Directorate General of Education and Science Statistics (DGEEC) | Direção Geral de Estatísticas da Educação e Ciência

Head of unit: Science and Technology Statistics and Information Society Services
(DSECTSI - Direção de Serviços de Estatísticas da Ciência e Tecnologia e da Sociedade de Informação)

Av. 24 de Julho, 134
1399-054 Lisboa, PORTUGAL

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.  

• 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).

See below.

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).

See below.

See below.

For R&D personnel with tertiary level of education (=> ISCED 5), the FTE calculation is based on the information provided in the individual form, regarding the percentage of time dedicated to R&D activities.
Although a person may perform R&D in more than one unit, due to the fact that there is an individual form, it is possible to identify if the same person is performing R&D in other units. If they exceeded 100%, the percentage is adjusted accordingly to the number of times that the person is identify and according to the percentage of time in R&D activities that was reported in each unit, assuring that no one is counted for more than 1.0 FTE.
For R&D personnel without tertiary education (< ISCED 5), the FTE is reported by the respondent unit as aggregated data (by gender and function) and considered as such, after the validation process (where the data is compared with previous years and/or questioned if needed).

The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.

See below.

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. 

Not requested. R&D statistics cover national and regional data.

Not requested. See point 3.4.

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.

R&D indicators are available in the following units:
Expenditure: Euros (thousand) and %
Personnel: HC and FTE.

Calendar year

See below.

- Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development

- European Business Statistics Methodological Manual on R&D

Not requested.

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: DGEEC proceeds according to the National Statistical System (Law Nr. 22/2008 of May 13th) that regulates statistical confidentiality (Article 6).

b)       Confidentiality commitments of survey staff: The staff working directly with statistical production have to sign commitment document, which ensures the acknowledge of the confidentiality issues and data protection law.

R&D data is checked in order to assure confidentiality. Monitoring and control of the data is made before it is published, assuring no confidential information is released. If applicable, checking any cell with less than 3 population units, and properly modifying the table to avoid also secondary disclosure is applied.

The calendars of statistical operations and statistical publications are publicly available (in January) on the DGEEC's website.

https://estatistica.dgeec.mec.pt/cdeo.php 

R&D data, by sectors of performance, is available to all users on the DGEEC’s website.
When data/publications are released in DGEEC website, the units surveyed in the reference year, regardless the type of response (performing R&D or not), are also informed by email.
The Chief of Staff of the Minister of Science, Technology and Higher Education, 24 hours before the scheduled of release, can receive information under embargo, as it is publicly described in the European Statistics Code of Practice and in accordance with point 15, chapter B, of Statistics Portugal (INE).

Yearly.
https://www.dgeec.mec.pt/np4/206/

See below.

1) Y - Yes, N – No

See below.

1) Y – Yes, N - No 

A list of the R&D units is provided in DGEEC’s website, which contains the name, general contacts, and the FORD of each unit that in the reference year performed R&D.
Link: https://www.dgeec.mec.pt/np4/44/

Not requested.

See below.

See below.

Not requested.

1) Y – Yes, N - No 

List of national descriptive text and/or references to methodological documents available to the R&D statistical process:
- IPCTN form – Institutional Sector (includes GOV, HE and PNP sectors); available: https://www.dgeec.mec.pt/np4/np4/np4/216/
- IPCTN Methodological Document (DGEEC, INE); available: https://estatistica.dgeec.mec.pt/dm.php and at INE’s website: https://smi.ine.pt/DocumentacaoMetodologica/Detalhes/1695
- Validation Handbook (internal working document / DGEEC),
- Handbook for questionnaire non- response cases (internal working document / DGEEC).

IPCTN form, for 2021 reference year, had 5 annexes which provide useful information for a correct filling of the questionnaire:
Annexe I – Concepts and examples of R&D activities (and also on intramural and extramural expenses),
Annexe II – Human resources performing R&D activities,
Annexe III – SEO according to Eurostat (NABS, 2007),
Annexe IV – National priorities according to R&D National Strategy for an Intelligent Specialisation (EI&I; 2014 - 2020),
Annexe V – Fields of R&D Classification (FORD, 2015),
Annexe VI – List of careers and categories of the personnel.

