ICT usage in enterprises (isoc_e)

National Reference Metadata in SIMS structure for INFOSOC Enterprises

Compiling agency: ISTAT – Italian National Institute of Statistics


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

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1. Contact Top
1.1. Contact organisation

ISTAT – Italian National Institute of Statistics

1.2. Contact organisation unit

ISTAT – Italian National Institute of Statistics

Department for statistical production DIPS/DCSE/SEC

1.5. Contact mail address

ISTAT

Department for statistical production DIPS/DCSE/SEC

Via Tuscolana 1776 - 00173 Rome - Italy


2. Metadata update Top
2.1. Metadata last certified 28/02/2024
2.2. Metadata last posted 28/02/2024
2.3. Metadata last update 28/02/2024


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
 Rilevazione sulle tecnologie dell'informazione e della comunicazione nelle imprese
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

Statistical unit used for analysis is the enterprise but the questionnaire is sent to single legal units included in the enterprise as reported by BR on enterprises and BR on legal units.

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

All the territory of the country is considered.

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.


5. Reference Period Top

The reference periods defined in the model questionnaire are 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:

National Statistical Programme-Psn 2020-2022, updating 2021-2022, published in the Ordinary Supplement no. 7 to the Official Gazette - general series - n. 44 of 21 February 2023. 

 

6.2. Institutional Mandate - data sharing
Legislative decree 6 September 1989, n. 322, "Rules on National Statistical System and on the reorganization of the National Statistical Institute" - art. 6 (duties of the offices statistics), art. 6-bis (processing of personal data), art. 7 (obligation to provide statistical data), art. 8 (official secrecy of employees of statistical offices), art. 9 (provisions for the protection of statistical secrecy), art. 11 (sanctions administrative), art. 13 (National Statistical Programme);
 
Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on protection of individuals with regard to data processing personal data, as well as to the free  movement of such data and that repeals Directive 95/46/EC (General Regulation on data protection);
 
Legislative Decree 10 August 2018, n. 101 “Provisions for the adaptation of the national legislation to the provisions of regulation (EU) 2016/679 of European Parliament and of the Council, of 27 April 2016”, relating to the protection of natural persons with regard to the processing of personal data (General Regulation on data protection).

 


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 : 

 Legislative references:

 1)  Legislative Decree 30 June 2003, n. 196, "Code regarding the protection of personal data" - art. 4 (definitions), Art. 104-110 (treatment for statistical or scientific purposes);

 2) "Code of ethics and good conduct for the processing of personal data for statistical and scientific research carried out as part of the National Statistical System" (all. A.3 of the Code regarding the protection of personal data - Leg. 30 June 2003, n. 196).

In the letter sent to enterprises we assure that the data collected, are protected by statistical confidentiality and, in the case of personal information, by law on the protection of such data and that data may be used for subsequent treatments, exclusively for statistical purposes by the subjects of the National Statistical System. May also be communicated for the purposes of scientific research subject to the conditions and in the manner prescribed by art.7 of the Code of conduct on the processing of personal data within the framework of the National Statistical System. The same data will be disseminated in an aggregated form, in such a way that can not be traced to individuals who provide them or to which they relate.

 Please, see for information (in Italian) https://www.istat.it/it/organizzazione-e-attivit%C3%A0/organizzazione/normativa

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 : 

For this survey we use general criterion about minimum number of enterprises by breakdowns.


8. Release policy Top
8.1. Release calendar

December 2023 (internal calendar).

8.2. Release calendar access

https://www.istat.it/en/information-and-services/journalists/press-releases-/press-calendar

8.3. Release policy - user access

 

Online release is foreseen in December via web site (www.istat.it)

 

The release consist in publication on homepage of Istat' website of a brief important result linked to:

 - Statistical Report on results;

 - Methodological note;

 - Data dissemination in the data wharehouse I.Stat (http://dati.istat.it/), theme Enterprises, subtheme Information Society.

 


9. Frequency of dissemination Top

Annual


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

National dissemination of results

Release is foreseen in December (Statistical Report linked to Data dissemination).

10.2. Dissemination format - Publications

National dissemination of results


Release is foreseen in December (Statistical Report and Data dissemination in the
data wharehouse I.Stat, theme Enterprises, subtheme Information Society)

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 :

Results for selected variables collected in the framework of this survey are available for all on national Istat data wharehouse of Istat website dedicated to ICT Survey.

10.4. Dissemination format - microdata access

Istat provides microdata files from its surveys free of charge for study and research purposes or for statistical-scientific purposes, in compliance with the regulations in force.

The files released are those available at the time of the request and may be subject to statistical revisions.

