from emerging to submerging economies new policy challenges for research and innovation

Luc Soete

From Emerging to Submerging EconomiesNew Policy Challenges for Research and Innovation

International Seminar: “The New Agenda for Innovation Studies and Policy Implications”, IREIN, Madrid, March 14th 2014.

Luc Soete – Universiteit Maastricht 2

Outline

• Start from a debate on March 4th with EC Commissioners Olli Rehn and Maire Geoghan-Quinn on conditions for growth.

• Follow-up from recent ERIAB Stress Test: “Placing excellence at the centre of research and innovation policy” presented at Innovation Convention earlier this week in Brussels.

• Divergence between international shifts in location of high-tech production and the value changes involved (see e.g. recent OECD study Interconnected Economies: benefiting from global value chains, 2013) and link with innovation versus international shifts in science.

• What are the policy implications of this divergence? And in particular what are the potential opportunities for new policy?


1. Investing in research and innovation

• Recognition of the long term importance of science, research and innovation is not an issue of debate in emerging countries where additional knowledge is considered these days as complementary to economic growth and structural change.

• Paradox is that in developed, knowledge based economies doubts are raised about the value of science and research. Yet, thanks to science and research our life expectancy has risen dramatically, there is more well-being than ever before, and we have more opportunities in life than previous generations.

• Discussion focuses on short vs long term: question in how far short term models as used by policy makers and economists in macro-economic similations, do contain in phases of “fiscal consolidation” an intrinsic bias against long term growth...

• Central role of public investment.


Public gross fixed capital formation (growth rates in volumes: 2009-2013)


Public prioritisation of R&D(GBAORD as % of total government expenditures)


Scenarios for R&I policies in 2014-2020

Scenarios Countries

“Modus operandi” Czech Republic, Hungary, Lithuania, Malta, Poland, Slovakia

“Empty pocket” Bulgaria, Cyprus, Greece, Italy, Latvia, Portugal, Romania, Slovenia, Spain

Long-term commitment to R&I policies

Past commitment based on regional identity

Austria, Denmark, Estonia, Finland, France, Germany, Ireland, Luxemburg, Netherlands, Norway, Sweden, Switzerland, UK

Belgium (Flanders)


Impacts of funding cuts: questions

• MS under the strongest budgetary pressures appear to have ‘consolidated’ their public spending most in areas where cuts in public spending raised the least immediate opposition but affected growth primarily in the long term.

• Raises the methodological question: to what extent do short term macro-economic models used for simulating MS’ fiscal needs contain an intrinsic bias against long term growth policy priorities (see e.g. the Dutch KNAW study)?

• What is the purpose and effectiveness of small countries (the majority of EU MS) investing in research as opposed to innovation?

• Has the continuous public support for R&I in countries with a pre-crisis priority given to R&I (Austria, Denmark, Estonia, Finland, Germany, Norway, Sweden, Switzerland) been a factor behind the stronger resilience of those economies, while providing them at the same time also with a less stringent fiscal consolidation framework?


2. An EU emerging knowledge divide?

• The euro-crisis has brought about a research and innovation divide within the EU likely to perpetuate itself.

• We witness the emergence within the EU of “submerging” economies (Paul Collier) with the crisis affecting their long term capacity to invest in human resources and R&I and as a result a brain drain of their most talented youngsters to the rest of Europe or abroad.

• Possible appearance of a knowledge divide “hysterisis effect”: while the current generation in “submerging“ economies appears more educated than the previous one, the lack of employment opportunities leads to rapid evaporation of this human capital. Combined with a structural declining trend in labour force participation because of ageing of the population, the high unemployment and low participation rate of youngsters is negatively affecting long-term productivity growth in those countries.


Common Smart Specialization Strategies?• Officially the heterogeneity of Europe’s regions requires more

place-based smart specialization strategies (S3) tailored for regions that reflect their absorptive capacity and regional characteristics.