The IPCTN Survey’s Methodological Document provides all information related to this national statistical operation. In general, it describes the needs, the goals and the funding of this statistical operation; it also provides a general characterisation of the statistical operation (type, source of information used, periodicity, geographic scope, breaks in time series, information available to users and its dissemination means) and contains methodological information on target population, data collecting, data treatment, data dissemination, and more. It’s the official methodological document approved by INE for registering this statistical operation in the NSS.

Data validation rules are defined in the Validation Handbook.
Rules for questionnaire non- response cases were defined in the Handbook (included uncompleted questionnaires), as well as for units that had submitted their questionnaire as non-R&D performer although being funded by the Foundation for Science and Technology (FCT) (see point 18.1.3.).

All these documents are updated on a yearly basis, for each statistical operation.

Not requested.

See below.

DGEEC as the institution responsible for the production of official statistics, must respect and be governed by national and international statistical quality standards, in accordance with article 7 of Law Nr. 22/2008 of May 13, and by the European Statistics Code of Practice. In the case of the R&D statistics, DGEEC also follows Eurostat's and OECD methodological recommendations.
Several data validation processes take place before the R&D indicators are released. This validation procedures have been updated over the years that, complemented with the use of new database management tools, have resulted in more efficient and effective data management. The major improvements were obtained through the use of technology and information systems, through a wider range of administrative databases, through more efficient communication between organizations, but also due to the expertise staff involved in these statistical operations, who greatly contributed to the quality of the survey responses.
The activities carried out by the technicians are highly complex and require in-depth knowledge of the concepts and methodologies inherent to this survey, in the field of statistics, as well as high computer skills, especially in programs that allow data management and calculation - for example, SQL, SAS and SPSS.
In addition, communication skills and contact with respondents are also privileged, both in the validation phase and in the phase of obtaining responses, which is why it is necessary to guarantee continuous training for all those who contribute to this census. Training has been given to technicians in these areas, as well as complementing training in areas related to database management and making information available (data scientist, PowerBI, etc.).
Internal manuals are updated annually, including a validation handbook, and a detail description of the entire final validation process, which takes place in SQL.
A thorough validation procedure of data collected is carried out, consisting in finding and correcting internal inconsistencies among the sections and questions in survey and by comparing with data from previous years or with other data sources. All efforts are made to reduce errors, identify and correct them. Assistance/helpdesk is provided to respondents during data collection.
During the validation process, entities are contacted for further clarifications or for correcting errors.
For all questionnaires, the following procedures are carried out: The electronic form includes validations that allow checking the consistency of the information (it may be necessary to contact the company, if incoherence is found). Inconsistencies of the "Error" type must be resolved before registration is accepted. Once the data registration is concluded, the information is analysed and processed, namely the analysis of the consistency of the year's data, comparison of values with the previous year for quality control. Some data are confronted with information from other administrative sources considered relevant.
DGEEC had also implemented a Quality Management System for improving the quality of its services by monitoring and measuring its services, processes and procedures. As part of this system, procedures are included in matters such as document management, resource management, human resources skills improvement on statistical production. The Quality Manual, as well as the commitment to quality could be also noticed in DGEEC’s annual programmes that are publicly available on its website. https://www.dgeec.mec.pt/np4/36/

The Portuguese R&D survey (IPCTN) is part of the National Statistical System, and DGEEC, as responsible for these official statistics, is legally obliged to respect the national and international statistical quality standards (Law for the National Statistical System, European Statistics Code of Practice).
The IPCTN survey has been implemented for almost 4 decades, with continuous adaptation, improvement, and ongoing monitoring to assure that the survey is according to FM.
The quality is considered very good, mainly because of the intensive follow-up activities with the respondents, the administrative databases that complement the survey, which contributes for the data validation, as well as the high response rates over the years.

See below.

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.)

To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.

See below.

For PNP, completeness rate is 100% for mandatory data, and 83% for total data required.

Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D):

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

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.

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.

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) : 

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:

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.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

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.

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: 31-12-2021

b) Date of first release of national data: 05-08-2022

c) Lag (days): 217

a) End of reference period: 31-12-2021

b) Date of first release of national data: 22-12-2022

c) Lag (days): 356

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.

Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)

See below.

Not requested.

The R&D statistics are according to FM (2015) and harmonized with OECD norms, therefore international comparability is ensured.

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.

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.

See below.

See below.

1)       Breaks years are years for which data are not fully comparable to the previous period.

The survey is annual since 2008; data have been produced in the same way in odd and even years. 

See below.

Not requested.

