ICT usage in enterprises (isoc_e)

National Reference Metadata in SIMS structure for INFOSOC Enterprises

Compiling agency: INSEE (for the French Public Statistical System - SSP)


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)



For any question on data and metadata, please contact: Eurostat user support

Download


1. Contact Top
1.1. Contact organisation

INSEE (for the French Public Statistical System - SSP)

1.2. Contact organisation unit

Division Enquêtes thématiques et études transversales - Timbre E430

1.5. Contact mail address

88 avenue Verdier CS 70058
92541 Montrouge Cedex


2. Metadata update Top
2.1. Metadata last certified 03/11/2023
2.2. Metadata last posted 08/04/2024
2.3. Metadata last update 08/04/2024


3. Statistical presentation Top
3.1. Data description

Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.

Large part of the data collected is used to measure the progress in the implementation of one of the main political priorities of the European Commission for 2019 to 2024 – A Europe fit for the digital age. Part of this is the "European strategy for data", envisioning a single market for data to ensure the EU's global competitiveness and data sovereignty, in which context a comprehensive set of new rules for all digital services was proposed: the Digital Services Act and the Digital Markets Act, which are centrepieces of the EU digital strategy. Furthermore, the Commission and the High Representative of the Union for Foreign Affairs and Security Policy presented a new “EU cybersecurity strategy”, which is intended to bolster the EU's collective resilience against cyber threats, safeguard a global and open internet and protect EU values and the fundamental rights of its people. Furthermore, data will allow monitoring the progress towards  A Europe fit for the digital age, one of the six priorities for the period 2019-2024 of the von der Leyen European Commission.

The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.

 

Name of data collection
 TIC 2023
3.2. Classification system

 NACE Rev.2 2008

3.3. Coverage - sector

All economic activities in the scope of Annex I of the Commission Regulation are intended to be included in the general survey, covering enterprises with 10 or more employees and self-employed persons. These activities are: NACE Rev. 2 sections C, D, E, F, G, H, I, J, L, M and N, division 95.1.

For micro-enterprises see the sub-concepts below.

3.3.1. Coverage-sector economic activity for micro-enterprises - All NACE Rev. 2 categories are covered
3.3.2. Coverage sector economic activity for micro-enterprises - If not all activities were covered, which ones were covered?

Micro-enterprises are not included in the survey.

3.4. Statistical concepts and definitions

The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following areas:

-          Access to and use of the Internet

-          E-commerce and e-business

-          Use of cloud computing services

-          Artificial Intelligence

-          Other topics: Data utilisation, sharing, analytics and trading, Invoicing.

The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.

3.5. Statistical unit

Enterprise

3.6. Statistical population

Target Population

As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons shall be covered by the survey.

For micro-enterprises see the sub-concepts below.

3.6.1. Coverage of micro-enterprises
No
3.6.2. Breakdown between size classes [0 to 1] and [2 to 9]
No
3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.

Not applicable

3.7. Reference area

 France (all territory, including overseas regions).

3.8. Coverage - Time

Years 2022 and 2023.

3.9. Base period

Not applicable


4. Unit of measure Top

Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro.


5. Reference Period Top

Reference periods defined in the model questionnaire were followed in the national survey.


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

Complementary national legislation constituting the legal basis for the survey on the use of ICT in enterprises:

The survey is mandatory at national level. Non-respondent units can be fined by the litigation commitee after the data collection period.

6.2. Institutional Mandate - data sharing

Data are shared on demand within the national statistical system.


7. Confidentiality Top
7.1. Confidentiality - policy

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.

At national level :

No cell of the table may concern less than three units.

No cell of the table may contain data for which a company represents more than 85 % of the total.

No cell of the table can be calculated from other cells.

 

7.2. Confidentiality - data treatment

Data are transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. Flags are added for confidentiality in case results must not be disclosed.

At national level : 

The tool Tau-Argus is used to identify values to flag as confidential.


8. Release policy Top
8.1. Release calendar

Some indicators calculated from microdata are planned to be disseminated in December 2023.

A publication analysing results of the survey is planned to be released in April 2024.

There is a short-time release calendar on Insee website.



Annexes:
Short time release calendar
8.2. Release calendar access

Not available.

 

8.3. Release policy - user access

Data tables of indicators and a thematic analyse are publicly disseminated on our website Insee.fr. Information on publication releases is given by Insee twitter account. Users can also subscribe to the newsletter on Insee.fr.



