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WIRE: Week of Innovative Regions in Europe Granada, 15th‐17th March 2010
Claire NauwelaersInnovation Unit
Competitiveness and Regional Governance DivisionPublic Governance and Territorial Development Directorate
OECDThe challenges for regional innovation policies: an EU-OECD project
Staying Competitive in a Changing World :Regional Innovation and Cohesion Policies
Present and Future
Brussels 14 September 2010
The challenges forinnovation in regions
Claire NauwelaersRegional Development Policy Division
OECD
Why worry about innovation and regions?
• Innovation has received increased priority to address not only productivity gaps, but also societal challenges in the move towards smart, sustainable and inclusive societies
• Regions are called as innovation mobilisers in their countries. Two moves: attention to territories in national innovation policies; more stress on innovation in regional development policies
• The adoption of a broader concept of innovation gives a chance to regions that are not at the technology frontier
How to organise complementarity/synergies between policies at various levels of government?
How effective are innovation policies by, for, in regions??
Sources§ New research (in house, outside)
§ OECD Survey on multi-level governance of STI policy
§ OECD Territorial Reviews• Globalisation and Regional
Economies (several case studies)
• North of England, UK
• Piedmont, Italy
• 15 Mexican States
• Catalonia, Spain
• Basque Country, Spain
• Switzerland
OECD Survey of the multi-level governance of science, technology and innovation 2010
Survey content
– Roles, budgets and challenges at different levels
– Multi-level governance coordination
– Instruments used at different levels
– Regional dimension of national S&T and innovation policies
– Future trends expected
Sources§ New research (in house, outside)
§ OECD Survey on multi-level governance of STI policy
§ OECD Territorial Reviews• Globalisation and Regional
Economies (several case studies)
• North of England, UK
• Piedmont, Italy
• 15 Mexican States
• Catalonia, Spain
• Basque Country, Spain
• Switzerland
Some typical responses to the OECD survey• Information sharing across levels of government to inform each
other's policy is difficult
• Capacity problems at sub-national level to formulate and deliverpolicy
• Financial resources are insufficient for certain regions/localities toactively participate and implement strategic plans
• Administrative boundaries at regional and city/local level are animpediment to policy efforts
• Policy silos at supranational/national level undermine efforts tocoordinate at the sub-national level
• Inefficiencies are high given the proliferation of programmesemanating from different levels
• Gaps in the allocation of responsibilities result in policy areas unmet atany level of government
Rationale for regional innovation policy
• Proximity matters for knowledge flows, because of tacit dimension: capitalising on localised knowledge spillovers, lower transaction costs, social capital: nurturing the innovation eco-system
• Indivisibilities imply economies of scale and different levels of intervention for activities with different degree of indivisibility
• Empirical evidence on regional disparities and uneven geography of innovation (agglomeration trend): need for differentiated approaches
• Regional governments are closer to actors in the field: reducing the information gap for managing some innovation support instruments (networks...)
Justifying the regional dimension = Fighting myths
• Myth 1: “Concentration = growth”
• Myth 2: Supporting lagging regions is a “social” policy not economic policy
• Myth 3: Urban regions drive growth and rural regions are marginal
• Myth 4: Infrastructure drives growth
• Myth 5: Only regions with a dense R&D infrastructure are innovative
• Myth 6: We should look for best practices in policies
Sources: OECD (2009) Regions Matter: Economic Recovery, Innovation and Sustainable Growth OECD (2009) How Regions Grow: Trends and Analysis.
Does concentration = growth?In practice, many other patterns emerge
Economic DensityGDP per square kilometre
Labour ProductivityGDP per worker
Economic GrowthReal GDP per capita growth
Germany
Source: OECD (2009) Regions Matter: Economic Recovery, Innovation and Sustainable Growth
Other findings…• Disparities are not simply a function of development
phase, both convergence and divergence appear at all levels of GDP
• Supporting lagging regions is not just a “social” policy as they contribute a large share of national growth
• Urban regions may have higher GPD per capita but many rural regions have higher growth rates
• Infrastructure influences growth only when human capital and innovation are present: complementarities are at play
Sources: OECD (2009) Regions Matter, and OECD (2009) How Regions Grow: Trends and Analysis.
.