For more information https://www.istat.it/en/analysis-and-products/microdata-files

10.5. Dissemination format - other

Not requested

10.5.1. Metadata - consultations

Not requested

10.6. Documentation on methodology

It is possible to find Survey description in Istat Information system on quality of statistical production processes (see link: http://siqual.istat.it/SIQual/visualizza.do?id=5000078)

10.6.1. Metadata completeness - rate

Not requested

10.7. Quality management - documentation

Nota available.


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 :

At national level, quality is assured by guidelines, test on online questionnaire and rules implemented linked with filling in the model, contact center workers training, scheduling the reminders, monitoring data collection.

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 :

At national level Eurostat recommendation are implemented, enterprise are helped with contact center, faq, guidelines.


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 :

Istat uses working groups for the preparation of the National Statistical Program (Psn). Six sectors have been identified, coordinated by directors, who deal with the activities related to the preparation of the Psn. Each sector is then divided into thematic areas coordinated by experts (Istat service managers or other experts in the field).

 

The working group in which is included the ICT survey is responsible to analyse the supply and demand for statistical information for the Psn. The participants are from other public Institutions or private sector.

 

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 :

At national level we don't measure this topic yet.

12.3. Completeness

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

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.

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 coefficient of variation is given by the square root of the variance of the estimator out of its expected value.

It is estimated by the ratio of the square root of the estimated sampling variance to the estimated value of the variable of interest.
Standard errors are calculated using the Taylor linearization technique (ReGenesees, is the software used to calculate standard errors, confidence intervals for Totals, Means, absolute and relative Frequency Distributions, Ratios)

 

b) Basic formula

 

 

 

c) Main reference in the literature
Särndal. C. E.. Swensson. B. and Wretman. J.. 1992, Model Assisted Survey Sampling, Springer-Verlag, New York.

Särndal. C. E.. Swensson. B. and Wretman. J.. 1989, The weighted residual technique for estimating the variance of the general regression estimator of the finite population total. Biometrika. vol.76. n.3. pp. 527-537.

 

d) How has the stratification been taken into account? 
 The estimation of the sampling variance has taken into account sampling design and changes of strata.

 

e) Which strata have been considered? 
 Strata are defined as combination of Economic Activities, Size Classes (defined by number of persons employed) and Administrative Regions,
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

The rate of enterprises out of scope is 3,2%.

13.3.1.2. Common units - proportion

Not requested

13.3.2. Measurement error

Not available.

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% 25646 100%
1. Response (questionnaires returned by the enterprise)     17770  69.3 
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)     16947  66.1 
1.2 Not used for tabulation     823  3.2 
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)     823  3.2 
1.2.2 Other reasons (e.g. unusable questionnaire)    
2. Non-response (e.g. non returned mail, returned mail by post office)     7876  30.7 

 

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

 

a) activities for preventing unit non-response: to guarantee on statistical confidentiality, written description of survey objectives, special care in writing clear instructions to fill-in questionnaires, establishing telephone numbers for further explanations, survey presentation letter signed by Istat’s President or Head of Directorate, to specify that survey is mandatory for enterprises;

b) follow-ups of non-respondent units (reminders by telephone, postal services and e-mailing system);

c) since 2016 usage of centralised contact center that is trained on specific technical topics (usage of FAQ); enterprises can open a 'ticket' to be recontacted by unit involved in the survey for specific and problems directly linked with ICT concepts.

 

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)  
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 )
 
The method used for treatment considers:
- auxiliary variables: no. of enterprises, no. of employed; known totals of auxiliary variables calculated from Italian updated BR (ASIA 2020-ENT);
- calibration domains;
- in the calibration process distance function used is the raking function, corresponding to the
"multiplicative method" of Deville, Särndal, Sautory, 1993; (Ref. Deville, J.C., Särndal, C.E., Sautory, O. - 1993, "Generalized Raking Procedures in Survey
Sampling", Journal of the American Statistical Association, Vol. 88, No. 423, pp. 1013-1020)
- sigma2 corresponds to no. of persons employed (Sigma2 is the argument used to take into account a
possible heteroskedasticity effect in the calibration model; it corresponds to the 1/q_k unit-weights
appearing inside the distance measures of Deville, J.C., Särndal, C.E. 1992. (Ref. Deville, J.C., Särndal, C.E. - 1992 "Calibration Estimators in Survey Sampling", Journal of the American Statistical Association, Vol. 87, No. 418, pp. 376-382).
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
 
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.
 We use the following editing and imputation procedures:

-deterministic error and outlier detection and imputation based on deterministic rules (IF-THEN);

-deterministic imputation based on previous year answers (if possible), median values, re-weighting in case of quantitative variable.

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.
 Not available.
13.3.4. Processing error

No processing errors were detected.

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 : 

No deviation.

14.2. Punctuality

 See detailed section below.

14.2.1. Punctuality - delivery and publication

Data were delivered six days before deadline.


