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  1. Science, Technology and Innovation Indictors ENID-PRIME summer school on S&T indicators Amsterdam September 1-4 2009 Innovation indicators Svein Olav Nås NIFU STEP and Research Council of Norway

  2. My background • Researcher since early 1990’s • Co-founder of STEP group in Oslo • Currently analysis for policymaking • OECD NESTI delegate • Drafting of Oslo manual • Economics a starting point • Evolutionary approach • Innovation systems • Administrative data • Firm demography, HRST • Non-R&D innovation – embedded knowledge

  3. Outline • Part 1 (2x45 min): What are innovation (indicators)? • Explicit measures; Frascati family, Oslo manual • CIS • Indirect/related measures; Other economic indicators • Outputs and effects • OECD innovation strategy • Micro analysis • Part 2 (45 min): Papers and posters • Knowledge investment agenda photo (Edo Haveman) • Measuring innovation in emerging economies (Marins and Zawislak) • The correlation between social capital and incremental innovation in small and medium enterprises (Maria Katia Orteca) • Part 3 (45 min): Needs, shortcomings and prospects • Innovation in public sectors • Entrepreneurship and firm demography • Skills for innovation • Policy for innovation • Other ideas • Discussion

  4. What are innovations - Schumpeter • Introduction of new products • New methods of production • Opening of new markets • Development of new sources of supply for raw materials or other inputs • Creation of new market structures in an industry

  5. What are innovations - and -indicators? • New, improved, new context, knowledge, intention, economic benefit, marketed/implemented • Modified?, copied?, embedded?, finalised?, successful?, profitable?, public sectors?, embedded?, .. • Product (good, service, solution/adventure?), process (organisation, marketing, delivery, business model?), source of raw materials?, market? • Timing: For how long is it new? • Inputs • Activities • Outputs • Effects • Complementary information? • Surveys or administrative data?

  6. STI indicators • The Frascati family of OECD manuals • STI as the starting point • R&D in Frascati the first concept – long time series • The conditions for and value of (academic) research • Explicit borderlines to development and innovation • A broadened perspective over time (for the family) • Patents as an output, trademarks, trade in intangibles (TBP), high-tech trade, scientific publications and citations • Human resources (HRST) (Canberra) • Globalisation – a big challenge to measurements • Generic technologies: ICT, Biotech, nano • Business demography • Oslo….

  7. R&D in Frascati • Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.

  8. Not R&D in Frascati • Education and training • Other related scientific and technological activities • Other industrial activities • Including innovation • Administration and other supporting activities

  9. Oslo Manual • Oslo manual 1992 • Explicitly addressing the left-overs from Frascati • R&D kept as a core activity • Biased towards manufacturing – TPP innovation • Product focus • Limited to what was considered measurable – pragmatic approach

  10. Oslo… • Second edition in 1997 • Adaptation to services • Third edition in 2005 • Linkages in focus • Marketing innovation • Organisational innovation • Recommends measure for output from process innovations

  11. Oslo innovation definition 2005 • An innovation is the implementation of a new or significantly improved product (good or service), process, or marketing method, or a significant organisational change. Innovations are the result of deliberate plans or activities aimed at improving the firm’s products and/or business functions. Innovations can utilise new knowledge or technologies, or can be based on new uses or combinations of existing knowledge or technologies.

  12. Oslo innovation activities definition 2005 • Innovation activities are all scientific, technological, organisational, financial and commercial steps, including investment in new knowledge, which actually, or are intended to, lead to the implementation of new or significantly improved products, processes, marketing methods or significant organisational changes. Some may be innovative in their own right, others are not novel activities but are necessary for the implementation of innovations. Innovation activities also include basic research that (by definition) is not directly related to the development of a specific innovation.

  13. Oslo (CIS) type innovation • Differences between the manual and actual surveys like CIS, Canada, Australia, Brasil – which also differ.. • CIS the de facto standard – but variations also in CIS (countries, time) • Intended to be inclusive • Diffusion; new to firm, open for “mainly developed by others” • Incremental innovation; New or significantly changed • Focus and filtering by outputs; innovations launched last 3 years or activities with the intention to launch • Innovative products shares of sales as output measures • Activity metrics by types of innovation activities • R&D bias

  14. CIS questionnaire 2008

  15. What did we get from Oslo? • Better understanding of innovation • Innovation is much more than R&D • Innovations are everywhere • Useful for micro-data analysis • International comparisons • Innovation modes – more nuanced concepts • Increasing number of academic publications • Good platform for further improvements and linking to external data

  16. What did we not get from Oslo (so far)? • Measures are not very accurate – indicators in the true sense • There is a lack of rigorous links to explicit theory – ad hoc modelling • Economic results and effects must be added from other sources • Insufficient information on “non-innovators” • Response rates are low • Lack of confidence among policymakers