Higher GDP per capita… Higher Productivity…
-50% 0% 50% 100% 150%
DEAGU
BERLIN
LILLE
TAMPA BAY
MANCHESTER
VALENCIA
ANKARA
KRAKOW
PHOENIX
ST.LOUIS
PITTSBURGH
MELBOURNE
COPENHAGEN
BUSAN
RANDSTAD-HOLLAND
PORTLAND
TURIN
PUEBLA
ISTANBUL
DUBLIN
OECD AVERAGE
BARCELONA
SAN DIEGO
AICHI
ATLANTA
HELSINKI
GUADALAJARA
VIENNA
DALLAS
MILAN
STOCKHOLM
MINNEAPOLIS
ROME
ATHENS
HOUSTON
MEXICO CITY
PRAGUE
PARIS
BUDAPEST
WARSAW
-50% 0% 50% 100%
NAPLES
LEEDS
MONTREAL
VANCOUVER
LILLE
TAMPA BAY
FUKUOKA
ST.LOUIS
MELBOURNE
PHOENIX
MIAMI
BARCELONA
STUTTGART
MILAN
LONDON
PORTLAND
OSAKA
HANBURG
FRANKFURT
ZURICH
MADRID
CLEVELAND
BRUSSELS
OECD AVERAGE
DETROIT
SAN DIEGO
LOS ANGELES
DENVER
PRAGUE
ATHENS
PARIS
SEATTLE
BOSTON
BUDAPEST
AUCKLAND
NEW YORK
WASHINGTON
SAN FRANCISCO
BUSAN
WARSAW
-30.0% -20.0% -10.0% 0.0% 10.0% 20.0%
NAPLES
RHINE-RUHR
PUEBLA
OSAKA
MONTERREY
FUKUOKA
BIRMINGHAM
HOUSTON
VIENNA
NEW YORK
PARIS
STUTTGART
LOS ANGELES
COPENHAGEN
ANKARA
MONTREAL
ATHENS
LEEDS
OECD AVERAGE
PHILADELPHIA
DALLAS
VANCOUVER
BALTIMORE
SAN DIEGO
LONDON
AICHI
PHOENIX
TAMPA BAY
SYDNEY
ST.LOUIS
WARSAW
BRUSSELS
ZURICH
WASHINGTON
VALENCIA
TURIN
KRAKOW
BUDAPEST
BARCELONA
MINNEAPOLIS
(Higher Employment…)
Concentration correlated with higher performance(TL3 predominantly urban regions 2005: comparison with country average)
Other findings…• Disparities are not simply a function of development
phase, both convergence and divergence appear at all levels of GDP
• Supporting lagging regions is not just a “social” policy as they contribute a large share of national growth
• Urban regions may have higher GPD per capita but many rural regions have higher growth rates
• Infrastructure influences growth only when human capital and innovation are present: complementarities are at play
Sources: OECD (2009) Regions Matter, and OECD (2009) How Regions Grow: Trends and Analysis.
.Higher GDP per capita… Higher Productivity…
-50% 0% 50% 100% 150%
DEAGU
BERLIN
LILLE
TAMPA BAY
MANCHESTER
VALENCIA
ANKARA
KRAKOW
PHOENIX
ST.LOUIS
PITTSBURGH
MELBOURNE
COPENHAGEN
BUSAN
RANDSTAD-HOLLAND
PORTLAND
TURIN
PUEBLA
ISTANBUL
DUBLIN
OECD AVERAGE
BARCELONA
SAN DIEGO
AICHI
ATLANTA
HELSINKI
GUADALAJARA
VIENNA
DALLAS
MILAN
STOCKHOLM
MINNEAPOLIS
ROME
ATHENS
HOUSTON
MEXICO CITY
PRAGUE
PARIS
BUDAPEST
WARSAW
-50% 0% 50% 100%
NAPLES
LEEDS
MONTREAL
VANCOUVER
LILLE
TAMPA BAY
FUKUOKA
ST.LOUIS
MELBOURNE
PHOENIX
MIAMI
BARCELONA
STUTTGART
MILAN
LONDON
PORTLAND
OSAKA
HANBURG
FRANKFURT
ZURICH
MADRID
CLEVELAND
BRUSSELS
OECD AVERAGE
DETROIT
SAN DIEGO
LOS ANGELES
DENVER
PRAGUE
ATHENS
PARIS
SEATTLE
BOSTON
BUDAPEST
AUCKLAND
NEW YORK
WASHINGTON
SAN FRANCISCO
BUSAN
WARSAW
-30.0% -20.0% -10.0% 0.0% 10.0% 20.0%
NAPLES
RHINE-RUHR
PUEBLA
OSAKA
MONTERREY
FUKUOKA
BIRMINGHAM
HOUSTON
VIENNA
NEW YORK
PARIS
STUTTGART
LOS ANGELES
COPENHAGEN
ANKARA
MONTREAL
ATHENS
LEEDS
OECD AVERAGE
PHILADELPHIA
DALLAS
VANCOUVER
BALTIMORE
SAN DIEGO
LONDON
AICHI
PHOENIX
TAMPA BAY
SYDNEY
ST.LOUIS
WARSAW
BRUSSELS
ZURICH
WASHINGTON
VALENCIA
TURIN
KRAKOW