Annexes:
Data tables of 2022 ICT survey on enterprises
Analysis publication related to 2022 ICT survey on enterprises
National X (twitter) account


9. Frequency of dissemination Top

Annual


10. Accessibility and clarity Top
10.1. Dissemination format - News release

National dissemination of results

Information on publication releases is given by Insee twitter account. Users can also subscribe to the newsletter on Insee.fr.

10.2. Dissemination format - Publications

National dissemination of results

Some indicators calculated from microdata are planned to be disseminated in December 2023.

A publication analysing results of the survey is planned to be released in April 2024.



Annexes:
Dissemination of results location
10.3. Dissemination format - online database

See detailed section 10.3.1.

10.3.1. Data tables - consultations

Results for selected variables collected in the framework of this survey are available for all participating countries on Digital economy and society of Eurostat website.

At national level :

 

Every survey year leads to a database publication, there is no fixed location on the Insee website for a unique database.

The number of consultations is not available.

 

10.4. Dissemination format - microdata access

Microdata are disseminated via the CASD. Any access has to be justified and granted (for example a study of a PHD student) by the Insee comité du secret. Some restrictions (for example relating to confidentiality) are indicated to users.



Annexes:
CASD website
10.5. Dissemination format - other

Not requested

10.5.1. Metadata - consultations

Not requested

10.6. Documentation on methodology

A national quality report is published in French and in English in SIMS format.

10.6.1. Metadata completeness - rate

Not requested

10.7. Quality management - documentation

At the end of the survey, a methodological documentation of every part of the survey process is published with microdata (with restricted access, see 10.4).


11. Quality management Top
11.1. Quality assurance

The European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises provides guidelines and standards for the implementation of the surveys. It is updated every year according to the changed contents of the model questionnaires.

At national level :

The Methodological Manual provides guidelines and standards for the implementation of the surveys in the Member States. It is updated every year according to the changed contents of the model questionnaires.

The quality informations are filled in the SIMS format.

11.2. Quality management - assessment

European level :

At European level, the recommended use of the annual Eurostat model questionnaire aims at improving comparability of the results among the countries that conduct the survey on ICT usage and e-commerce in enterprises. Moreover, the Methodological Manual provides guidelines and clarifications for the implementation of the surveys.

National level :

Model questionnaire is translated to produce the national questionnaire. Methodological Manual guidelines are also used.


12. Relevance Top
12.1. Relevance - User Needs

European level : 

At European level, European Commission users (e.g. DG CNECT, DG GROW, DG JUST, DG REGIO, DG JRC) are the principal users of the data on ICT usage and e-commerce in enterprises and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaires at a very early stage.

User needs are considered throughout the whole discussion process of the model questionnaires aiming at providing relevant statistical data for monitoring and benchmarking of European policies.

National level :

Once available, the model questionnaire is translated into French and discussed with national stakeholders (from administrations and civil society) and users (e.g. researchers). The discussion includes fine-tuning the translations, choosing the proper examples, deciding on the optional questions considering the overall response burden/length of the questionnaire and sometimes adding national questions.

12.2. Relevance - User Satisfaction

European level : 

At European level, contacts within the Commission, the OECD and other stakeholders give a clear picture about the key users' satisfaction as to the following data quality aspects: accuracy and reliability of results, timeliness, satisfactory accessibility, clarity and comparability over time and between countries, completeness and relevance. Overall users have evaluated positively (good, very good) the data quality on the ICT usage and e-commerce in enterprises.

National level :

A satisfaction survey is being conducted from March until June 2020 on data users (users displaying ICT survey aggregated data and publications on the NSI website or being granted an access to ICT survey microdata through CASD.eu). Results have been detailed in the 2020 quality report.

During the annual meeting concerning the national questionnaire, users provide feedback on the survey.

12.3. Completeness

Detailed information is available in “ Annex I _ Completeness “ excel file - related to questionnaire, coverage, additional questions.



Annexes:
Annex I _ Completeness
12.3.1. Data completeness - rate

Not requested. 


13. Accuracy Top
13.1. Accuracy - overall

Comments on reliability and representativeness of results and completeness of dataset

These comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).

More detailed information is available in “ Annex II. _ Accuracy “ excel file - related to European aggregates, comments on reliability and use of flag.



