Research and development: documentation of statistics
Basic data of the statistics
Data description
Statistical population
In the government and private non-profit sectors, the statistical unit is composed of units which have reported R&D activities in the previous survey. The panel is also regularly supplemented with units which can justifiably be expected to engage in research activities. In practice, the public sector’s R&D statistics can be considered to be a complete enumeration.
The higher education sector’s target statistical population is made up of universities, university hospitals, universities of applied sciences and the National Defence University, comparable to universities. The sector of higher education may also include public or private research institutions closely integrated into the research conducted by institutions of higher education. The statistics represent a complete enumeration in terms of their coverage.
Statistical unit
Unit of measure
Reference period
Reference area
Sector coverage
Business enterprises
Public sector (central government, other public institutions and local government)
Private non-profit sector
Higher education (universities, university hospitals, universities of applied sciences and the National Defence University, comparable to universities). The sector of higher education may also include public or private research institutions closely integrated into the research conducted by institutions of higher education.
Time coverage
Frequency of dissemination
Concepts
Extramural research and development
Other R&D personnel
R&D in full-time equivalents (FTE)
Research and development activity
The five criteria for identifying R&D:
To be aimed at new findings (novel)
The aim of the R&D is to produce new knowledge and novelties. Mere application of the existing knowledge in development of new solutions, products or procedures is not R&D activity.
To be based on original, not obvious, concepts and hypotheses (creative)
Characteristic to R&D activity is creativity, setting and testing of new hypothesis and concepts. Routine activities in the development of products, processes or other procedures in not R&D activity.
To be uncertain about the final outcome (uncertain)
R&D involves uncertainty regarding outcomes and costs.
To be planned and budgeted (systematic)
R&D is conducted in a planned way, with records kept of both the process followed and the outcome. The purpose of the R&D project and the sources of funding for the R&D performed should be identified. R&D is often organized as a project, but it can also be goal-oriented activity of a person or a group.
To lead to results that could be possibly reproduced (transferable and/or reproducible)
An R&D project should result in the potential for the transfer of the new knowledge which also can be reproduced.
Distribution by type of R&D
Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view.
Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective.
Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.
Research and development expenditure
Share of R&D work in annual wages according to R&D person-years. Labour costs include actual wages, fringe benefits in actual value, holiday pay and holiday bonuses. They also include social security payments, contributions to unemployment insurance and compulsory and voluntary pension contributions.
Materials, equipment and other current expenditure
Materials and equipment needed for R&D activities including acquisition of machinery and equipment with operating life at most one year. Other current expenditure includes the share of R&D activity in cost items such as buildings and premises, information technology, travel and administrative costs (also labour costs of administrative and maintenance personnel, which are not included in the R&D wages).
Purchased services
Purchases of services integrated into enterprise's own R&D activities. Services that are produced by external personnel, but which are closely linked to the intramural R&D of an enterprise. They may include software services, consultancy and other planning services, which are not considered as intramural R&D activities from the point of view of the service provider.
Capital costs (acquisition of machinery, equipment, buildings and the like)
Acquisitions which serve R&D only are included in total, in other cases the share of R&D is estimated by the share of use for R&D purposes. Item covers also acquisition of software for R&D activities along with licence fees.
Research and development personnel
Research and development personnel by function
Product development engineers, researchers or equivalent are persons whose job is to produce new knowledge or develop new applications in product, process or other development work. This category also includes people responsible for the managing and planning of the contents of R&D projects. Person performing only administrative activities linked to the R&D projects belong to the group other R&D staff. According to the R&D definition every statistical unit performing R&D has at least one person who is product development engineer, researcher or equivalent.
Other R&D staff includes technical experts, other personnel carrying out R&D tasks (e.g. laboratory technicians, computer programmers) and staff providing other kinds of support for R&D projects.
Researcher
University
University of applied sciences
Classifications
Accuracy, reliability and timeliness
Overall accuracy
Timeliness
Punctuality
Comparability
Comparability - geographical
Comparability - over time
Changes in the time series
Business enterprises
Comparisons by industry in the business enterprise sector are complicated by changes in industrial classifications and by business enterprises which change their industry. On a rough industrial level, the time series is nevertheless fairly comparable from 1985 onwards.