BUDAPEST
BARCELONA
MINNEAPOLIS
Higher Employment…
Concentration correlated with higher performance
(TL3 predominantly urban regions 2005)
-6%
-4%
-2%
0%
2%
4%
6%
Lond
onPr
ague
Leed
sM
anch
este
rBi
rmin
gham
Nap
les
Stoc
khol
mR
ome
Mila
nLy
onW
arso
wBu
san
Turin
Mun
ich
Dub
linSt
uttg
art
Hel
sink
iTo
kyo
Fuku
oka
Lisb
onVa
lenc
iaM
adrid
Cop
enha
gen
Paris
Aich
iFr
ankf
urt
Lille
Brus
sels
Seou
lO
slo
Anka
raH
ambu
rgR
ands
tad-
Hol
land
Osa
kaVi
enna
Ista
nbul
Rhi
ne-R
uhr
Barc
elon
aBe
rlin
Athe
nsIz
mir
Krak
owD
aegu
Buda
pest
…but recent Growth has often been below national averages
(TL3 predominantly urban regions 2005 –difference w. National Growth)
Strong regional disparity in R&D and patentsR&D as a share of GDP Share of patents in top 10% of regions
Source: OECD (2009) OECD Regions at a Glance 2009.
R&D, patent variables are associated with growth – NOT for lagging regions
Notes: Lagging= initial GDP per capita <75% of national average, quasi-lagging =75-99% of national average, leading above the national average, growing =GDP per capita growth above the national average rate, underperforming=growth rate below the national average. Data from 1995-2005.
Source: OECD Regional database
population density 102 98 178 156 612 471GDP density (PPP yr 2000) 1.9 1.1 4.3 3.2 28.3 17.7productivity (PPP yr 2000) 31476 29380 54098 50141 72210 56819employment rate 58% 57% 69% 66% 68% 64%unemployment rate 9.69 7.07 6.35 8.30 5.86 7.30youth unemployment rate 24.14 25.49 16.80 21.45 14.84 19.50patent applications 33 31 271 214 985 514patent intensity 13.63 11.76 67.14 65.87 124.44 72.52primary attainment rate over LF 45.20 46.25 28.54 24.36 27.13 30.91tertiary attainment rate over LF 12.90 13.06 10.76 13.21 9.73 11.21infrastucture 0.24 0.15 0.29 0.20 0.19 0.20BERD % GDP 34% 42% 95% 89% 127% 104%GERD % GDP 25% 21% 23% 13% 40% 17%HED % GDP 41% 39% 36% 36% 43% 33%distance to mtks 4.56 4.54 4.58 4.54 4.63 4.58accesibility to mtks 2.39 2.08 1.59 2.09 2.31 2.81# regions in each category 37 15 61 103 54 55
leading underperforming
lagging growing
lagging underperforming
quasi‐lagging growing
quasi‐lagging underperforming
leading growing
Average values per group, relative to national averages
Lessons from empirical analyses• Disparities are not simply a function of development
phase, both convergence and divergence appear at all levels of GDP
• Supporting lagging regions is not just a “social” policy as they contribute a large share of national growth
• Infrastructure influences growth only when human capital and innovation are present: complementarities are at play
• Opportunities for growth exist in various types of regions
• Policy interventions should be informed by soundunderstanding of regional sources and barriers for growth
• R&D policies are long-term policies
Sources: OECD (2009) Regions Matter, and OECD (2009) How Regions Grow: Trends and Analysis.
Regional innovation policies
Looking for “the best” policy model??
