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