuracy of the statistics on the main variables of interest.
The change in method from a specific estimator to a simple sum leads to zero variance. However the new estimators are biased (although we try to reduce this bias - see above).
13.3. Non-sampling error
Methods for taking into account the unit non-responses:
- In the survey, the unit non response is taken into account by two different ways:
in the take all part of the sample, an imputation procedure is used, mainly based on past responses of the business. If the firm is new in the sample, mean imputation procedures are used, except for categorical data, imputed through random hot-deck method. The adjustement cells used for mean or hot-deck imputations are shaped according to industry and employment size classes. For big businesses, informations from their public reports are also used;
in the take‑some part of the sample, the « RHG model » weighting procedure is used. The RHGs are defined with the CHAID algorithm applied to various auxiliary variables explaining the response mechanism. The minimum size of each RHG is fixed to 100, in order to ensure estimation of response probability robustness. RHG should also contain at least 10 % of respondents, to avoid a too strong dispersion of the weights after non-response adjustments.
- Unit non‑response is treated by an imputation procedure for the administrative data. This imputation procedure (presented at the EESW 2013) is mostly based on the use of historical information. When this is not possible, the imputed values are implemented by strata medians.
- Moreover, a calibration procedure is applied on the take‑some part of the sample, using turnover and number of enterprise – available in administrative data – as auxiliary variables.
For minimising the unit non-response:
The survey is mandatory
When an enterprise does not send the questionnaire, there are several follow-up: official letters and then a direct contact for big non-responding firms.
Weighted unit non-response rate:
The sampling weights of legal units was used for weighting non-response. Groups 531, 559, 721, 722, 750 and 813 are not in the scope of the survey. Consequently, some variables only from the survey are not produced for these sectors.
Bias:
Bias resulting from non-response : the estimates are unbiased under the RHG model (for the take‑some part of the sample) and under the assumptions of the imputation models (for the take‑all part of the sample and for the administrative data).
The bias of the estimate: the estimate has zero variance, but it is biased, albeit with a limited effect on the overall accuracy of the estimate.
The impact of imputation:
Not important. Imputation of administrative data concerns only small or very small businesses and represent a very limited share of the aggregated fiscal turnover. Imputations of survey responses for businesses in the take-all strata mainly use past responses of the firm.
Coverage errors - Frame:
Almost none, because of the statistical inference that is made
Out-of-scope units:
The business register has no under coverage problems. External information (VAT files, fiscal data, registers of compulsory liquidations) is used to identify and discard out-of-scope units, which do not participate in the ex-post treatments and in the estimates.
14.1. Timeliness
For the statistical survey, data collection spreads from February to December N+1.
For the administrative data: we receive different files between April N+1 and January N+2, considered for SBS data of reference year N.
Preliminary data (built from the administrative source) are sent to Eurostat in October N+1.
First dissemination in France is in January N+2 (only in legal unit and for internal use by the national accounts). Definitive dissemination – both in legal units for internal users and in enterprises – is in July N+2.
14.2. Punctuality
Data with 2022 as reference year have been delivered on June 28th 2024
15.1. Comparability - geographical
The same statistical concepts are applied in the entire national territory.
15.2. Comparability - over time
Series are comparable from 1996 to 2007.
There was a change of system for the production of results 2008.
Moreover, the results of 2010 and years after include a new category of small enterprises created in 2009 (“autoentrepreneurs” in French); this category, if not very important considering macro-economic aggregates (as turnover), is composed of numerous small units.
Moreover, the results from 2012 include for the first time some categories of small units without employees, kinds of French civil property companies and private management leasers, that are composed of numerous and in general small units, for most of them in sections F and L.
In addition, in 2015, the variable that defines the productive character of the statistical units belonging to the field has changed, which improves the way we define the SBS statistical population. Furthermore, branches of foreign units – that is local units not constituting separate legal entities but dependent on foreign enterprises and classified as quasi-corporations in accordance with ESA – which until 2014 were, with some exceptions, automatically considered as out of scope, are now potentially part of the scope, on the condition that they have declared a fiscal form to the French tax adminstration for the 2015 year or the previous year, and secondly that they have at least one employee.
Since the reference year 2017, the French SBS results are produced in enterprise, which leads to a major break in time series compared to the previous years, when the SBS results were produced mainly in legal units, except for some of the biggest groups which were manually profiled.
Finally, in 2021, agregate calculus method was modified: we changed from a composite method to a classical additive method. Thus, data are different from those calculated the previous years.
Employment:
From the year 2020, the number of employees provided in the Structural Business Statistics is estimated from a new source, which significantly improves the accuracy of the estimates. This change is being made in coordination with Business Demography Statistics as well as with the Business Register.
From the year 2021, we improve the number of employees (EMPL) as we managed to calculate an average number of employees over the year. Indeed, this information is now available within the Eurostat planning. Average number is calculated for emplyees only. For self-employed, we improved the estimation, but we still use the number of self-employed persons at 31/12 instead of average.
