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

Directorate for Science and Technology Statistics and Information Society Services
(DSECTSI - Direção de Serviços de Estatística da Ciência e Tecnologia e da Sociedade de Informação)

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

Statistics on Business enterprise R&D (BERD) measure research and experimental development (R&D) performed in the business enterprise 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 business enterprise sector consist of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. The “enterprise” is defined in Council Regulation (EEC) No 1993/696 of 15 March 1993. The results are related to the population of all R&D performing enterprises classified in Sections A to U of the common statistical classification of economic activities as established by Regulation (EC) No 1893/2006 of the European Parliament and of the Council (NACE Rev.2).

The main concepts and definitions used for the production of R&D statistics are given by 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 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 are based on Statistical classification of economic activities in the European Community (NACE Rev. 2);
• The local unit for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
• The distribution by socioeconomic objectives (SEO) are based on Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS);
• The fields of research and development are 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 enterprise) is not included in intramural R&D performance totals (FM, §4.12).

See below.

See below.

FTE is reported by the company as aggregated data (percentage dedicated to R&D in the reference year by gender, qualification, function and internal/external personnel). After, in the validation process, the data is compared with the information of the individual forms (in BES the individual form it’s not mandatory and it’s only for tertiary graduated personnel in R&D,as mentioned before), with data from previous years and the company is questioned if needed.

The statistical unit for BERD is the enterprise as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993, – if there are deviations please explain.

See below.

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 Business Enterprise Sector should consist of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. In practice however, countries in their R&D surveys might exclude some enterprises for which R&D activities are deemed to be non-existent or negligible, in order to limit the response burden or due to budgetary constraints.

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.

1)       i.e. enterprises previously not known or not supposed to perform R&D

R&D statistics cover national and regional data. Aggregated for NUTS I, NUTS II and NUTS III.

Not requested. See point 3.4.

Not requested.

BES 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

- EBS Methodological Manual on R&D Statistics

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.

The rule applied for defining cells with direct disclosure risk (primary confidentiality) is 2 firms or less in a cell is considered confidential (Rule of Three). When necessary it is applied the rule of the secondary confidentiality, if then disclosure is possible by subtraction.

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 companies is provided in DGEEC’s website, which contains the name and general contacts of each company that in the reference year performed R&D and authorized this disclosure.
Link: https://www.dgeec.mec.pt/np4/44/

Not requested.

See below.

See below.

Not requested.

1) Y – Yes, N - No 

The BES R&D data dissemination files provides methodological information and the questionnaire. The publication of main R&D statistics and indicators (online) gives information to users about methodological procedures, data collection methods and list of variables; present a definition of conceptual framework; provides a copy of R&D questionnaire and offers a range of tables. When is necessary, some of the tables are available with the respective footnotes. For further explanations users can request telephonic or e-mail assistance.

List of national descriptive text and/or references to methodological documents available to the R&D statistical process:
- IPCTN form – BES 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/1586
- Validation Handbook (internal working document / DGEEC),

R&D form (IPCTN), 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 expenditures),
Annexe II – Human resources performing R&D activities,
Annexe III – Fields of R&D Classification (FORD, 2015),
Annexe IV – SEO according to Eurostat (NABS, 2007),
Annexe V – National priorities according to R&D National Strategy for an Intelligent Specialisation (EI&I; 2014 - 2020),
Annexe VI – List of products.

The 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. These 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, to identify and correct them. Assistance/helpdesk is provided to respondents during data collection.
During the validation process, respondents 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 BES, completeness rate is 100% for mandatory data and 97% for total data required.

Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.

Criteria:

A) Obligatory data. Only 'Very Good' = 100%, Poor' >95%; 'Very Poor' <100% apply.

B) Optional data. 'Very Good' = 100%; 'Good' = >75%; 'Satisfactory' 50 to 75%%; 'Poor' 25 to 50%; 'Very Poor' 0 to 25%.

See below.

1) Y-start year, N – data not available

1) Y-start year, N – data not available

1) Y-start year, N – data not available

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'), if R&D data for BES are collected for additional breakdowns or/and at more detailed level than requested.

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.

1)  Ranking of the type(s) of errors that result in over/under-estimation, from the most important source of error (1) to the least important source of error (5). In the event that errors of a particular type do not exist, is used the sign ‘-‘.

2)  The perceived direction of the ‘overall’ error using the signs “+” for over estimation, “-” for under estimation and “+/-” when assumption of the direction of the error cannot be made for R&D.

1) 'Very Good' = High level of coverage (annual rate of substitution in the target population lower than 5%). High average rates of response (>80%) in census and sample surveys (BES R&D). Full data consistency with reference to totals and relationships between variables in the dataset sent to Eurostat.  

