1.1. Contact organisation
ISTAT - Italian National Institute of Statistics
1.2. Contact organisation unit
Departement for Statistical Production
Directorate for Economic Statistics
SEC-Structural statistics on businesses, governmental and non-profit organizations
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Via Tuscolana, 1788, 00173 Roma
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
31 October 2023
2.2. Metadata last posted
31 October 2023
2.3. Metadata last update
31 October 2023
3.1. Data description
Statistics on Private non-profit R&D (PNPRD) measure research and experimental development (R&D) performed in the private non-profit sector, i.e. R&D expenditure and R&D personnel. In line with this objective the target population for the national R&D survey of the private non-profit sector should consist of all R&D performing units (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.
The main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. Statistics on science, technology and innovation were collected until the end of 2020 based on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
3.2. Classification system
- The distribution of principal economic activity and by product field is based on Statistical classification of economic activities in the European Community (NACE Rev. 2);
- The local units for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
- The distribution by socioeconomic objectives (SEO) is based on Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS);
- The fields of research and development based on Classification and distribution by Fields of Research and Development (FORD).
3.2.1. Additional classifications
| Additional classification used | Description |
| No additional classification are used | - |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | No deviation from FM. |
| Fields of Research and Development (FORD) | From 2008, data are available separately for NSE and SSH. |
| Socioeconomic objective (SEO) | This classification is not utilized. |
3.3.2. Sector institutional coverage
| Private non-profit sector | Non-profit institutes peforming R&D activity , with the exclusion of those units included in the Higher education sector (HES) . |
| Inclusion of units that primarily do not belong to GOV | - |
3.3.3. R&D variable coverage
| R&D administration and other support activities | No deviation from FM. |
| External R&D personnel | Italian R&D data include both internal and external personnel. |
| Clinical trials | No deviation from FM. |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | No deviation from FM. |
| Payments to rest of the world by sector - availability | No deviation from FM. |
3.3.5. Extramural R&D expenditures
According to the Frascati Manual, expenditure on extramural R&D (i.e. R&D performed outside the statistical unit) is not included in intramural R&D performance totals (FM, §4.12).
| Data collection on extramural R&D expenditure (Yes/No) | Yes |
| Method for separating extramural R&D expenditure from intramural R&D expenditure | Extramural expenditure is separately collected from intramural expenditure. |
| Difficulties to distinguish intramural from extramural R&D expenditure |
3.4. Statistical concepts and definitions
See below.
3.4.1. R&D expenditure
| Coverage of years | |
| Source of funds | |
| Type of R&D | |
| Type of costs | |
| Defence R&D - method for obtaining data on R&D expenditure |
3.4.2. R&D personnel
See below.
3.4.2.1. R&D personnel – Head Counts (HC)
| Coverage of years | |
| Function | |
| Qualification | |
| Age | |
| Citizenship |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | |
| Function | |
| Qualification | |
| Age | |
| Citizenship |
3.4.2.3. FTE calculation
The ratio of working hours actually spent on R&D during a specific reference period (the calendar year) divided by the total number of hours conventionally worked in the same period by the total personnel.
3.4.2.4. R&D personnel - Cross-classification by function and qualification
| Cross-classification | Unit | Frequency |
| Annual data on R&D personnel and researchers cross-classified by occupation and qualification are available. | HC and FTE. | Annual. |
| |
||
3.5. Statistical unit
The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.
3.6. Statistical population
See below.
3.6.1. National target population
The target population is the population for which inferences are made. The frame (or frames, as sometimes several frames are used) is a device that permits access to population units. The frame population is the set of population units which can be accessed through the frame and the survey data really refer to this population of institutional units.
The objective of the European R&D statistics is to cover all intramural R&D activities. In line with this objective, the target population for the national R&D survey of the PNP Sector should consist of all R&D performing units (including known R&D performers or assumed to perform R&D). In practise however, countries in their R&D surveys might have difficulty in identifying R&D activities at the municipality level.
| Target population when sample/census survey is used for collection of raw data | Target population when administrative data or pre-compiled statistics are used | |
| Definition of the national target population | All PNP Institutions known or assumed to perform R&D in the reference year (with the exclusion of those units included in the Higher education sector HES). |
|
| Estimation of the target population size | 429 statistical units. |
3.7. Reference area
Not requested. R&D statistics cover national and regional data.
