Parallel session 3 - 20 September 2016

1. National Innovation System and policy mix:
typology and relationship with
competitiveness and innovation
performances
Virginie Maghe & Michele Cincera
iCite
Solvay Brussels School of Economics and Management
Université Libre de Bruxelles
OECD Blue Sky Forum III - Ghent,
September 19- 21, 2016
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2. Theoretical background
• The Innovation System (IS) concept:
« the network of institutions in the public and private sectors whose activities and
interactions initiate, import, and diffuse new technologies » (Freeman 1987)
• Justification for public intervention = system failures (Woolthuis et al., 2005)
• Evaluating performances before and after policy treatment = strong ceteris paribus
assumption
 Environmental aspect of innovation may be not captured (Arnold, 2004)
• Evaluation of a National Innovation System = Benchmarking/Comparison (Edquist,
2001)
 No general equilibrium
 Typologies based on traditional innovation indicators (performances)
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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3. Data and methodology
• Exhaustive innovation policy database for the 2007-2013 period
 Objectives, instruments, beneficiaries, sectors and budgets
 Quality check: GERD financed by government and GBOARD
 Min. 60% - Max 120%
• 28 EU Member States + Canada, US, Japan, China, South Korea and Australia
• RIO (former Erawatch) and STIP databases, RIM Plus, OECD, Eurostat, and national
sources
• Taxonomy  Classification of all policy measures  Contingency tables
• Data and cluster analysis
• Contribution and novelty of the paper: typology built on policy implementation
characteristics rather than traditional innovation performances (R&D
investments, patents,…).
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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4. Taxonomy
Beneficiaries Instruments Objectives Sectors (NACE rev2)
Business
Education
Research and
technology
Other
organizations
Science,
Technology and
Innovation (STI)
support
STI diffusion
STI framework
Creation of
knowledge and
technology
Transfer of
knowledge and
technology
Absorptive capacity
Agriculture, Mining,
Chemicals, Biotech and
pharmaceuticals, Computer
and electronics, Electrical
equipment, Other
equipment, Automotive,
Ships and boat, Railway,
Aerospace , Energy,
Construction, Transport, ICT,
Financial activities, Scientific
R&D, Education, Human
health and social interests,
Other
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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5. Functional matrices
• Taxonomical classification  Functional matrices.
Example for one single policy measure.
 The measure targets 2 objectives and 3 beneficiaries.
 Its budget represents 15% of the overall budget of all national policy measures
= weight of 15%*1/2*1/3.
• Sum up all the weighted policy measures within the matrices.
 Relative weight of each dimension.
 Weight of crossed dimensions.
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September 19,20 and 21
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6. Functional matrices (cont.)
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September 19,20 and 21
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i.e. 1.63%*1/4 + 5.6%*1/7= 1.2% of policy measures concern applied R&D
objective of HEI research units (universities)

7. Data analysis
• Contingency tables computed for each of the 34 countries
• Do clusters of EU and Non-EU countries exist on specific STI political
issues?
• Factorial analysis of correspondence (FAC) + hierarchical ascendent
classification (HAC) using the FactomineR package of R
• Comparisons with the Global Competitiveness Index ranking and the
EU Summary Innovation Index
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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8. Data analysis: results
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September 19,20 and 21
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#Rank Country Score (1-7) Cluster
3 FI 5.54 5
4 DE 5.51 5
5 US 5.48 1
6 SE 5.48 1
8 NL 5.42 2
9 JP 5.4 1
10 UK 5.37 1
14 CA 5.2 2
15 DK 5.18 5
16 AT 5.15 2
17 BE 5.13 2
21 AUS 5.09 2
22 LU 5.09 1
23 FR 5.05 2
25 KR 5.01 2
28 IE 4.92 2
29 CN 4.84 1
32 EE 4.65 4
35 ES 4.57 2
41 MT 4.5 4
42 PL 4.46 4
46 CZ 4.43 4
48 LT 4.41 3
49 IT 4.41 1
51 PT 4.4 3
52 LV 4.4 4
57 BG 4.31 3
58 CY 4.3 1
62 SI 4.25 1
63 HU 4.25 3
75 HR 4.13 3
76 RO 4.13 1
78 SK 4.1 3
91 EL 3.23 3