Annexes:
Annex II. _ Accuracy
13.2. Sampling error

For calculation of the standard error see 13.2.1.1.

13.2.1. Sampling error - indicators

Standard error (for selected indicators and breakdowns)

Precision measures related to variability due to sampling, unit non-response (the size of the subset of respondents is smaller than the size of the original sample) and other (imputation for item non-response, calibration etc.) are not (yet) required from the Member states for all indicators.  Eurostat will make basic assumptions to compute these measures for all indicators produced (e.g. stratified random sampling assuming as strata the crossing of the variables “Number of employees and self-employed persons” and “Economic Activity” as it was defined in the 3 tables of section 18.1).

More detailed information is available in“ Sample and standard error tables 2023 “ excel file – worksheets starting with “Standard error".

13.2.1.1. Sampling error indicator calculation

Calculation of the standard error

Various methods can be used for the calculation of the standard error for an estimated proportion. The aim is to incorporate into the standard error the sampling variability but also variability due to unit non-response, item non-response (imputation), calibration etc. In case of census / take-all strata, the aim is to calculate the standard errors comprising the variability due to unit non-response and item non-response.

a) Name and brief description of the applied estimation approach
The SAS macro “Everest” developed at Insee is used.
The standard error is calculated as sqrt(variance)*100.
Variance due to sampling, to unit non-response, to calibration and winsorization is taken into account, but not variance due to item non-response. Our variance estimations are therefore under-estimated.

 

b) Basic formula
see annex 'std_error_basic_formula_FR'

 

c) Main reference in the literature
Philippe Brion / Emmanuel Gros

 

d) How has the stratification been taken into account? 
See above 

 

e) Which strata have been considered? 
The strata considered have been the sampling strata, and the response homogeneity groups (non response has been considered as a second phase sampling). 


Annexes:
Standard error basic formula
13.3. Non-sampling error

See detailed sections below.

13.3.1. Coverage error

See concept 18.1.1. A) Description of  frame population.

13.3.1.1. Over-coverage - rate

Over-coverage is treated during collection:
-during data collection, if a unit states that it is out of scope, mostly because they stopped existing or their number of persons employed dropped under 5* persons, it is properly flagged and excluded from the data
processing;
-an estimate of the share of over-coverage due to ceased units (not existing anymore) is calculated and used during calibration step.
Over-coverage concerns about 2% of units in the sample (excluded from final data).
*threshold of 5 persons instead of 10 is used to compensate for the units that were not included in the frame because they were registered below 10 in the business register, though they would have 10 or more persons employed at the time of the survey

13.3.1.2. Common units - proportion

Not requested

13.3.2. Measurement error

None

13.3.3. Non response error

See detailed sections below.

13.3.3.1. Unit non-response - rate

See detailed sub-concepts below.

13.3.3.1.1. Unit response

The following table contains the number of units (i.e. enterprises), by type of response to the survey and by the percentage of these values in relation to the gross sample size.

 

Type of response Enterprises
0-9 employees and self-employed persons 10 or more employees and self-employed persons
Number % Number %
Gross sample size (as in section 3.1 C)   100%  14217 100%
1. Response (questionnaires returned by the enterprise)      9667 68%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)     9399 66%
1.2 Not used for tabulation     268 2%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)      268 2%
1.2.2 Other reasons (e.g. unusable questionnaire)      0 0%
2. Non-response (e.g. non returned mail, returned mail by post office)     4550 32%

 

Comments on unit response, if unit response is below 60%
 
13.3.3.1.2. Methods used for minimizing unit non-response

Monitoring the survey included the following phases:
- First reminder by mail one month after having sent the first letter;
- Second reminder by mail 20 days after (giving notice to answer);
- No response statements 30 days after;
- Fine for main non-responding units (not this first year on enterprises);
A systematic phone call reminder was organised at the same time for the most important units.
Reminders are sent to respondents who have logged in the response website but have not finilized and send the questionnaire.

