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Measuring R&D in Developing Countries: Annex to the Frascati Manual
TRAINING WORKSHOP ON SCIENCE, TECHNOLOGY AND INNOVATION INDICATORSCairo, Egypt
28-30 September 2009
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Outline
• The problem
• The process
• Contents of the Paper
• Thinking ahead
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R&D statistics in developing countries (1)
• Recognition, meeting targets, evidence-based S&T policy, but:
• lack of interest at the level of policy makers (low policy-relevance?)
• lack of resources devoted to statistics in S&T
• lack of technical knowledge for the production of cross-nationally comparable R&D statistics
• difficulties in applying FM concepts and methods
• weak statistical institutions
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R&D statistics in developing countries (2)
• Particular characteristics of R&D activities to be taken into account:
• different structures in terms of government, innovation system, higher education system, statistical system
• particular ‘culture of information’
• Users of R&D stat: Gov, analysts. + international donor agencies
• S&T indicators need to be adapted to particular policy needs, and need to provide answers to actual policy questions.
• However, international comparability is foremost.
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The process (1)
• Experience acquired through the UIS work, in particular through direct contact with S&T statisticians in numerous workshops and other meetings around the developing world.
• Advisory Meeting to the UIS S&T Statistics Programme held in Montreal, Canada, December 2007.
• Papers commissioned by UIS to Jacques Gaillard (IRD, Paris), Michael Kahn et al (HSRC, South Africa), and Gustavo Arber et al (RICYT, Argentina).
• Proposal for an annex to the Frascati Manual on measuring R&D in developing countries was presented at the OECD 2008 and 2009 NESTI meeting.
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The process (2)
• Expert Meeting on Measuring R&D in Developing Countries in Windhoek, Namibia, 14 to 16 September 2009
• Consultant to draft:• Working paper on Measuring R&D in Developing
Countries
• Proposed Annex to the Frascati Manual
• Both to be released in 2010
• Some of the issues might also present measurement challenges for a future revision of the Frascati Manual
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Main outcomes of the Namibia meeting
Developing countries a very heterogeneous concept
Problems not unique to developing countries
Stay within boundaries of FM
Most recommendations stood up
Much additional work needed
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Contents of the Working Paper
1. Introduction
2. Characteristics of R&D in Developing CountriesWill be merged with
3. Special Concepts and Definitions to be Applied in Developing Countries
4. Strategies for setting up S&T statistics systems
5. Thinking Ahead
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Chapters 2 and 3: Characteristics of R&D in Developing Countries + measurement implications
• Heterogeneity and concentration
• Special types of R&D
• Traditional knowledge
• Clinical trials
• Industrial activities
• Other activities
• Foreign institutions
• Counting researchers
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Special types of R&D - Traditional knowledge
Traditional knowledge
A cumulative body of knowledge, know-how, practices and representations maintained and developed by peoples with extended histories of interaction with the natural environment.
These sophisticated sets of understandings, interpretations and meanings are part and parcel of a cultural complex that encompasses language, naming and classification systems, resource use practices, ritual, spirituality and worldview.
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Special types of R&D - Traditional knowledge
Dichotomy between traditional and scientific knowledge systems
• substantive grounds – because of differences in the subject matter and characteristics of traditional and scientific knowledge
• methodological and epistemological grounds – because the two forms of knowledge employ different methods to investigate reality
• contextual grounds – because traditional knowledge is more deeply rooted in its environment
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Special types of R&D - Traditional knowledge
Links between traditional and scientific knowledge systems
• Traditional knowledge (in general) as an object of scientific study.
• The application of scientific methods to traditional knowledge, converting it into a source of scientific information
• Interaction between scientists and communities in participatory technology development
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Special types of R&D - Clinical trials
Clinical trials
• (Can) involve a significant amount of R&D
• Need to be conducted on a wide population
• Growth area for developing countries
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Special types of R&D - Clinical trials
Measurement of clinical trials
• Registers of clinical trials available, e.g. WHO but also national
• Funding often from abroad
• Performance various possibilities• a local branch of the foreign main sponsor
• universities and university hospitals
• individual researchers
• local medical clinics
• locally registered PNPs
• international PNPs
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Special types of R&D - Clinical trials
Measurement issues and recommendations
• Occupation category of local staff
• Medical doctors and other professionals with at least ISCED 5A degrees should be considered as researchers
• Nurses and other staff with qualifications below ISCED 5A should be accounted for as technicians
• FTE calculation is important (often part-time)
• Attribution of sector of performance must be done with care to avoid double counting
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Special types of R&D - Industrial activities
• Reverse engineering: understanding the structure and functioning of an object (in order to make a new device or program creates a similar object in a different way), copying it, or improving it.
• Recommendation: If reverse engineering is carried out in the framework of an R&D project to develop a new (and different) product, it should be considered as R&D.
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Special types of R&D - Other activities
• Community development and other social projects should be considered R&D only as long as they are in a development and testing phase, in which case they should be counted as experimental development, most probably in the field of social sciences
• In some developing countries, religious research has a particular importance. In principle, religious research is a part of humanities, and institutions performing it should be included in R&D surveys. Such countries might consider for example compiling the R&D activity of religious institutions as a separate sector.