15.2.1. Time series
Time series
First reference year available (calendar year)
1996
Calendar year(s) of break in time series
2008, 2010, 2012, 2015, 2017, 2021
Reason(s) for the break(s)
2008 : change of system for the production
2010 : ajout des "autoentrepreneurs avec impact principal sur nb unit
2012 : coverage extension (most of them in sections F and L)
2015 : improved coverage: better consideration of the productive nature of the business + inclusion of foreign branches
2017 : change level unit : UL vs EP
2021 : agregate calculus method was modified: change from a composite method to a classical additive method. Better estimate of employment
Length of comparable time series (from calendar year to calendar year)
1996 to 2007
2008 to 2016 (modulo few sectors)
2017 to 2020
2021 to 2022
Comment
15.3. Coherence - cross domain
From 2021, SBS and BD use the same business register to delineate their respective scope, so the consistency between SBS and BD has been improved.
Nevertheless, the difference remains significant. We plan to reduce this gap by working on micro enterprises and the defintion of active unit.
15.4. Coherence - internal
The aggregates are always consistent with their main sub-aggregates (e.g. the total for different size classes, NACE, CPA, NUTS...). The modality FRZ (extra region) of NUTS is not taken into account for Eurostat validation checks. That explains messages appearing as "error" which are not relevant.
Esane was especially implemented to reduce businesses response burden. The use of administrative fiscal data enabled to drastically reduce the size of surveys questionnaire. An optimization of sampling design was carried on that enabled to reduce the size of the sample by half in take-some strata while keeping the same precision for estimates. Finally, a new coordination method has been introduced in 2013 : it enables coordination of all business surveys together, so as to smooth response burden between small and medium businesses while respecting each survey' sampling design. The method is described in more details in "Sampling coordination of business surveys conducted by Insee" a paper by Fabien Guggemos and Olivier Sautory, presented at the fourth International Conference on Establishment Survey (Montreal, 2012).
17.1. Data revision - policy
No revision policy has been put into place. However, revisions occur at least once a year when provisional data published in November is replaced by definitive data. Revisions also occur when methodological or scope changes are made. We estimate these revisions to approximately represent 0.2 point of the value added growth rate.
17.2. Data revision - practice
The data used for compiling the preliminary results comes from a first delivery of the fiscal files (arriving in Insee in July N+1).
Definitive data are elaborated with both supplementary files from the fiscal source and data coming from the surveys.
18.1. Source data
The sources are statistical survey combined with administrative source. The sample survey is conducted on a sample of legal units, and the administrative information is exhaustive.
18.1.1. Data sources overview
Data sources overview
Survey data
yes
VAT data
no
Tax data
no
Financial statements
yes
Other sources, please specify
Nominative Social Declaration (DSN) : administrative data
Comment
NA
18.2. Frequency of data collection
Annual data collection.
18.3. Data collection
SBS variables are essentially based on administrative data. However, the French production process includes the possibility of correcting some administrative data with survey data : the percentage of administrative data corrected by the survey is very low and concerns only cases with outliers values.
The survey
It was initially an exclusively postal survey by questionnaire. From the reference year 2012, it was possible to answer via internet by filling out a form identical to the paper questionnaire, with a specific file format. Web questionnaire is available since the reference year 2018.
The number of units surveyed is about 90 000.
Dashboards are used to follow-up non-response.
Enterprises are contacted again by mail twice if necessary and the fourth time with the threat of a financial sanction.
Specific e-mail are sent to very large companies if they did not answer the first time.
Administrative source
We use an extraction from the fiscal database, transmitted by fiscal administration
Moreover, this selective editing procedure carried out on a continuous flow basis during the production process is supplemented by a final output editing process.
Finally, Edit tool controls are computed before sending data to Eurostat (format and file structure checks, Intra-dataset checks, Inter-dataset checks, times series checks).
Inference (grossing-up):
Statistical combined estimates are used, described in detail in this webpage.
18.5. Data compilation
Imputation is used to treat item non‑response for all take‑some units in the survey. For the take‑all units as well as the administrative data, imputation is used to treat both item and unit non‑response.
Imputation by historical data – using the previous reference period – is carried out as far as possible, otherwise, the mean, median or ratio imputation by class method is used.
18.6. Adjustment
In case the enterprise has a fiscal year different from the calendar year, the data of this fiscal year are affected to the calendar year including the most important part of the fiscal year
Many activity sectors have been severely affected by the Covid19 pandemic. 2022 is the year of the recovery of the global economy. Confinements and curfews were still in force in 2021. In addition, 2022 was marked by high inflation in raw materials, including energy.
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 2division level (2-digits).
28 August 2024
SBS constitutes an important and integrated part of the new European Business Statistics Regulation N° 2152/2019
Since the reference year 2017, the French SBS results are produced in enterprise, and are fully complient with the statistical unit Regulation N° 696/93.