Comparison
with the Global
Competitiveness
Index ranking.
3 4 5 6 7 8 9 10
LU LU LU LU LU LU LU LU
SE SE SE SE SE SE SE SE
RO RO RO RO RO RO RO RO
CN CN CN CN CN CN CN CN
IT IT IT IT IT IT IT IT
SI SI SI SI SI SI SI SI
JP JP JP JP JP JP JP JP
UK UK UK UK UK UK UK UK
US US US US US US US US
CY CY CY CY CY CY CY CY
HR HR HR HR HR HR HR HR
BG BG BG BG BG BG BG BG
SK SK SK SK SK SK SK SK
PT PT PT PT PT PT PT PT
EL EL EL EL EL EL EL EL
HU HU HU HU HU HU HU HU
LT LT LT LT LT LT LT LT
PL PL PL PL PL PL PL PL
LV LV LV LV LV LV LV LV
EE EE EE EE EE EE EE EE
CZ CZ CZ CZ CZ CZ CZ CZ
MT MT MT MT MT MT MT MT
AUS AUS AUS AUS AUS AUS AUS AUS
KR KR KR KR KR KR KR KR
ES ES ES ES ES ES ES ES
CA CA CA CA CA CA CA CA
IE IE IE IE IE IE IE IE
NL NL NL NL NL NL NL NL
BE BE BE BE BE BE BE BE
AT AT AT AT AT AT AT AT
FR FR FR FR FR FR FR FR
DE DE DE DE DE DE DE DE
FI FI FI FI FI FI FI FI
DK DK DK DK DK DK DK DK

9. Data analysis : results (cont.)
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September 19,20 and 21
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Cluster 1: LU, SE, US, CY, JP, UK, RO, SI, CN, IT
v.test
Mean in
category
Overall
mean
sd in
category
Overall
sd p.value
HEI research 3.85 0.48 0.34 0.13 0.14 0.00
Science Base 3.40 0.22 0.12 0.11 0.10 0.00
Fundamental
R&D
2.90 0.28 0.16 0.19 0.14 0.00
Non-Profit 2.40 0.13 0.09 0.07 0.07 0.02
Universities 2.05 0.14 0.08 0.12 0.10 0.04
Infrastructure 1.97 0.12 0.08 0.11 0.08 0.05
Research
Competences
-2.16 0.00 0.02 0.00 0.04 0.03
Private
Research
-2.29 0.05 0.09 0.05 0.07 0.02
Start-ups -2.57 0.07 0.15 0.06 0.12 0.01
Downstream
Activities
-2.70 0.07 0.11 0.05 0.06 0.01
SMEs -2.84 0.07 0.14 0.05 0.09 0.00
Non-EU strong innovators and
strongly competitive European
countries targeting research
organizations and science base.
 University research units
 Education and science base
 Fundamental research
 Non-profit organizations
 SMEs
 Downstream R&D
activities
 Start-ups
 Private research
organizations

10. Data analysis: results (cont.)
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Cluster 2: AUS, BE, AT, FR, NL, KR, ES, IE, CA
v.test
Mean in
category
Overall
mean
sd in
category
Overall
sd p.value
Tax Credits 3.86 0.24 0.10 0.14 0.12 0.00
Applied R&D 3.57 0.26 0.18 0.04 0.08 0.00
Large
companies
3.34 0.11 0.06 0.06 0.05 0.00
Downstream
Activities
3.29 0.17 0.11 0.05 0.06 0.00
Private
Research
2.06 0.13 0.09 0.06 0.07 0.04
Universities -2.07 0.02 0.08 0.01 0.10 0.04
Direct Support -2.78 0.26 0.34 0.10 0.11 0.01
Absorption -2.90 0.08 0.17 0.04 0.10 0.00
Cluster 3: HR, BG, SK, PT, EL, HU, LT
v.test
Mean in
category
Overall
mean
sd in
category
Overall
sd p.value
Transfer 3.11 0.16 0.08 0.07 0.07 0.00
SMEs 2.07 0.20 0.14 0.09 0.09 0.04
Collaborations 2.02 0.09 0.05 0.09 0.05 0.04
HEI research -2.21 0.23 0.34 0.05 0.14 0.03
Science Base -2.49 0.03 0.12 0.01 0.10 0.01
Relatively strong non-EU countries
and Western-EU countries with high
scores targeting market-oriented
R&D activities
 Indirect measures
 Applied R&D
 Large companies
 Downstream R&D activities
 Absorptive capacity
 Direct measures
Weakest performers focusing on the
transfer capacities of small
companies
 Knowledge and technology
transfers
 SMEs
 Collaborations
 Education and science base