SNA classifications are used to classify R&D units in their institutional sector.

See below.

This part compares key R&D variables as preliminary and final data.

(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).

The assessment of costs associated with a statistical product is a rather complicated task since there must exist a mechanism for appointing portions of shared costs (for instance shared IT resources and dissemination channels) and overheads (office space, utility bills etc). The assessment must become detailed and clear enough so that international comparisons among agencies of different structures are feasible. 

1)       The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.

1)        T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)

Not requested.

Not requested.

Not requested.

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.

Annual (since 2008).

See below.

A thorough validation procedure of data collected is carried out (see also point 11.1), that is implemented along with the data collection, and increased when then response rate is high (in the first months the main efforts are conducted to obtain the maximum number of responses, for the provisional results).
In general, the validation process can be described in three main levels:
- 1st: Validation of the online platform, when the units are filling the questionnaire. The survey’s electronic template form cross-checks the information consistency: "Error" type inconsistencies are checked out otherwise the platform don’t allow the questionnaire submission.

- 2nd: Considering the guidelines of the Validation Handbook, for the data collection, a validation procedure of the information gathered is carried out, regarding:
Coherence - analysis of data inconsistencies among the sections and the questions of the units’ questionnaire
Comparison - analysis of the data, compared with responses from with previous years (if available).
Cross-check - analysis of the data, compared with other sources: administrative databases (DGEEC’s or other entities)

- 3rd: parallel with the previous phases, DGEEC calculates estimations on Current expenditures on R&D activities in the reference year. This information is provided to the Units during the validation process, in order to compare it to what was reported in the survey.
Calculation on personnel costs, is made by considering the FTE and the career of R&D personnel that was reported by the units. Considering the information provided in the individual form (=> ISCED 5), as well in the section of the form for the personnel without tertiary education (< ISCED 5), and having the National Pay Scale System for Public Administration as the starting point, it is estimated an average salary for each person reported by the unit. The aggregate amount of these salaries is compared with the personnel expenditure reported by the Unit, compared also with the response of the previous year (when available), and analysed by the IPCTN survey staff.
Calculation on average salaries, considering only the report expenditure by the units are made, in order to validate the amount that was reported. if the average salary is too low or too high, units are contacted to provide clarifications.

During the all validation process, if inconsistencies, or major variations, are detected, units are contacted for further clarification and, if needed, for correcting errors.

See below.

Not applicable

Not requested.

Not requested.

Brief historical notes on the (IPCTN) R&D survey (all sectors included):
- The IPCTN survey started to be administrated in 1982 (every two years; even years), however in 1994 was a gap year (missing data). For the years that the IPCTN survey was not administrated, data were based in simple averages between the surveyed years.
- For 1993 and 1994, the GERD were estimated by applying the annual average growth rate of the period 1992-1995. By sector of performance, the value was distributed in terms of their weight (%) in the GERD, as it was observed in 1992.
- For the 1999 IPCTN survey, special attention was given to the public hospital and clinics: a special survey was launched based on R&D undertaken projects (project approach).
- From 2001 onwards: DGEEC has started to undertake electronic Survey administration and also postal survey (when required by the units). In 1997 and 1999: Floppy disk and postal survey. Until 1995: postal survey.
- From 2008 onwards, the IPCTN Survey started to be administrated yearly.
- In the 2009 IPCTN Survey, it was made a new revision of the hospitals’ core model questionnaire, and, from 2011 onwards, hospitals and health facilities were surveyed along with other units (in the institutional sector).
- From 2008 to 2010, phases 1, 2 and 3 of clinical trials were surveyed in R&D core model questionnaire for public and university hospitals.
- From years 2009 to 2011, DGEEC had reviewed data according to the following: i) removed all master students doing thesis from R&D personnel data that had been added to specific institutions (universities, colleges and polytechnic institutes) in the years 2009, 2010 and 2011 (that were estimated by DGEEC); ii) added postgraduate students at the PhD level with an individual R&D grant, financed by FCT, that weren’t included in the R&D personnel data of IPCTN surveys from 2009 to 2011.
- In 2010, it was introduced a new section in the IPCTN Survey for the BE sector: Section VI – Biotechnology R&D activities.
- In 2012, it was introduced the Section VI – Biotechnology R&D activities in the IPCTN Survey for the PNP, GOV and HE sectors. These data collection was interrupted from 2015 to 2017, and it was put back on in the 2018 survey.