Three arguments for more effective innovation policies in regions:
1. Variety in innovation policy models
2. Openness (content, space) of policies
3. Policy learning and experimentation
Diverse regions, diverse policy responses
• S&T–driven innovation /application , adaptation of knowledge
• Specialisation of productive fabric
• Potential niches for smart specialisation
• Innovation driven by large incumbents/New firms
• Density of local linkages, regional cohesion, social capital
• Orientation and strength of global linkages
• Specific RIS bottlenecks: human capital, finance, etc.
• Institutional competences of the region in innovation
• Formal powers versus effective powers and budgetary means
• Intensity and quality of public commitment to innovation
• Development choices, strategic priorities, future visions…
Diverse regions, diverse policy responses
Regional innovation policy portfolios reflect diversity of regions along three dimensions:
1. Institutional power of the region in country context
2. Economic specialization, innovation profile
3. Strategic development choices
Tendency to overlook one or two dimensions!
Identifying Policy Models
• The policy question: how to prioritise between various possible regional policy objectives ?
• An answer: identifying typical policy models - and associated policy instruments portfolios (traditional, emerging, controversial) – away from the “supply-matching-demand” model, balance between knowledge creation-absorption-diffusion :
• “Entrepreneurial” model
• “Node in global hub” model
• “Absorptive capacity” model
• “Innovation ecosystem” model
• “S&T co-generation” model
• …
Towards “borderless” innovation policies for regions
1. The need for borderless content of innovation policies
– “Hidden” forms of innovation, beyond R&D-driven innovation, should bestimulated through mixes of instruments from various policy areas: education, S&T, environment, infrastructure, etc.
2. The need for borderless territory for innovation policies
– Innovation does not stop at administrative borders: cross-border collaborations in policies are called for to target functional areas
– RIS are not “small NIS”: complementarities need to be ensured between policies and instruments at various levels
Policies versus policy mix
RIS Characteristics
Broad Policy Objectives
Policy impacts
R&D policy instrument
R&D policy instrument
R&D policy instrument
R&D policy instrument
R&D policy instrument
R&D policy instrument
R&D policy instrument
R&D policy instrument
R&D policy instrument
Other policy instrument
Other policy instrument
Other policy instrument
Other policy instrument
Other policy instrument
Other policy instrument
Governance
Source: www.policymix.eu
Land‐Use Zoning
Transportation
Natural Resources
Building
Renewable Energy
Waste and Water
0
1
2High impact
Medium impact
Neglible impact
Climate change policy packagesSource: OECD (2009), “Cities and climate change” Working Paper
Seeking policy complementarities
Horizontal coordination at regional level: example of agencies
Old Paradigm New Paradigm
Place of agency Outside of the system Actor in the system
Role Top-down resource provider
Facilitator, node in the system
Rationale for intervention
Market failures Systems failures, learning failures
Mission Redistributing funds Identifying and reinforcing strengths in the system: a change agent
Instruments Isolated Policy mix
Accountability and control mechanisms
Administrative and financial
Strategic, goal-oriented,additionality
Autonomy Restricted to execution Expanded to strategic decisions
Source: OECD (2009) Governance of Regional Innovation Policy: Variety, Role and Impact of Regional Agencies Addressing Innovation (RIAs), unpublished.
Given different country contexts and shared responsibilities …
Source: Technopolis et al. (2006) Strategic Evaluation on Innovation and the knowledge based economy in relation to the Structural and Cohesion Funds, for the programming period 2007-2013: Synthesis Report. A report to the European Commission, Directorate General Regional Policy, Evaluation and additionality, 23 October 2006.
Evaluation still highly under-developed, but key to getting the strategies right
• Traditional performance indicator benchmarking– Regional Innovation Scoreboard type indicators
– Need to develop metrics for broad innovation
• Lack of policy indicators (intensity , direction)
• Evaluations of individual programmes necessary…
• … but the evaluation of the policy mix is rarely performed
• Evaluations of the actors promoting innovation– Innovation agencies , intermediaries and others
• Need for more Strategic policy intelligence and improved capacities (in-house, outside)
Policies for regional innovation systems
1. From stocks to flows as main focus of policy (of knowledge, human resources, finance,…)
2. From supply-driven to user and society-driven innovation
3. From raising resources to promoting change and resilience: fostering learning capacity of agents in system
4. From best practice to system-specific policies: Variety
5. From standard policy-making towards policy intelligence and room for policy experimentation
6. From regions to « functional regions »: cross-border policies
7. From “one problem-one response” to policy synergies: search foeffectiveness of policy mixes (multi-level, multi-domain)
VERTICAL and HORIZONTAL COORDINATION CHALLENGES
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