From 1971 to 1983, business enterprises divided their responses according to the industrial unit (product group). As of 1985, according to the business enterprise’s main industry.
From 1998 to 2004, the source of financing for R&D expenditure ‘the group’s foreign units’ was incorporated to a business enterprise’s own financing, reducing the share of foreign financing. The reason for this was problems in the availability of data. The category was reclassified as of 2005.
In 2011, business enterprises of more than 100 employees were added from the following industries: 47, 55, 56, 68, 69, 75 to 88 and 96 to 99.
In 2020, a sample of business enterprises of 10 to 99 employees were added from the following industries: 47, 55, 56, 68, 69, 75 to 88 and 96 to 99.
Public sector and private non-profit sector
The data prior to 1983 are not comparable to a subsequent time series in all respects
The biggest municipalities were added to the statistics in 2007.
The ‘own funding’ source of funding for research expenditure was divided as of 2017 to: 1) basic funding (funding from state or municipal budgets) and 2) own funding (e.g. business operations, fund raising, investment and financing operations as well as profit from own funds and foundations).
Institutions of higher education
The data prior to 1983 are not comparable to a subsequent time series in all respects.
The share that research accounts for in the working hours of teachers and researchers was investigated with surveys conducted in 1983, from 1992 to 1993 and from 2004 to 2005. Based on these surveys, new shares of research by occupational title and field of R&D were defined for the calculation.
The number of individuals included in the higher education sector grew with university hospitals in 1997 and with universities of applied sciences in 1999. Due to lack of data, the R&D in full-time equivalents in some universities’ basic funding were estimated in 2010. The change in the higher education sector’s statistical method as of 2011 affects the comparability of the university data. In departure from previous time use surveys, the share of research was determined from administrative time use and working plan data.
The share that research accounts for in the time use of teachers and researchers was updated in terms of 2014. The update of the time-use coefficients in 2014 increased the share of research in terms of working hours, which contributes to an increase of R&D in full-time equivalents and research expenditure from 2013 to 2014.
The National Defence University, which was previously included in the public sector, was added to the higher education sector in 2016.
The update of universities’ time-use coefficients in terms of 2017 increased the share accounted for by research in the working hours of the universities’ research staff. This resulted in an increase of the higher education sector’s R&D in full-time equivalents and expenditure. The update of the time-use coefficients in 2021 did not have much effect on the number of R&D in full-time equivalents or amount of R&D expenditure.
Coherence - cross domain
Coherence - internal
Source data and data collections
Source data
Target population and sample
The data are collected with a digital form in a survey. The target statistical population consists of business enterprises operating in Finland. The frame is the business register maintained by Statistics Finland. The statistical unit is primarily a business enterprise. In some cases, the statistical unit is a group or part of an international group operating in Finland.
The basic element of data collection is a panel monitored on an annual basis. The panel is composed of business enterprises which have reported R&D activities in the previous year’s survey and business enterprises which have received product development funding from Business Finland. Data on other business enterprises making up the statistical frame population are collected with a sample. The sample serves to update the panel, i.e. business enterprises reporting R&D activities transfer to the panel the following year.
The survey was mailed in March 2022 and the 7,038 target enterprises had the possibility to respond to it online or a paper form, if necessary. A reminder was sent to those who had not responded after a month or so and another reminder was sent later. In addition, the most important big enterprises were contacted separately, if necessary.
Public sector and private non-profit sector
The R&D data of general government and private non-profit sector were collected with an electronic form from units engaged in R&D activities. The data collection began in March and non-respondents were sent two reminders.
Higher education sector
The data of universities of applied sciences, university hospitals and the National Defence University, comparable to universities, are collected as a complete enumeration with a direct questionnaire.
