Measuring Research and Experimental Development
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Transcript Measuring Research and Experimental Development
Measuring R&D:
Challenges Faced by Developing Countries
CENTRAL ASIAN SUB-REGIONAL CONSULTATION MEETING ON SCIENCE, TECHNOLOGY AND
INNOVATION (STI) STATISTICS AND INDICATORS
Tashkent, Uzbekistan
4-5 November 2010
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Outline
The problem
The process
Contents of the Technical Guide
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 policyrelevance?)
• S&T is still not properly represented in economic/social
public policies. lack of resources devoted to statistics in
S&T
• lack of technical knowledge for the production of crossnationally comparable R&D statistics
• weak statistical institutions
• difficulties in applying FM concepts and methods
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R&D statistics in developing countries (2)
Particular characteristics of R&D activities to be taken into
account:
• R&D performers function within the specific context of a national,
cultural, political, financial and economic system
• 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
• adapted to particular policy needs
• provide answers to actual policy questions
However, international comparability is foremost
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The process
Process started in 2007
Lead papers by consultants
Meetings in 2007 and 2010
Experience acquired through the UIS work
Proposal for an annex to the Frascati Manual at
the OECD 2008 and 2009 NESTI meetings
Technical Guide released in English
• Translations in Spanish and French almost finished
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Products
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Contents of the Technical Guide
1. Introduction
2. The nature of R&D activity in developing countries
3. R&D expenditure
4. Internal and international mobility of the R&D workforce
5. Specific fields of R&D activity
6. Foreign and internationally controlled entities
7. Strengthening R&D statistical systems
8. Thinking ahead
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Chapter 2: The nature of R&D activity in
developing countries
The growing importance of R&D
• More ‘R’ than ‘D’ in developing countries.
• Strong presence of the government and
higher education sectors in the
performance of R&D. Lower emphasis on
R&D in business sector.
• Occasional R&D / Informal R&D
• Special types of R&D
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Chapter 2: The nature of R&D activity in
developing countries
cont…
Heterogeneity and concentration
•
Developing countries are a heterogeneous
group:
» Group A: countries with consolidated R&D systems and
developed S&T statistics systems no major difficulties in
applying Frascati Manual concepts.
» Group B: countries with consolidated R&D systems and
less developed S&T statistics systems need specific
guidance on how to establish and consolidate sound R&D
statistics systems.
» Group C: countries with incipient R&D systems need
specific guidelines on how to start creating a regular R&D
statistical collection.
•
High degree of concentration (in group of
countries, in particular institutions, in major
projects, etc) lead to volatility and inconsistencies in
statistics.
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Chapter 3: R&D expenditure
Use of secondary data from national budget
New sources of funds emerging
Discrepancy between voted and allocated budget
Budgetary commitments are not followed up
Mixing of budgetary records and annual reports from performing units
Definition of S&T / R&D budgets
Identifying R&D components in the national budget
State-owned enterprises, university-owned companies and national
scientific academies
Private universities
Fiscal year vs. calendar year
Information systems in government and higher education inadequate
for statistics
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Chapter 4: Internal and international
mobility of the R&D workforce
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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Chapter 5: Specific fields of R&D activity
Traditional knowledge
Clinical trials
Industrial activities
Other activities
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Special types of R&D - Traditional
knowledge
Traditional knowledge (TK)
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
Scientific approach to TK (in ethno-botany, ethnopedology, ethno-forestry, ethno-veterinary medicine, ethnoecology, etc).
The application of scientific methods to TK,
converting it into a source of scientific information.
(in biodiversity science or nature conservation; traditional
health and pharmacopeia).
Interaction between scientists and communities in
participatory technology development
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Special types of R&D - Traditional
knowledge
Measurement issues and recommendations
Establish the boundaries for TK (what qualify as
R&D)
The activities establishing an interface between
traditional knowledge and R&D
Some fields of activities in TK are transdisciplinary (e.g. ethno-botany), making them
extremely difficult to map into the current
classification’s structure.
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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
• R&D only in development and testing phase
experimental development (most probably in the field of
social sciences)
Religious research
• part of humanities,
• should be included in R&D surveys.
This (religious research) will not be a recommendation
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Chapter 6: Foreign and internationally
controlled entities
Foreign antennas
Foreign company’s R&D labs
International organizations operating in the
country
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
What is included?
• Foreign antennas
• International organizations
• Foreign company’s R&D labs (remains in the business sector)
• Foreign universities (remains in the HE sector)
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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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Chapter 7: 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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Chapter 8: 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
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Thank you!
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[email protected]
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