3.8. Coverage - Time
Not requested. See point 3.4.
3.9. Base period
Not requested. The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.
The unit of measure used for the data values of the expenditures is Thousands of Euros. Head count and full-time equivalent are the units of measure for R&D personnel.
The data values refer to the calendar year.
6.1. Institutional Mandate - legal acts and other agreements
See below.
6.1.1. European legislation
| Legal acts / agreements | Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology was in force until the end of 2020. |
| Nature of the “obligations” of responsible national organisations to produce statistics and report to international organisations | Mandatory. |
6.1.2. National legislation
| Existence of R&D specific statistical legislation | Programma statistico nazionale (art. 13 d.lgs. n. 322 del 1989 and following acts) |
| Legal acts | DL 322/89 and following acts; National Statistics Plan 2011-2013; DCPM 21/03/2013; DPR 19/07/2013; D.lgs 30/06/2003 n.196. |
| Obligation of responsible organisations to produce statistics (as derived from the legal acts) | DL 322/89. |
| Right of responsible organisations to collect data – obligation of (natural / legal) persons to provide raw and administrative data (as derived from the legal acts) | DPR 19/07/2013; DL 322/89. |
| Obligation of responsible organisations to protect confidential information from disclosure (as derived from the legal acts) | DL 196/30/06/2003. |
| Rights of access of third organisations / persons to data and statistics (as derived from the legal acts) | National Statistics Plan. |
| Planned changes of legislation | No changes are planned. |
6.1.3. Standards and manuals
- Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development
- European Business Statistics Methodological Manual on R&D
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
Confidentiality, being one of the process quality components, concerns the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and the extent of its use for statistical purposes.
A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.
a) Confidentiality protection required by law:
National legislation: Data Protection Code - Legislative Decree no. 196/2003 and subsequent amendments and additions;
b) Confidentiality commitments of survey staff:
Code of conduct and professional practice applying to the processing of personal data for statistical and scientific research purposes within the framework of the national statistical system and subsequent amendments and additions.
7.2. Confidentiality - data treatment
Primary and secondary confidentiality is respected for any data released.
8.1. Release calendar
The release calendar for the R&S data set exists and it is publicly accessible.
8.2. Release calendar access
8.3. Release policy - user access
Through Istat databases and information systems users can choose the information according to their needs. In some cases it is possible to build customised tables, in other cases, data are structured in prepackaged downloadable tables. Each database is accompanied by methodologies, classifications, definitions related to the topic.
Through Paper, electronic and interactive publications and specialist publications (Rivista di statistica ufficiale, Istat Working Papers) Istat promotes and enhances the research activity, sharing the results of studies in the field of official statistics.
For journalists there is a press room. The Istat Media Relations Office is responsible for all dealings with the media – from national newspapers, magazines, broadcasters and online publications – and provides ongoing information, monitoring and support for publications, articles and television programmes. The press releases are issued by Istat press office from 10 a.m. on the date indicated, after a briefing to illustrate the main data, reserved for certified news agencies. During the briefing, journalists prepare the launch texts with no outside contact until a member of the press office staff approves the data release (lock-up system). Press office staff monitor agencies constantly throughout the briefing to ensure the embargo is respected. Accredited news agencies agree to respect this dissemination procedure. Failure to comply with the lock-up system may lead to temporary – or complete, in the case of repeated infractions – suspension of access to the press room.
Yearly.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
| Regular releases | Y | On-line press release: LA RICERCA E SVILUPPO IN ITALIA - ANNI 2021/2023 |
| Ad-hoc releases | Y | On-line press release: LA RICERCA E SVILUPPO IN ITALIA - ANNI 2021/2023 |
1) Y - Yes, N – No
10.2. Dissemination format - Publications
See below.