The statistics describing the research and development activities of universities is a complete enumeration composed of several different data sources. The statistics are produced by combining the data received from the following sources:
A separate survey conducted by Statistics Finland which makes university-specific inquiries concerning the grants allocated to the full-time work of the researchers in the areas of responsibility (departments), investments in R&D activities, the funding of research relying on external funding per the source of funds, and the expenditure of research conducted with a university’s own funds per area of responsibility. For the calculation of R&D personnel, cross-sectional data of the university’s personnel is collected according to the situation at the end of September.
The Ministry of Education and Culture’s collection of personnel, establishment and financial data: The collection of personnel data yields person-year, occupational title, education, field of R&D, area of responsibility, and establishment data per individual. The details of the data collected on establishments provides data on the location of each individual’s workplace. These data are used in the calculation of the sub-regional and regional data. The details used in terms of the collection of financial data are the administrative expenditure in the financial statements. These are used in the calculation of the research portion of the current costs (excluding the research staff’s wage and salary costs).
The wage and salary data of the Confederation of Finnish Industries, which use the wage and salary data as well as occupational titles of university staff.
Data on the education and degrees of universities’ research staffs are obtained from Statistics Finland’s Register of Completed Education and Degrees.
Universities’ working hours monitoring and working plan data, which allow for calculating time-use coefficients by personnel groups and main fields of R&D. Statistics Finland collects the data in question every four or five years.
Calculation of universities
The statistics cover all universities in Finland. University research includes research carried out at university hospitals by the staff simultaneously holding a post at a university department (the individuals reported by universities in a direct questionnaire). Other research work carried out at university hospitals is inquired about with an electronic form as a separate survey.
‘Budget funding’ refers to the expenditure of research activities carried out with funding pursuant to the Universities Act. Universities’ own funding is composed of their funds spent on research activities (the research funding of universities’ funds and foundations as well as profit from business operations). Other funding which passes through the universities’ accounting is considered to be external funding of research. The funding data are inquired exclusive of value-added tax.
R&D personnel
The statistical unit of universities’ research staff is composed of individuals of whose working time more than 10 per cent concerns research. The data are produced by combining the department-specific personnel data provided by universities with the wage and salary data provided by the Confederation of Finnish Industries. Of the personnel working in departments engaged in research, researchers refer to persons with a researcher career stage defined in the personnel data of the Ministry of Education and Culture. This personnel includes doctoral school students, postdoctoral researchers, university lecturers, professors and research directors and fee-paid teachers. Other R&D personnel include research support staff and IT staff as well as, based on service, a few occupational titles without a researcher career stage. Classifications into personnel groups are made based on data on occupational titles. The R&D personnel of universities consists entirely of researchers and occupational titles defined as other R&D personnel. Educational data for the staff is obtained primarily from Statistics Finland’s data on completed education and degrees for the statistical year.
A department is considered to be engaged in research if the discipline researched has been determined for at least part of the staff. Usually, units of this kind also receive external research money, but they can also operate solely on the basis of basic funding. Administrative offices, libraries, language centres and training schools, for example, are not units engaged in research, even if data on a discipline were detailed for some of their staff.
R&D in full-time equivalents
The calculation of R&D in full-time equivalents is based on the proportions, arrived at with time-use coefficients, of research work by personnel groups on the level of the principal field of R&D. The time-use coefficients are calculated with the help of universities’ working hours monitoring and working plan data. R&D in full-time equivalents are calculated only for R&D staff working in the unit engaged in research. A portion of the other staff’s working hours is classified under research, but this is only counted as current expenditure, not as full-time equivalents. Uncertainties in the calculation relate to the determination of the research staff and the quality of the time-use coefficients. Some occupational titles to be included in research staff are also reclassified when the research portion is updated. R&D in full-time equivalents also includes work carried out with a grant. Data on grants paid through a university’s accounting are provided by a direct questionnaire of Statistics Finland in which the number of full-time equivalents carried out with a grant is inquired. The data on the number of full-time equivalents carried out with a grant obtained in the survey is supplemented by calculating the number of full-time equivalents from grants by dividing the amount of reported grants by the maximum amount of tax-free grants confirmed in the statistical reference year.