11. Data analysis: results (cont.)
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September 19,20 and 21
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Cluster 4:LV, PL, CZ, EE, MT
v.test
Mean in
category
Overall
mean
sd in
category
Overall
sd p.value
Students 3.10 0.02 0.00 0.03 0.01 0.00
Research
Competences 3.05 0.07 0.02 0.06 0.04 0.00
Absorption 2.64 0.28 0.17 0.02 0.10 0.01
Energy 2.61 0.09 0.04 0.08 0.05 0.01
Upstream Activities 2.44 0.27 0.15 0.12 0.11 0.01
NGOs 2.41 0.00 0.00 0.00 0.00 0.02
Direct Support 2.11 0.44 0.34 0.03 0.11 0.03
Railway 2.07 0.01 0.00 0.01 0.01 0.04
Applied R&D -2.97 0.08 0.18 0.01 0.08 0.00
Cluster 5: DE, FI DK
v.test
Mean in
category
Overall
mean
sd in
category
Overall
sd p.value
Creation of Firm 5.28 0.18 0.03 0.04 0.05 0.00
Risk-capital 4.87 0.14 0.02 0.06 0.04 0.00
Start-ups 4.17 0.45 0.15 0.16 0.12 0.00
Lifelong learning 2.89 0.00 0.00 0.01 0.00 0.00
Social Interests 2.69 0.03 0.01 0.04 0.02 0.01
Financial services 2.59 0.19 0.05 0.25 0.09 0.01
Computer 2.44 0.19 0.08 0.17 0.08 0.01
Upstream Activities 2.43 0.30 0.15 0.09 0.11 0.02
Environment 2.42 0.02 0.01 0.02 0.01 0.02
Other sectors -2.36 0.09 0.19 0.05 0.08 0.02
Direct support -2.78 0.18 0.34 0.05 0.11 0.01
Eastern EU countries with lower
scores in terms of competitiveness
targeting competences within the IS
 Students
 Research competences
 Absorptive capacity
 Applied R&D
Top performers in terms of
competitiveness focused on
upstream R&D activities
 Creation of firms
 Risk capital
 Start-ups
 Direct support measures

12. Challenges and further research
• Current research
 Use of obtained typology in a stochastic frontier approach (Battese and Coelli
1995)
 Efficiency of public intervention in leveraging Business Expenditure in R&D
financed by the business sector
ln (𝐵𝐸𝑅𝐷𝑏𝑦𝐵𝑈𝑆it) = 𝛽1 + 𝛽2 ln(𝐵𝐸𝑅𝐷𝑏𝑦𝐺𝑂𝑉it) + 𝛽3 ln (𝐺𝑂𝑉𝐸𝑅𝐷it) + 𝛽4 ln(𝐻𝐸𝑅𝐷it)
+ 𝜈it − 𝑢it
BERDbyBUS = BERD financed by the business sector
BERDbyGOV = BERD financed by the government sector
GOVERD = R&D performed by government
HERD = R&D performed by the higher education secor
𝜈it = error term
𝑢it = inefficiency term expressed as
 Effect of BERDbyGOV on BERDbyBUS: additionality or crowding out.
 Effect of policy mix cluster (clus) on the efficiency of public R&D.
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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13. Challenges and further research (cont.)
• Systemic evaluation of innovation policies
Not self-sufficient
Complement traditional diagnosis of innovation performances
• Necessity of extensive innovation policy databases for further
research
 Period of time, beneficiaries, level of implementation (Regional – National),
management institutions and selection criteria
 Annual budgets (provisional or attributed)
 Comparability between countries for benchmarking purpose
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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14. Thank you for your attention

vmaghe@ulb.ac.be
OECD Blue Sky Forum III - Ghent,
September 19,20 and 21
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