10.2.1. Availability of means of dissemination
| Means of dissemination | Availability (Y/N)1 | Content, format, links, ... |
| General publication/article (paper, online) |
Y | The Annual R&D Report describes the principal results of the R&D survey; it includes graphs, tables, and regional estimates. A chapter of the Italian Statistical Yearbook (the "Annuario Statistico Italiano") is also dedicated to R&D; R&D data are also available in other Istat general publications (Noi Italia, Bes, Rapporto SDGs. Other small reports for specific topics are eventually published. |
| Specific paper publication (e.g. sectoral provided to enterprises) (paper, online) |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Tables providing R&D data are available ( http://seriestoriche.istat.it ).
Italian PNP R&D statistics are available at I.stat (http://dati.istat.it/ ), a warehouse of statistics currently produced by Istat.
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Data are available and accessible by following the standard procedures implemented by ISTAT. |
| Access cost policy | Data are available and accessible by following the standard procedures implemented by ISTAT. |
| Micro-data anonymisation rules | Data are available and accessible by following the standard procedures implemented by ISTAT. |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
| Internet: main results available on the national statistical authority’s website | y | Aggregate figures | |
| Data prepared for individual ad hoc requests | y | Micro-data/ Aggregate figures | |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Methodological note in specific Report
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
See below.
10.7.1. Documentation and users’ requests
| Type(s) of data accompanying information available (metadata, graphs, quality reports, etc.) | Tables, graphs and a short glossary are available. |
| Request on further clarification, most problematic issues | No |
| Measure to increase clarity | No |
| Impression of users on the clarity of the accompanying information to the data | We do not receive particular requests on PNP statistics; the available documentation is supposed to be clear. |
11.1. Quality assurance
Quality tools have been developed by Istat in order to improve the quality of statistical processes and products, consistently with Istat’s mission and according to the quality framework of the European Statistical System.
The Quality Guidelines are among these tools which Istat set up initially only for statistics from surveys, and subsequently also for processes using administrative sources.
For transparency purposes, the quality documentation of Istat statistical processes is available through:
- the Information system on quality (SIQual) containing all metadata describing each production process and its features
- Quality at a glance, standard summary reports for each Istat survey
- The National Quality Reports (Schede Standard di Qualità, only available in Italian), more extensive and detailed reports for expert users, including quantitative indicators on process quality, harmonised with European standards.
ISTAT has also established guidelines and procedures for assessing the quality of statistics produced within Sistan.
11.2. Quality management - assessment
Italy is in line with the Frascati Manual recommendations. Response rate increased over the last years. Biggest institutions can undervalue R&D expenditure and R&D personnel (in particular, they may not be able to supply exact figures for contract staff and consultants). In scientific institutions for research, hospitalization and health care, there is still difficulty to distinguish R&D activity from other related activities.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
| Institutions | European level: Eurostat International organizations: OECD National Level: The Italian Ministry of University and Research, Regional authorities |
Statistics, country comparison and policy analysis |
| Media | Newspapers | Reporting and analysis |
| Researchers and students | Public research centres and universities | Economic analysis and research |
1) Users' class codification
1- Institutions:
• European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
• in Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
• International organisations: OECD, UN, IMF, ILO, etc.
2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.
3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of statistics to the general public.
4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)
5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)
6- Other (User class defined for national purposes, different from the previous classes.)
12.2. Relevance - User Satisfaction
To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.
12.2.1. National Surveys and feedback
| Conduction of a user satisfaction survey or any other type of monitoring user satisfaction | NO |
| User satisfaction survey specific for R&D statistics | NO |
| Short description of the feedback received | - |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
not available
12.3.2. Data availability
Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 1.9% .