R&D expenditure
Research expenditure is composed of the R&D staff’s wage and salary expenditure, other current costs classified under research and capital costs. Wage and salary expenditure for a full-time equivalent are calculated according to the average wage and salary expenditure of a personnel group and universities. Holiday pay, social security costs and pension costs are added to the calculated wage and salary expenditure. The research portion of the wage and salary expenditure of staff, other than research staff, is included in other current costs. The basis for calculating the classification is the ratio of research wage and salaries to the university’s total wage and salary expenses. Any grants paid as wages are also included in research wages and salaries. A portion of premises costs, purchased services and other current costs is also calculated for research.
Data collection
Frequency of data collection
Methods
Data compilation
2) Item non-response is imputed with logical rules between variables and, in terms of business enterprises, with the previous year’s industry-specific distribution data
3) The greatest units in unit non-response are imputed with the previous year’s response.
4) In the business enterprise sector, the calculation of weighting coefficients in the panel section means non-response correction, in the sample section design weight (sampling ratio) is also included. The calculation of the weighting factors relies on the business register’s turnover data. A stratum’s weighting factor is the ratio between the total turnover of the business enterprises included in the survey and the turnover of the respondents. Group-level responses and some business enterprises considered extreme values in terms of the extent of research activities have been removed from the calculation of weight factors. These form their own post-stratum with a weighting factor of 1. The other sectors represent complete enumeration.
Data validation
Principles and outlines
Contact organisation
Contact organisation unit
Legal acts and other agreements
Further information: Statistical legislation
Commission Regulation (EC) No 2019/2152 requires the collection of data on research and development activities and their delivery to Eurostat. It also steers the compilation of the statistics.
Confidentiality - policy
Further information: Data protection | Statistics Finland (stat.fi)
Confidentiality - data treatment
The data are released in the basic publications mainly in such a way that separate protection is not required (the published data includes a sufficient number of observations and there is no dominance). If exceptions to this are made – by increasing the degree of detail in tabulations, for example – each case is assessed separately.
With regard to the public sector, the letter accompanying the questionnaire form notes that according to Section 12 of the Statistics Act, data describing the activities and public service production of central and local government authorities that are public based on other legislation are also public as statistical data. Data concerning individuals are private, and they are used solely for statistical purposes.
In the higher education sector, Statistics Finland releases university of applied sciences-specific and university-specific data on the basis of the written permissions it has received.
Release policy
Further information: Publication principles for statistics at Statistics Finland
Data sharing
Accessibility and clarity
In addition to statistical data published in the StatFin database, a release on the key data is usually published in the web service. If the release contains data concerning several reference periods (e.g. monthly and annual data), a review bringing together these data is published in the web service. Database tables updated at the time of publication are listed both in the release and in the review. In some cases, statistical data can also be published as mere database releases in the StatFin database. No release or review is published in connection with these database releases.
Releases and database tables are published in three languages, in Finnish, Swedish and English. The language versions of releases may have more limited content than in Finnish.
Information about changes in the publication schedules of releases and database tables and about corrections are given as change releases in the web service.
Data revision - policy
Revisions – i.e. improvements in the accuracy of statistical data already published – are a normal feature of statistical production and result in improved quality of statistics. The principle is that statistical data are based on the best available data and information concerning the statistical phenomenon. On the other hand, the revisions are communicated as transparently as possible in advance. Advance communication ensures that the users can prepare for the data revisions.
The reason why data in statistical releases become revised is often caused by the data becoming supplemented. Then the new, revised statistical figure is based on a wider information basis and describes the phenomenon more accurately than before.
Revisions of statistical data may also be caused by the calculation method used, such as annual benchmarking or updating of weight structures. Changes of base years and used classifications may also cause revisions to data.
Quality assessment
Quality assurance
Quality management requires comprehensive guidance of activities. The quality management framework of the field of statistics is the European Statistics Code of Practice (CoP). The quality criteria of Official Statistics of Finland are compatible with the European Statistics Code of Practice.
Further information: Quality management | Statistics Finland (stat.fi)
User access
Further information: Publication principles for statistics Unless otherwise separately stated in connection with the product, data or service concerned, Statistics Finland is the producer of the data and the owner of the copyright. The terms of use for statistical data.