2) 'Good' = In the event that at least one out of the three criteria above described would not be fully met.

3) 'Satisfactory' = In the event that the average rate of response would be lower than 60% even by meeting the two remaining criteria.

4) 'Poor' = In the event that the average rate of response would be lower than 60% and at least one of the two remaining criteria would not be met.

5) 'Very Poor' = If all the three criteria are not met.

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)

Not applicable; Census survey.

1)        Industry sector (NACE Rev. 2: 01-03, 05-09, 10-33, 35, 36-39, 41-43)

2)        Services sector (NACE Rev 2.: 45-47,49-53,55-56,58-63,64-66 68,69-75,77-82,84,85,86-88,90-93,94-96,97-98,99)

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.

Coverage errors (or frame 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.

a)       Description/assessment of coverage errors: Not applicable.

b)       Measures taken to reduce their effect: Not applicable.

Magnitude of error (%) = (Observed Value-True Value)/ True Value (%) 

Not requested.

Misclassification rate measures the percentage of enterprises that changed stratum between the time the frame was last updated and the time the survey was carried out. It is defined as the number of enterprises that changed stratum divided by the number of enterprises which belong to the stratum, according to the frame. The rate can be estimated based on the characteristics of the surveyed enterprises.

Measurement errors occur during data collection and generate bias by recording values different than the true ones (e.g. difficulty to distinguish intramural from extramural R&D Expenditure). The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.

a)       Description/assessment of measurement errors: Not applicable.

b)      Measures taken to reduce their effect: Not applicable.

Non-response occurs when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.

There are two elements of non-response:

- Unit non-response, which occurs when no data (or so little as to be unusable) are collected on a designated population unit.

- Item non-response, which occurs when data only on some, but not all survey variables are collected on a designated population unit.

The extent of response (and accordingly of non response) is also measured with response rates.

The main interest is to judge if the response from the target population was satisfying by computing the weighted and un-weighted response rate.
Definition:
Eligible are the sample units which indeed belong to the target population. Frame imperfections always leave the possibility that some sampled units may not belong to the target population. Moreover, when there is no contact with sample units and no other way to establish their eligibility they are characterised as ‘unknown eligibility units’
Definition:
Un-weighted Unit Non- Response Rate = 1 - (Number of units with a response) / (Total number of eligible and unknown eligibility units in the survey) 
Weighted Unit Non- Response Rate = 1 - (Total weighted responding units) / (Total weighted number of eligible / unknown eligibility units in the sample)

1)        Industry (NACE Rev. 2: 01-03, 05-09,10-33,35,36-39,41-43)

2)        Services (NACE Rev 2.: 45-47,49-53,55-56,58-63,64-66 68,69-75,77-82,84,85,86-88,90-93,94-96,97-98,99)

Four official reminding letters are sent for non-respondents. Furthermore, telephone and email contacts were made in order to follow-up the non-respondent units.

Definition:
Un-weighted Item non-Response Rate (%) = 1-(Number of units with a response for the item) / (Total number of eligible , for the item, units in the sample) * 100

Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.

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’s criteria, 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 and EBS Methodological Manual on R&D Statistics paragraphs 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.

This part deals with any national coherence assessments which may have been undertaken. It reports results for variables which are the same or relevant to R&D statistics, from other national surveys and / or administrative sources and explains and comments on their degree of agreement with R&D statistics.  Intramural R & D expenditure (code 230101 in the Commission Implementing Regulation (EU) 2020/1197) and R & D personnel (code 230201) are surveyed also in foreign-controlled EU enterprises statistics (inward FATS).

The Community innovation survey 2020 (CIS2020) (inn_cis12) (europa.eu) also collects the R&D expenditure of enterprises that form the coverage of the CIS2020 survey. 

Not requested.

Not available.

DGEEC collects R&D data and Statistics Portugal (INE) are responsible for FATS data. DGEEC and INE analyze the link between the two data collections.

See below.

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

171,5

(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.

See 12.3.3.

See below.

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 or at least to identify and correct them. It's provided assistance 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 sources considered relevant.

See below.

Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition:
Imputation rate (for the variable x) % = (Number of imputed records for the variable x) / (Total number of possible records for x)*100

1)       Industry (NACE Rev. 2: 01-03, 05-09,10-33,35,36-39,41-43)

2)       Services (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

Not requested.

Not requested.

Brief historical notes on the IPCTN Survey (all sectors included):
o 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.
o 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.
o 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).
o 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.
o From 2008 onwards, the IPCTN Survey started to be administrated yearly.
o 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).
o 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.
o In 2010, it was introduced a new section in the IPCTN Survey for the BE sector: Section VI – Biotechnology R&D activities.