12.3.2.1. Incorporation of PNP sector in another sector
| Incorporation of PNP in another sector | In Italy, PNP sector data are separately collected in a specific survey. |
| Reasons for not producing separate R&D statistics for the PNP sector | In Italy, PNP sector data are separately collected in a specific survey. |
| Share of PNP expenditure in the total expenditure of the other sector | In Italy, PNP sector data are separately collected in a specific survey. |
| Share of PNP R&D Personnel in the respective figure of the other sector | In Italy, PNP sector data are separately collected in a specific survey. |
12.3.2.2. Non-collection of R&D data for the PNP sector
| Reasons for not compiling R&D statistics for the PNP sector | In Italy, PNP sector data are separately collected in a specific survey. |
| PNP R&D expenditure/ GERD*100) | In Italy, PNP sector data are separately collected in a specific survey. |
| Share of PNP R&D Personnel in the respective figure of the total national economy | In Italy, PNP sector data are separately collected in a specific survey. |
12.3.2.3. Data availability on more detail level
| Additional dimension/variable available at national level1) | Availability2 | Frequency of data collection | Breakdown variables |
Combinations of breakdown variables | Level of detail |
| No additional dimension/variable | |||||
1) This question is optional. It refers to variables and breakdowns NOT asked by the Commission Implementing Regulation (EU) No 2020/1197 (neither as 'optional').
2) Y-start year
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
a) Coverage errors,
b) Measurement errors,
c) Non response errors and
d) Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
13.2. Sampling error
That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated.
13.2.1. Sampling error - indicators
The main indicator used to measure sampling errors is the coefficient of variation (CV).
Definition of coefficient of variation:
CV= (Square root of the estimate of the sampling variance) / (Estimated value)
Coefficient of variation for Total R&D expenditure :
Coefficient of variation for Total R&D personnel (FTE) :
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
a) Extent of non-sampling errors:
b) Measures taken to reduce the extent of non-sampling errors:
c) Methods used in order to correct / adjust for such errors:
13.3.1. Coverage error
Coverage errors are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
13.3.1.1. Over-coverage - rate
Not requested.
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
Not requested.
13.3.3. Non response error
Not requested.
13.3.3.1. Unit non-response - rate
Not requested.
13.3.3.2. Item non-response - rate
Not requested.
13.3.4. Processing error
Not requested.
13.3.5. Model assumption error
Not requested.
14.1. Timeliness
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
14.1.1. Time lag - first result
Time lag between the end of reference period and the release date of the results:
Indicator: (Release date of provisional/ first results) - (Date of reference for the data)
a) End of reference period: 2021
b) Date of first release of national data:september 2023
c) Lag (days):
14.1.2. Time lag - final result
a) End of reference period:
b) Date of first release of national data:
c) Lag (days):
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)
14.2.1.1. Deadline and date of data transmission
| Transmission of provisional data | Transmission of final data | |
| Legally defined deadline of data transmission (T+_ months) | 10 | 18 |
| Actual date of transmission of the data (T+x months) | 10 | 18 |
| Delay (days) | ||
| Reasoning for delay |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. General issues of comparability
As from 1991 extramural expenditure is collected separately in Italian R&D surveys and can thus be excluded from the data. The R&D personnel is total (internal + external) R&D personnel.
15.1.3. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Implementing Regulation (EU) No 2020/1197 or Frascati manual paragraphs and the EBS Methodological Manual on R&D Statistics with recommendations about these concepts / issues.
| Concept / Issues | Reference to recommendations | Deviation from recommendations | Comments on national definition / Treatment – deviations from recommendations |
| R&D personnel | FM2015 Chapter 5 (mainly paragraph 5.2). | No deviation. |
|
| Researcher | FM2015, § 5.35-5.39. | No deviation. | |
| Approach to obtaining Headcount (HC) data | FM2015, § 5.58-5.61 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel | FM2015, §5.25 | No deviation. | |
| Approach to obtaining FTE data | FM2015, § 5.49-5.57 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Intramural R&D expenditure | FM2015,Chapter 4 (mainly paragraph 4.2). | No deviation. | |
| Statistical unit | FM2015, § 10.40-10.42 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Target population | FM2015, § 10.40-10.42 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Sector coverage | FM2015, § 10.2-10.8 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Reference period for the main data | Reg. 2020/1197: Annex 1, Table 18 | No deviation. | |
| Reference period for all data | Reg. 2020/1197: Annex 1, Table 18 | No deviation. |
15.1.4. Deviations from recommendations
The following table lists a number of key methodological issues, which may affect the international comparability of national R&D statistics. The table gives the references in the Frascati manual, where related recommendations are made. Countries are asked to report on the existence of any deviations from existing recommendations and comment upon.