15. Coherence and comparability Top
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 comment at national level, with exception for the fact that introduction of enterprise statistical unit in year 2021 may have an impact on the comparability over time of the results delivered to Eurostat since before year 2021 to 2021 onwards.

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

At the moment of publication, the statistics are classified as final so we do not need of any revision policy for ICT survey.

17.2. Data revision - practice
Changes in the methodology used in data collection or in the definition of variables are indicated in a note when data are published.
Corrections are possible in case of relevant errors in collected data, computation errors; in this case it is published a note on the website or on the document with which the corrected data are released.
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: 

Use of stratified random sample for statistical unit Enterprise (Ent), with strata = 35 Nace sectors (see note 1) x 2 ICT sectors (see note 2) x 4 size classes (see note 3) x 21 regions.

The sample allocation is calculated by applying a multivariate and multi-domain technique (Bethel, 1989). The solution is optimal with respect to two variables (see note 4) and four domains (see note 5), by imposing stronger constraints on the expected coefficients of variations for the couple “variable‑domain” than those required.

We take a census of enterprises with at least one of the following conditions: 250 and more persons employed; Nace= 47911; Nace=47 and no. persons employed≥49.5; Ateco=61.

 

(1) 35 Nace sectors: 10-12; 13-15; 16-18; 19; 20; 21; 22-23 ; 24-25; 26; 27; 28; 29-30; 31-33; 35; 36-39; 41-43; 45; 46; 47 except 47911; 47911; 49-52; 53; 55; 56; 58; 59-60; 61; 62-63; 68; 69–71 ; 72; 73–75 ; 77-78+80-82; 79; 95.1.

(2) 2 ICT-sectors: 26.1, 26.2, 26.3, 26.4, 26.8, 46.5, 58.2, 61, 62, 63.1 e 95.1; other sectors.

(3) 4 Size classes in terms of persons employed: 10-49;50-99;100-249; ≥250.

(4) The two variables are: number of persons employed and turnover.

(5) The four domains are: 35 Nace sectors; 2 ICT-sectors; 4 major sectors (Industry, Energy, Construction, Services) x 4 size classes; 4 major sectors x 21 regions

 

 

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)

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? April 2023                    
b) When was the last update of the Business register that was used for drawing the sample of enterprises for the survey? June 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) It is the same
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):

BR used for sampling is referred to year 2020; BR and Frame used for grossing up is referred to 2021.

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.  BR is referred to 2020

 

 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  3 May 2023  20 July 2023
Micro-enterprises  Not included  Not included
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

We have one stand-alone web survey based on self-compilation of web questionnaire (html questionnaire).

Enterprises have possibility to fill online the questionnaire using a web site dedicated to data collection named 'Portale delle imprese' (Business Portal) (link: https://imprese.istat.it )

In this Portale, enterprises have one ID and password to view all open/closed surveys in which they are involved and they can delegate specific respondents to answer to one or more surveys, modify own personal details and activity status.

A facsimile of the questionnaire can be downloaded as a pdf from the web site but this form is not accepted for answering.

 

18.3.5. Survey participation
Mandatory
18.4. Data validation

We use Eurostat Server based EDIT validation.

18.5. Data compilation

Grossing-up procedures

All estimates are obtained on the basis of a final weight for each respondent calculated with calibration weights procedure (calibration estimators)

which guarantees that for given domains of population, the estimates of the total number of enterprises and the total number of persons employed are exactly equal to the known totals

of these two auxiliary variables, coming from the Italian Business Register (ASIA-ENT) - year of reference 2020.
 
This method reduces the bias caused by the total non response.
The final weight wk is obtained as a product of three factors:
wk = dk g1,k g2,k
where:
- dk is the direct weight (the reciprocal of the inclusion probability);
- g1,k is the total non-response correcting factor and is equal to nh/mh where nh is the number of sampled units and mh is the number of respondents belonging to the homogeneity group h (defined by
cross classifying Nace grouping and size classes of persons employed as recorded in the updated frame);
- g2,k is the post-stratification factor.
The software for estimation is a R application developed in ISTAT (ReGenesees - R evolved Generalised software for sampling estimates and errors in surveys; R-based software system for design-based and modelassisted
analysis of complex sample surveys). For documentation on software see following link: https://www.istat.it/en/methods-and-tools/methods-and-it-tools/process/processing-tools/regenesees 
 
18.5.1. Imputation - rate

Not available.

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)  
National reports on methodology (if available)  
Analysis of key results, backed up by tables and graphs in English (if available)  
Other Annexes  


Annexes:
Questionnaire in Italian


Related metadata Top


Annexes Top
Completeness for 2023 Italian data
Sample and standard error tables 2023 updated
Accuracy for 2023 Italian data