13.3.3.1.3. Methods used for unit non-response treatment
1. No treatment for unit non-response  
2. Treatment by re-weighting
2.1 Re-weighting by the sampling design strata considering that non-response is ignorable inside each stratum (the naïve model)  
2.2 Re-weighting by identified response homogeneity groups (created using sample-level information)  x
2.3 Re-weighting through calibration/post-stratification (performed using population information) by the groups used for calibration/post-stratification  x
3. Treatment by imputation (done distinctly for each variable/item)  
4. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of unit non-response. (e.g. Re-weighting using Horvitz-Thompson estimator, ratio estimator or regression estimator, auxiliary variables )
First step of re-weighting is based on the GRH method (response homogeneity groups). Several characteristics were found (by logistic regression models) to explain most of the bias due to nonresponse behaviour, mainly economic activity, geographic localisation, legal situation, staff bracket, accounting information.
Second step of re-weighting is calibration on known margins, using population information.
13.3.3.1.4. Assessment of unit non-response bias

Not available

13.3.3.2. Item non-response - rate

Not available

13.3.3.2.1. Methods used for item non-response treatment
1. No treatment for item non-response  
2. Deductive imputation
An exact value can be derived as a known function of other characteristics.
 x
3. Deterministic imputation (e.g. mean/median, mean/median by class, ratio-based, regression-based, single donor nearest-neighbour)
Deterministic imputation leads to estimators with no random component, that is, if the imputation were to be re-conducted, the outcome would be the same
 
4. Random imputation (e.g. hot-deck, cold-deck)
Random imputation leads to estimators with a random component, that is, if the imputation were re-conducted, it would have led to a different result
 x
5. Re-weighting  
6. Multiple imputation
In multiple imputation each missing value is replaced (instead of a single value) with a set of plausible values that represent the uncertainty of the right value to impute. Multiple imputation methods offer the possibility of deriving variance estimators by taking imputation into account. The incorporation of imputation into the variance can be easily derived based on variability of estimates among the multiply imputed data sets.
 
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
A two-step method is used:
- First, series of deductive rules are defined and used when possible (taking into account the global consistency of the questionnaire).
- Secondly, when this is not possible, groupings of units having the same response behaviour regarding a specific question (or a class of questions linked) are defined. A hot-deck procedure is implemented within the grouping taking into account the distribution of answers within this group.
For background questions, other sources may be used (turnover and number of persons employed).
13.3.3.2.2. Questions or items with item response rates below 90% and other comments

Other comments relating to the item non-response

Additional issues concerning "non-response" calculation (e.g. method used in national publications).
 Not available

 

Questions and items with low response rates (cut-off value is 90% ) and item non-response rate.
 No response rate under 90% (minimum for A3 (92,8%))
13.3.4. Processing error

There is no imputation for unit non-response (treated with reweighing).

The imputation rates for item non-response are attached (file Imputation_rates_2023.ods).



Annexes:
2023 imputation rates by variable
13.3.5. Model assumption error

Not requested


14. Timeliness and punctuality Top
14.1. Timeliness

See detailed section below.

14.1.1. Time lag - first result

Not applicable

14.1.2. Time lag - final result

European level : 

Data are to be delivered to Eurostat in the fourth quarter of the reference year (due date for the finalised dataset is 5th October). European results are released before the end of the survey year or in the beginning of the year following the survey year (T=reference year, T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year e.g. e-commerce).

At national level : 

December of the reference year. T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year.

14.2. Punctuality

 See detailed section below.

14.2.1. Punctuality - delivery and publication

 

Date of data delivery to Eurostat : 05/10/2023



15. Coherence and comparability Top

The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in reference periods, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the metadata.

15.1. Comparability - geographical

The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.

Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I _ Completeness “ excel file - related to questionnaire, coverage, additional questions.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable

15.2. Comparability - over time

See section below.

15.2.1. Length of comparable time series

The length of comparable time series depends on the module and the variable considered within each survey module. Additional information is available in annexes attached to the European metadata.

No significant change that could impact the comparability with previous year.

15.3. Coherence - cross domain

Not applicable

15.3.1. Coherence - sub annual and annual statistics

 Not applicable

15.3.2. Coherence - National Accounts

Not applicable

15.4. Coherence - internal

Not applicable


16. Cost and Burden Top
Restricted from publication


17. Data revision Top
17.1. Data revision - policy

Should a considerable mistake be noticed after the timely data transmission, a corrected table would be produced and sent, even years after (as was done in 2018 to fix mistakes in number of person  employed in 2016 data).

17.2. Data revision - practice

Not available

17.2.1. Data revision - average size

 Not requested


18. Statistical processing Top
18.1. Source data

A) Frame population description and distribution

For more information see concept 18.1.1.