| Methodological issues | Deviation from recommendations | Comments on national treatment / treatment deviations from recommendations |
| Data collection method | No deviation. | |
| Survey questionnaire / data collection form | No deviation. | |
| Cooperation with respondents | No deviation. | |
| Data processing methods | No deviation. | |
| Treatment of non-response | No deviation. | |
| Data compilation of final and preliminary data | No deviation. |
15.2. Comparability - over time
See below.
15.2.1. Length of comparable time series
See below.
15.2.2. Breaks in time series
| Length of comparable time series | Break years1 | Nature of the breaks | |
| R&D personnel (HC) | |||
| Function | |||
| Qualification | |||
| R&D personnel (FTE) | |||
| Function | |||
| Qualification | |||
| R&D expenditure | |||
| Source of funds | |||
| Type of costs | |||
| Type of R&D | |||
| Other |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.2.3. Collection of data in the even years
Data produced in the same way in the odd and even years.
15.3. Coherence - cross domain
See below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Data on R&D expenditure are yearly requested by the SNA for their calculations.
15.4. Coherence - internal
See below.
15.4.1. Comparison between preliminary and final data
This part compares key R&D variables as preliminary and final data.
| Total PNP R&D expenditure (in 1000 of national currency) | Total PNP R&D personnel (in FTEs) | Total number of PNP researchers (in FTEs) | |
| Preliminary data (delivered at T+10) | |||
| Final data (delivered T+18) | |||
| Difference (of final data) |
15.4.2. Consistency between R&D personnel and expenditure
| Average remuneration (cost in national currency) | |
| Consistency between FTEs of internal R&D personnel and R&D labour costs (1) | N/A |
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) | N/A |
(1) Calculate the average remuneration (cost) of individuals belonging to the internal R&D personnel, excluding those who are only formally ‘employees’ (university students, grant holders, etc.).
(2) Calculate the average remuneration (cost) of individuals belonging to the external R&D personnel (FTEs/other current R&D costs for external R&D personnel).
Restricted from publication
16.1. Costs summary
Restricted from publication
16.2. Components of burden and description of how these estimates were reached
Restricted from publication
17.1. Data revision - policy
Not requested.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. For simplicity, we call them surveys irrespective of whether they are sample surveys, censuses, collections of administrative data/pre-compiled statistics. This section presents the names of the surveys by sector of performance as well as methodological information for each survey. Depending on the type of survey and sector of performance, only the sections corresponding to that survey and sector are filled in.
18.1.1. Data source – general information
| Survey name | Statistical Survey on the Research and Development in Private non profit institutions- Final data 2021- Preliminary data 2022 and 2023 |
| Type of survey | The survey is census-based, considering that the target population is composed of all Private non profit istitutions that potentially perform R&D, according to the information we received from other statistical or administrative sources. |
| Combination of sample survey and census data | NO |
| Combination of dedicated R&D and other survey(s) | NO |
| Sub-population A (covered by sampling) | - |
| Sub-population B (covered by census) | - |
| Variables the survey contributes to | |
| Survey timetable-most recent implementation | Data collection of 2021 R&D data: March-May 2023 |
18.1.2. Sample/census survey information
| Stage 1 | Stage 2 | Stage 3 | |
| Sampling unit | Private non profit institution | ||
| Stratification variables (if any - for sample surveys only) | - | ||
| Stratification variable classes | - | ||
| Population size | 301,044 | ||
| Planned sample size | - | ||
| Sample selection mechanism (for sample surveys only) | - | ||
| Survey frame | The most updated release of the official Italian Statistical Register. |
||
| Sample design | |||
| Sample size | |||
| Survey frame quality |
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | - |
| Description of collected data / statistics | - |
| Reference period, in relation to the variables the survey contributes to | - |
18.2. Frequency of data collection
Odd and even years, without differences.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Information provider | The Italian PNP R&D survey is a web survey (with the same characteristics as the surveys conducted for the GOV and BES sectors). Data collection uses the Istat Web Portal. A single software tool is used for electronic questionnaires, a generalized in-house product that allows the creation of the main survey’s contents: survey metadata, survey variables, questionnaire structure, management of filter rules and checking rules plan. |