However, the data transmitted by the French National Bank for class 64.11, 64.19 and division 65 are in legal units.
The data collection units are mainly the legal units. For the biggest groups, which are manually profiled, some data are collected at the enterprise level. For the others, automatic profiling is carried out using legal unit data only.
The French SBS system Esane covers all market and economically consistent units, without any threshold of size, excluding financial units (save for class 64.20 and division 66) and agriculture.
The statistics produced by the Esane process are supplemented by results produced by the French National Bank for class 64.11, 64.19 and division 65.
Only activities conducted on the French territory including overseas departments are considered.
Branches of foreign units – that is local units not constituting separate legal entities but dependent on foreign enterprises and classified as quasi-corporations in accordance with ESA –, were, until 2014, with some exceptions, automatically considered as out of scope. They are now potentially in the scope, on the condition that they have declared a fiscal form to the French tax administration for the reference year or the previous year and secondly that they have at least one employee.
2022 Data refer to calendar year
As in all statistical process involving a survey, the results of the Esane system can be affected by sampling errors, coverage errors, non-response and measurement errors.
However, as we will see in the following paragraphs, in principle, none of these potential sources of errors leads to a significant bias on the results.
The French business register has no under coverage problems, and the use of external administrative information allows us to deal with the problem of over coverage.
A complex data editing process – based on selective editing combined with micro-editing for the data editing carried out on a continuous flow basis during the production process supplemented by a final output editing process – aims to reduce as much as possible the significant measurement errors.
Imputation procedures – imputation by historical information, failing that by class imputation means or medians – and reweighting procedures are used to deal with missing units/items, both in survey and administrative data. We try also to minimise the non-response in the survey, thanks to the mandatory character of the survey and to a strict follow-up procedure.
Finally, the use of a complex adjustment procedure – involving the non-response adjustment steps already mentioned, a winsorization procedure and a calibration on margins based on administrative data – and calculating aggregates by simple sum using jointly survey and administrative data tends to reduce as much as possible the non-response bias and to improve the accuracy of the statistics on the main variables of interest.
The change in method from a specific estimator to a simple sum leads to zero variance. However the new estimators are biased (although we try to reduce this bias - see above).
• 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.
Imputation is used to treat item non‑response for all take‑some units in the survey. For the take‑all units as well as the administrative data, imputation is used to treat both item and unit non‑response.
Imputation by historical data – using the previous reference period – is carried out as far as possible, otherwise, the mean, median or ratio imputation by class method is used.
The sources are statistical survey combined with administrative source. The sample survey is conducted on a sample of legal units, and the administrative information is exhaustive.
Annual.
For the statistical survey, data collection spreads from February to December N+1.
For the administrative data: we receive different files between April N+1 and January N+2, considered for SBS data of reference year N.
Preliminary data (built from the administrative source) are sent to Eurostat in October N+1.
First dissemination in France is in January N+2 (only in legal unit and for internal use by the national accounts). Definitive dissemination – both in legal units for internal users and in enterprises – is in July N+2.
The same statistical concepts are applied in the entire national territory.
Series are comparable from 1996 to 2007.
There was a change of system for the production of results 2008.
Moreover, the results of 2010 and years after include a new category of small enterprises created in 2009 (“autoentrepreneurs” in French); this category, if not very important considering macro-economic aggregates (as turnover), is composed of numerous small units.
Moreover, the results from 2012 include for the first time some categories of small units without employees, kinds of French civil property companies and private management leasers, that are composed of numerous and in general small units, for most of them in sections F and L.
In addition, in 2015, the variable that defines the productive character of the statistical units belonging to the field has changed, which improves the way we define the SBS statistical population. Furthermore, branches of foreign units – that is local units not constituting separate legal entities but dependent on foreign enterprises and classified as quasi-corporations in accordance with ESA – which until 2014 were, with some exceptions, automatically considered as out of scope, are now potentially part of the scope, on the condition that they have declared a fiscal form to the French tax adminstration for the 2015 year or the previous year, and secondly that they have at least one employee.
Since the reference year 2017, the French SBS results are produced in enterprise, which leads to a major break in time series compared to the previous years, when the SBS results were produced mainly in legal units, except for some of the biggest groups which were manually profiled.
Finally, in 2021, agregate calculus method was modified: we changed from a composite method to a classical additive method. Thus, data are different from those calculated the previous years.
Employment:
From the year 2020, the number of employees provided in the Structural Business Statistics is estimated from a new source, which significantly improves the accuracy of the estimates. This change is being made in coordination with Business Demography Statistics as well as with the Business Register.
From the year 2021, we improve the number of employees (EMPL) as we managed to calculate an average number of employees over the year. Indeed, this information is now available within the Eurostat planning. Average number is calculated for emplyees only. For self-employed, we improved the estimation, but we still use the number of self-employed persons at 31/12 instead of average.