This (religious research) will not be a recommendation
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The foreign institutions sector
What is included?
• Foreign antennas
• International organizations operating in the country
Remains in the business sector:
• Foreign company’s R&D labs
Remains in the HE sector:
• Foreign universities based and conducting R&D in campuses set up in the country
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The foreign institutions sector
Recommendation
• Create a “foreign institutions” (FI) sector as a separate sector of performance
• Funding flowing from this sector to other sectors should be considered from “Abroad” as stated in the main body of the Frascati Manual
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The foreign institutions sector
The principal sector sub-classification
• Business enterprises
• Government
• Higher Education
• Private non-profit
• International organizations
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Counting researchers
Underestimation of researchers
• Unpaid research
• Informal research
• Research outside of the normal work setting with external funding
• Multiple part time positions not taken into account or undercounted
• Master’s research
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Counting researchers
Overestimation of researchers
• Counting the contract instead of the real effort
• Multiple full-time research positions
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Counting researchers
Special cases
• FTE calculation >1 and FTE>HC
• R&D in times of crisis
• Visiting researchers
• Brain circulation
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Counting researchers
Recommendations
• Peer interviews of researchers
• Include a module on barriers
• Use secondary sources• Publication databases, both national and international
• STMIS and other databases of researchers
• Databases and registers of clinical trials
• Databases and registers of the main foreign donors involved in funding R&D in the countries
• University accreditation databases
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Other issues
• Informal R&D:• Occasional R&D
• R&D in the informal sector
• Budget data
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Chapter 4: Strategies for setting up S&T statistics systems in developing countries
• Institutionalizing S&T statistics
• Establishing registers
• Structural issues in the private sector and the private not-for-profit sector
• User-producer networks
• Science & Technology Management Information Systems and other secondary sources
• Survey procedures and estimation
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Institutionalization of S&T statistics
Political support
Infrastructure and sustained staff training/capacity building
Involvement of NSOs: “Official statistics” status for R&D surveys.
Adequate legal framework
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Establishing registers
• R&D in developing countries tends to be very much the purview of public bodies
Recommendations:
• Establishing a database of public sector R&D projects
• include human and financial resources; align with national policies.
• design could reflect the R&D statistical reporting/definitions.
• source for evaluation of such projects.
• Establishing STMIS
• provide overview of research system.
• framework for establishing complete registers as sample frames for R&D surveys.
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Establishing registers
• Other sources
• associations (trade, academic).
• learned societies.
• registers or databases of scientists and engineers.
• database of research grants.
• databases of scientific publications.
• patents and other IP documents.
• business registers.
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Structural issues in the private sector and the PNP sector
• Publicly-owned businesses play a major role in R&D in some developing countries
Recommendations:
• should consider issuing data for ‘publicly-owned businesses’ separately from the ‘fully private enterprise sector’.
• private enterprises could also be disaggregated by ownership, in particular the various degrees of foreign ownership.
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Structural issues in the private sector and the PNP sector
• Business enterprise R&D is presumed to be generally weak in developing countries when compared to industrial countries.
Recommendations:
• take into account when conducting sample surveys, perhaps by over-sampling, especially amongst larger companies.
• big companies should not be missed out as it might imply significant error.
• invest time in interviewing key firms to understand their R&D function and obtain a clear picture of their activity.
• Private-non-profit sector: make a significant contribution to R&D in developing countries, but the sector tends to be very volatile.
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User-producer networks
Recommendations: • user-producer networks and other forms of stakeholder
consultation should be instituted.
• establishing national S&T statistics groups.
• involve multiple actors.
• coordinating/networking among institutions/databases.
• partnering with business associations.
• conducting face-to-face visits by statisticians and project leaders.
• exploit pre-existing personnel ties.
• get NSO involved; to deal with privacy of information.
• training of interviewers/primary data producers.
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Science and Technology Management Information System and other secondary sources
• STMIS (e.g. database of scientists, research grants, etc): frequent source for the production of R&D statistics.
Recommendations: • need close integration between the statistical system and the
STMIS.
• need adjustments to produce comparable statistics, taking into account issues of definitions and coverage.
• need a balanced approach using both STMIS and surveys.
• need different approach to Private sector organizations as they are frequently not covered by these systems.
• Combined R&D and innovation surveys
Recommendations: • the relative rarity of occurrence of R&D in businesses needs to be
taken into account.
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Survey procedure and estimation
Recommendations:• attention needs to be paid to questionnaire design.
• frequency of survey.
• prioritize area of work; accompanied by step-by-step approach.
• use of survey questionnaires of other countries for inspiration: need adaptations to local situation.
• get expertise from the NSO, in conducting survey, in sampling ….
• different questionnaires might be designed for different sectors based on stakeholder consultations. “one size does not fit all”.
• procedures need to be developed for estimating missing data.
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Thinking ahead: Other products – beyond R&D
Redefine the concepts of scientific and technological education and training at broadly the third level (STET), Scientific and technological services (STS) and S&T activities (STA)
Better integrate education statistics with R&D statistics
Hands on guidance
Metadata
Model questionnaire