 

B) Sampling design - Sampling method

Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata: 

 

This section includes a description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE categories related to the "possible calculation of European aggregates", and the final number of strata.

 

The sample is stratified by sector (divisions or groupings of divisions), reported employment and turnover (about 200 non-empty strata each year). Random sampling is used for most strata. A full enumera on is used for strata meeting one of the following criteria (take-all strata):
• 500 persons employed and more
• High level of turnover (“high” depends on the employment range (e.g. >=100 M€ for 10-19 persons employed strata, turnover>=110 M€ for 20-49 persons employed strata, etc.))
• Retail sale via mail order houses or via Internet (NACE 47.91A and 47.91B) (to gain precision in the measure of the e-sales amounts)
Local accuracy constraints are added to improve the quality of the results for small strata. The goal is that in every breakdown, the estimated standard error shall be less than 5 percentage points. Last, the response rate per strata from the previous year is used to  adjust the number of units in each stratum (increasing the size of strata with lesser response rates). Coordination with the sampling of 2022 ICT survey (only for single legal units this year due to statistical unit transition from legal unit to enterprise) is done in order to keep in 2023 half of the sample of the 2022 survey (besides the take-all strata). That way, we steady the year-to-year comparisons, especially for e-sales amounts.
Negative coordination with most of the other surveys led in 2022 by Insee is done to make sure the response burden is equally shared within the enterprises (other than the enterprises belonging to a takeall strata).

 

 

C) Gross sample distribution

More detailed information is available in “ Sample and standard error tables 2023  “ excel file (Worksheet: GROSS SAMPLE)

 

D) Net sample distribution

More detailed information is available in “ Sample and standard error tables 2023  “ excel file (Worksheet: NET SAMPLE)



Annexes:
Sample and standard error tables 2023
18.1.1. Population frame

A) Description of frame population

a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn? November 2022                         
b) When was the last update of the Business register that was used for drawing the sample of enterprises for the survey?  October 2022
c) Please indicate if the frame population is the same as, or is in some way coordinated with, the one used for the Structural Business Statistics (different snapshots)  Yes
d) Please describe if different frames are used during different stages of the statistical process (e.g. frame used for sampling vs. frame used for grossing up):  No
e) Please indicate shortcomings in terms of timeliness (e.g. time lag between last update of the sampling frame and the moment of the actual sampling), geographical coverage, coverage of different subpopulations, data available etc., and any measures taken to correct it, for this survey.  None

 

 B) Frame population distribution

More detailed information is available in “ Sample and standard error tables 2023  “ excel file (Worksheet: FRAME POPULATION)

18.2. Frequency of data collection

Annual

18.3. Data collection

See detailed sections below.

18.3.1. Survey period
Survey / Collection Date of sending out questionnaires Date of reception of the last questionnaire treated
General survey  2023 January 31th  2023 June 30th
Micro-enterprises  Not applicable  Not applicable
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
The collection of micro-enterprises was integrated with the general survey
18.3.4. Survey type

Web survey (using phone, mails and emails for reminders and further information). If the enterprise doesn't want to answer using the website, self-administered mail survey (less than 1% of the respondents, either paper or email PDF).

18.3.5. Survey participation
Mandatory
18.4. Data validation

The server based validation tool by Eurostat is used. We also check for consistency during various stages of the data collection and processing.

18.5. Data compilation

Grossing-up procedures

As for the majority of surveys at INSEE, the procedure used is calibration on margins using CALMAR (SAS macro “calage sur marges”).
Margins are the number of enterprises by group of economic activity, staff size and turnover in the frame population.

18.5.1. Imputation - rate

There is no imputation for unit non-response (treated with reweighing).
The imputation rates for item non-response are attached (file Imputation_rates_2023.ods).



Annexes:
2023 imputation rates
18.6. Adjustment

Not applicable

18.6.1. Seasonal adjustment

Not applicable


19. Comment Top

Problems encountered and lessons to be learnt: 

19.1. Documents
Questionnaire in national language  x
Questionnaire in English (if available)  x
National reports on methodology (if available)  x
Analysis of key results, backed up by tables and graphs in English (if available)  
Other Annexes  


Annexes:
Questionnaire in English
Questionnaire in national language
Internal note - sampling request
Internal note - sampling delivery


Related metadata Top


Annexes Top
Annex I._Completeness 2023
Annex II._ Accuracy 2023
Sample and standard error tables 2023