Www.uis.unesco.org Measuring R&D in Developing Countries: Annex to the Frascati Manual TRAINING WORKSHOP ON SCIENCE, TECHNOLOGY AND INNOVATION INDICATORS.

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Measuring R&D in Developing Countries: Annex to the Frascati Manual TRAINING WORKSHOP ON SCIENCE, TECHNOLOGY AND INNOVATION INDICATORS Cairo, Egypt September 2009

Outline The problem The process Contents of the Paper Thinking ahead

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

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.

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 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.

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

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

Contents of the Working Paper 1.Introduction 2.Characteristics of R&D in Developing Countries Will 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

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

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.

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

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

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

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

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

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.

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

The foreign institutions sector What is included? Foreign antennas International organizations operating in the country Remains in the business sector: Foreign companys R&D labs Remains in the HE sector: Foreign universities based and conducting R&D in campuses set up in the country

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

The foreign institutions sector The principal sector sub-classification Business enterprises Government Higher Education Private non-profit International organizations

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 Masters research

Counting researchers Overestimation of researchers Counting the contract instead of the real effort Multiple full-time research positions

Counting researchers Special cases FTE calculation >1 and FTE>HC R&D in times of crisis Visiting researchers Brain circulation

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

Other issues Informal R&D: Occasional R&D R&D in the informal sector Budget data

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

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

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.

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.

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.

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.

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.

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.

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.

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

Thank you!