  17. Outputs and effects • Innovation activities may result in measurable outputs, like • New products share of sales • Scientific publications • Patents, trademarks • Firms are not trying to innovate, but to earn money • Governments are not trying to be innovative, but to create welfare • Economic results are thus the first order effect • Defending a position may be a positive effect – but difficult to identify as such • Second order effects relate to other firms and society • Difficult to judge when, where and why effects occur • Metrics for effects to a large extent exist in the form of standard economic indicators – although sometimes difficult to match • Modelling – and underlying theory - essential for how causal relationships are understood

  18. Indirect/related measures • All the other Frascati family manuals, education, HRST • Other economic indicators, accounts, employment, wages, industry structure, market shares • New firm formation; entrepreneurship and firm demography, FDI • The timing issue: causality, panel data • Immeasurable effects: Things we don’t see or count, keeping position • Public sectors without measurable output • Social versus private effects and benefits • Anything new or only useful new – which is?? • Indirect effects – input output tables • Policy interventions

  19. OECD innovation strategy • Initiated by Ministers 2007 – to deliver by summer 2010 • Broad notion of innovation as engine of sustainable growth • Whole-of-government approach • References to current crisis and global challenges • “The quick pace of change and the new forms innovation is taking, require thorough consideration of what should and can be measured”

  20. IS – NESTI roadmap • NESTI roadmap – inspired by Blue sky II, Canada • Gap analysis – what we know and need to know • (Econometric) analysis of micro data (CIS and similar) • CDM type productivity model • Innovation modes, cluster analysis • Matching with external data; accounts, patents • Skills for innovation, HRST • Innovation in public sectors • Public support to innovation • Harmonising and rethinking R&D and innovation surveys • Output indicators - results, effects • Openness and knowledge flows • Intangible assets revisited • Measurement of generic technologies – a common approach?

  21. Extended CDM Nordic

  22. CDM core model findings • 20 countries, 4 with extended model • Surprisingly robust despite important problems (timing, productivity, endogeneity) • Similar results across countries • Innovation inputs affect innovtion outputs positively which affects productivity positively • The model needs and can be refined

  23. Extended model in 4 countries • Confirms core model although smaller coefficients • Better productivity measures • Inclusion of output of process innovation with positive coefficient • Panel to time inputs and outputs correctly • Dummies replaced with metrics where possible • Herfindahl index for concentration and industry characteristics, previous performnce

  24. Papers and posters • Knowledge investment agenda photo • Edo Haveman • Measuring innovation in emerging economies • Marins and Zawislak • The correlation between social capital and incremental innovation in small and medium enterprises • Maria Katia Orteca

  25. Innovation in public sectors • Make up large shares of the economies • Conscious renewal and improvements going on • Much activity similar to private services • Highly competent, utilises knowledge by persons, embedded, codified, commissions new knowledge • What are the public sectors? • Administration • Health • Education • Infrastructure, security • SNA, ownership, NACE? • Public sectors are very different, nationally and across countries • Address activities independent of sector?

  26. Innovation in public sectors 2 • What are the relevant units to address? • Command lines, cost cutting, producing more efficiently • Different incentive structures from business • Lack of markets and prices; outputs==inputs, difficult to establish productivity measures • Two approaches: • CIS inspired survey (Nordic, NL) • Re-use/interpretation of national accounts data (UK) • Questionnaires become complex, conflicts with massive existing reporting systems • Existing data less accurate in terms of contents/definitions

  27. Entrepreneurship and firm demography • Economic growth and restructuring via two (interrelated) main routes: • Innovation in existing firms • Firm creation, destruction and reorganisation • The relationships needs to be investigated • Firm demography poorly understood • Success criteria and potential for entrepreneurship still open q. • Can be studied using business registers and matched employer-employee data

  28. Skills for innovation • “Knowledge society” interpreted to signify “more theoretical knowledge to all”: • Longer and more theoretical educations • R&D as core ingredient for innovation • Only R&D and education data available/in use • Innovation means doing something different, original, new or in a new setting • Most likely it involves things like ability to combine knowledge, coordinate, communicate, organise, market, establish positive relationships, trust, risk management, being visionary, seeing opportunities,… • Where do we find the relevant information on this? • Education is not enough • Is something hidden in CVs, other types of track records, income statements? • Can the issue be surveyed – who and what should be asked?

  29. Policy for innovation • Govenments support R&D and higher education and to some extent other types of innovation activities • Right types of education – other skills? • Is R&D it – and do we supply the necessary complements? • Do we manage to support other things than “things” – for business services, new business models, public services? • How much do governments effectively spend on innovation policies? Composition? Does it work? International comparisons? • Are R&D tax credits better than direct support, crowding out or additionality? • What innovation related bi-effects occur from all other types of regulations? • Are anti-trust policies conducive for innovation, from a national perspective? • Is the national level relevant for statistics on operations that are global in nature?