Statistics Sweden

Economic Statistics and Analysis

Innovation, Business sector production and Research

Statistics Sweden
Att. Nils Adriansson
ESA/NUP/INF
Solna strandväg 86, Solna
SWEDEN

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).

Not applicable, not breakdown by classifications available for the Private non-profit sector.

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.

R&D full-time equivalents are estimated by extrapolation based on data collected by questionnaire concerning 2017. The method of extrapolation is a moving average based on data for government agencies. Analysis of historical data has shown that the development of R&D personnel in the Private non-profit sector closely ressembles that of government agencies, why data on the development among government agancies is assumed to be an adequate proxy for the development in the Private non-profit sector. 

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.

National currency in thousands and full-time equivalents.

2021

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:

The major policy in place to ensure confidentiality and prevent unauthorised disclosure of data that identify a person or economic entity is the Public Access to Information and Secrecy Act (2009:400). There are also specific conditions concerning the confidentiality of official statistics in the Official Statistics Act (2001:99). 

b)       Confidentiality commitments of survey staff:

Statistics Sweden has a confidentiality policy to which all survey staff must adhere. It contains guidance on the practical application of the legal acts stated above. 

For aggregate outputs, primary cell suppression is used as a general rule to ensure no confidential information is disclosed. To ensure that the information cannot be calculated using data in other cells, secondary cell suppression is used. 

Any disclosure of microdata must be tried. It can be disclosed only for research or statistical purposes and only to such entities that are deemed able to ensure confidentiality protection of the data. 

The release policy and the release calendar are publicly available at Statistics Sweden's website.

The publication calendar is available on Statistics Sweden's website.

Statistics Sweden's release policy states that all statistics must be made available to all users equally and at the same time. Statistics are always released at 8.00 am on weekdays. Users are also informed of the availability of new statistics by news releases on Statistics Sweden's website. It is possible for users to subscribe to get e-mail notifications when new statistics within a certain subject area are released. Statistics are released by being made available in the statistical database. The release policy is available on Statistics Sweden's website.

Annually.

See below.

1) Y - Yes, N – No

See below.

1) Y – Yes, N - No 

An online statistical database is available on Statistics Sweden's website (see link in Annex). During 2022, the R&D tables in the database were accessed 3 431 times. 

Not requested.

See below.

See below.

Not requested.

1) Y – Yes, N - No 

The main documentation on methodology is titled Statistikens framställning (translates to Statistical production) which is updated when new statistics are published. There is a common document covering all sectors for the R&D statistics in which the specific methodology for each sector is described. This documentation is only available in Swedish.

Not requested.

See below.

Statistics Sweden is certified according to ISO 20252:2012 for market, opinion and social research surveys. The certification confirms that we fulfil the fundamental quality requirements in the production of statistics.

The quality of the statistics is assessed regularly, and the R&D statistics meet the quality requirements. Measurement error is considered the most important source of error in the statistics as a result of the relatively complex concepts involved in R&D statistics and that respondents are required to report on. Yet, the quality is considered appropriate in relation to such legal requirements and user needs as have been identified. For the time-use survey, object non-response is also a mounting challange. Statistics Sweden has faced declining response rates for several years which has a negative effect on the quality of the statistics. For the survey on R&D expenditure however, there are no non-response issues. As it is a census there are neither any issues concerning sampling or coverage. Results are presented in more detail in sections 12 to 15 below.

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.)

The views and opinions from users are primarily collected through the User council for statistics on research and development which meets twice yearly. The user council consists of representatives from the Ministry of Enterprise, the Ministry of Education, the Swedish Higher Education Authority, the Swedish Research Council, Vinnova (Sweden's innovation agency), RISE, the Swedish Association of Local Authorities and Regions, the Swedish Agency for Growth Policy Analysis, the Research Institute of Industrial Economics, Lund University and Teknikföretagen (the trade association for the Swedish industry sector). Minutes from the last meeting of the user council are available in Swedish at Statistics Sweden's website.

See below.

2 percent (6 percent for mandatory variables and 0 percent for voluntary variables).

Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 0,1 percent.

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:  Not applicable, no sample survey is used for the Private non-profit sector.

Coefficient of variation for Total R&D personnel (FTE): Not applicable, no sample survey is used for the Private non-profit sector.

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: 

Because figures for the Private non-profit sector are calculated using extrapolation, the main source of potential non-sampling errors is model assumptions. 

b)       Measures taken to reduce the extent of non-sampling errors: 

An analysis of historical data has been conducted to validate the reasonableness of the model assumption that the development of R&D in government agencies can be used as a proxy for the development in the Private non-profit sector.

c)       Methods used in order to correct / adjust for such errors:

There are no methods in place to correct or ajust for non-sampling 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: 2021-12-31

b) Date of first release of national data: 2022-07-14

c) Lag (days): 195

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

b) Date of first release of national data: 2022-10-27

c) Lag (days): 300

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.

International comparability is generelly deemed to be poor. The main issue for comparability is missing values. Due to difficulties with accuracy only a small number of variables are available for the private non-profit sector. 

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.

Statistics are produced in the same way for all reference years.

See below.

Not requested.

Not available, no analysis of coherence with the National Accounts has been conducted. 

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.

Pre-compiled statistics from R&D in the Govenment sector are collected annually.

See below.

Not applicable, no raw or administrative data collected. For information on data validation for R&D in the Governement sector, see the documentation for that sector.

See below.

Not applicable, imputation is not used for the Private non-profit sector.

Not requested.

Not requested.