• Less research-intensive regions should enhance the innovation capacity of domestic firms with a focus on the promotion of growth and new jobs.

• Prioritised investment in education and training to deliver social inclusion and an absorptive capacity for innovation outputs is essential to underpin measures to stimulate Research and Development and innovation investments in all types of regions but even more so in regions in receipt of ESIF

• Central role of regional policies: but are they well equipped?


SSS and globalisation of innovation

• Long tradition on economic research on impact of internationalisation in production.

• Today focus on global value chains: example of iPad but quid about the evidence at the more aggregate level about industries and countries?

• New trends: re-shoring? Using new technological developments such as 3-D printing? Starts again from practical product examples towards broader industry/country analyses.

• Opportunity for regional innovation policy? Local anchorage of creativity and innovation; possibly also with respect to servicing, but quid about production?

• Link with smart specialisation debate.


Country value distribution of an iPad

Source: Kraemer, Linden en Dedrick, 2011)


The smiling curve of the value chain


3. Policy challenges and inconsistencies

• Growing inconsistencies between MS’ and European research (ERA), innovation (IU) and social cohesion (ESIF) support policies: – EU programs are viewed by MS as fiscal “relief” for national

R&I budget rather than the result of “joint programming” initiatives

– Creating national/regional value out of grand challenges or how to link local “smart specialisation” with global grand challenges?

– Focus on “beggar-thy-neighbour” (e.g. R&D tax credits?) rather than on “smart” national/regional R&I policies.


Direct funding of business R&D and R&D tax incentives, 2010 (As a percentage of GDP, 2011)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45% Direct government funding of BERD Indirect government support through R&D tax incentives Data on tax incentive support not available


“Good science anywhere is good for science everywhere“ (Subra Suresh) • Long term global challenges to European nationally organized science

and research. The emergence of e-science (David Osimo):– New scientific outputs and players: nanopublications, data

and code; vertical disintegration of the value chain– Greater role for inductive methods: everything becomes a

Genome Project– Scaling serendipity: Big linked data, collaborative annotation,

social networking and knowledge mining detect unexpected correlations on a massive scale

– Better science: reproducible and truly falsifiable research findings; earlier uncovering of mistakes

– More productive science: reusing data and products, crowdsourcing work, reduce time-to-publication


Global Research Policy Challenges

• Shift from national focus of “national” research councils such as FWO, NWO, ERC, NSF, NISTEP, STEPI, Chinese Academy of S&T towards a more Global Research Council structure?

• How to sell to “national” policy makers in periods of fiscal “consolidation” that the heavily biased “long tail” output distribution of inventions with hundred years’ rate of return could be drastically brought back (see Bill Press keynote at 2013 AAAS meeting)?

• Global policy coordination migth be essential: Science 2.0 as MOOR (Massive Online Open Research) and Smart Science Specialisation?

• Not all research data is the same but interoperability of data is more hampered by different “quality notions” of data across disciplines than accross countries;

• Global crowd-funding as a new social capital in support of collective intelligence?


Conclusions

• Today, we have in Europe a strong European commitment to both research and innovation with the new Horizon 2020 programme illustrating the EC’s strong commitment to its own pattern of smart fiscal consolidation (within a declining overall budget, expenditures for research and innovation increased from 50 to 72 billion euros);

• And a diverging pattern in the public priority given to research in individual MS. Time hence for some more radical reflections on moving from the old “open” to more “strict methods of coordination” of “joint programming” of research.

• By contrast, in the area of European “social cohesion” policies aimed at achieving standard of living convergence, the EU is confronted for the first time with knowledge divergence. While the fact that the advantages accruing to certain MS (and regions) could be considered as an illustration of intra-European solidarity based, as in the case of development cooperation, their lack of effectiveness calls for more “open” differentiated regional strategies addressing policies as integral part of a new long term growth strategy.


Thank you for your attention!

from emerging to submerging economies new policy challenges for research and innovation

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