| Description of collected information | No deviation from Frascati Manual |
| Data collection method | The Italian PNP R&D survey is a web survey (with the same characteristics as the surveys conducted for the GOV and BES sectors). Data collection uses the Istat Web Portal. A single software tool is used for electronic questionnaires, a generalized in-house product that allows the creation of the main survey’s contents: survey metadata, survey variables, questionnaire structure, management of filter rules and checking rules plan. |
| Time-use surveys for the calculation of R&D coefficients | - |
| Realised sample size (per stratum) | - |
| Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.) | |
| Incentives used for increasing response | |
| Follow-up of non-respondents | E-mail reminders and phone reminders are usually undertaken to receive the questionnaires properly filled. |
| Replacement of non-respondents (e.g. if proxy interviewing is employed) | |
| Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility) | 89.1 % |
| Non-response analysis (if applicable -- also see section 18.5. Data compilation - Weighting and Estimation methods) |
18.3.2. Questionnaire and other documents
| Annex | Name of the file |
| R&D national questionnaire and explanatory notes in English: | Not available. |
| R&D national questionnaire and explanatory notes in the national language: | Questionario di rilevazione sulla R&S nelle istituzioni private non profit |
| Other relevant documentation of national methodology in English: | Not available. |
| Other relevant documentation of national methodology in the national language: | "Guida alla compilazione" available in the Istat web Portal (website for the respondents) |
18.4. Data validation
The validation activities consist of:
- checking the quality of population coverage;
- monitoring that the response rate is good;
- detecting and correcting individual errors in data records through a set of edits (checks for identifying routing errors, coding errors, inconsistencies, outliers and missing answers) that are performed for PNP R&D survey;
- contacting the respondent concerning inconsistencies, errors or missing data;
- comparing the 2021 data with the 2020 data at micro, whereas the respondents had already filled in questionnaire in the previous edition;
- comparing the 2021 data with the 2020 data at macro level.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Not applicable
18.5.2. Data compilation methods
| Data compilation method - Final data (between the survey years) | The survey is carry out every year. |
| Data compilation method - Preliminary data |
18.5.3. Measurement issues
| Method of derivation of regional data | The regional data are produced on the basis of the place where R&D is really undertaken. |
| Coefficients used for estimation of the R&D share of more general expenditure items | N/A |
| Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures | N/A |
| Differences between national and Frascati Manual classifications not mentioned above and impact on national statistics | N/A |
18.5.4. Weighting and estimation methods
| Description of weighting method | N/A |
| Description of the estimation method | N/A |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
Statistics on Private non-profit R&D (PNPRD) measure research and experimental development (R&D) performed in the private non-profit sector, i.e. R&D expenditure and R&D personnel. In line with this objective the target population for the national R&D survey of the private non-profit sector should consist of all R&D performing units (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.
The main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. Statistics on science, technology and innovation were collected until the end of 2020 based on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
31 October 2023
See below.
The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.
See below.
Not requested. R&D statistics cover national and regional data.
The data values refer to the calendar year.
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
a) Coverage errors,
b) Measurement errors,
c) Non response errors and
d) Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
The unit of measure used for the data values of the expenditures is Thousands of Euros. Head count and full-time equivalent are the units of measure for R&D personnel.
See below.
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. For simplicity, we call them surveys irrespective of whether they are sample surveys, censuses, collections of administrative data/pre-compiled statistics. This section presents the names of the surveys by sector of performance as well as methodological information for each survey. Depending on the type of survey and sector of performance, only the sections corresponding to that survey and sector are filled in.
Yearly.
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
See below.
See below.
