Towards a quantification of innovation systems

  Manuel Mira Godinho

 ISEG/UTLisbon

Presentation to the

Tampere 5 June 2008

Part 1 Lecture’s Topic

Part 2 Conceptual Framework

Part 3 Method

Part 4 Cluster Analysis

Part 5 Conclusions

Part 1 / Lecture’s Topic

• Is it possible to measure the development and maturity of a NIS?

• What specific technique can be used for that?

• Can we apply it to both the advanced, the emerging and the developing economies?

1st step Mapping NISs

2nd step With output of step 1: put forward a NIS taxonomy

4 largest EU economies

-0,5

0

0,5

1

1,5

21

2

3

4

5

6

7

8

Germany

United Kingdom

France

Italy

Example of N.I.S. Mapping

Part 2 / Conceptual Framework

Different NIS Concepts

• Freeman (1987) organization of R&D in firms and role of government in Japan

• Nelson (1988) high tech sectors and R&D system

• Lundvall (1988) Inter-firm and user-producer interactions

• (...)

‘NIS’ emerged in the literature as a qualitative concept

Is quantification possible / desirable?

• Possible: YES• Desirable…YES, but!

… caution needed in the analysis

Each NIS Idiosyncratic

How to Quantify NISs?

• Concentrate on NIS “characteritics”

• Derivate quaintifiable “DIMENSIONS”

(D1 to D8)

What a “NIS” is?

“NIS” is a “system”

“whole” more than “the parts”

(Sources of increasing returns … )

- Knowledge spillovers

- Network economies

- Dynamic economies of scale

- Agglomeration economies

NIS comprehends:-Actors (diversity, roles, behaviours, strategies)

-Their interactions (linkages, channels, system density)

-Institutions (with given functions, enable or limit innovation and

diffusion)

NIS purposes -Allocation of resources for innovation and diffusion

-Speed up accumulation and distribution of knowledge

-Provide a favourable regulatory framework

NIS peformances

a) learning, accumulation of capabilities …

b) … innovation, diffusion …

c) …. growth, development, sustainability

‘Innovation’ vs. ‘Diffusion’ in N.I.S.

trade-off or complementarity ?

In some NIS

‘diffusion’ more important than ‘innovation’

(in the limit ‘innovation’ = 0,

but even in this case we can speak of ‘NIS’)

Part 3 - Method

• Decide what are the relevant n Dimensions

• Decide what variables shall be used for each D

• All indicators standardized

• Aggregate 2-5 indicators into each relevant D

• Map D1 to D8 into bi-dimensional space

• 8 Dimensions object of cluster analysis

8 NIS dimensions defined – Market opportunities – Institutional conditions – [intangible and tangible] Accumulation– S&T Opportunities– Economic structure– External communication– Diffusion – Innovation

In order to materialise such 8 NIS dimensions 27 individual indicators selected

Dimension 1 - Market Opportunities-Income per capita-Overall GDP size -Population density

Dimension 2 - Institutional conditions-GINI index (1/G)-Youth of population -Life expectancy-Corruption index

Dimension 3 – (Intangible and tangible) Accumulation-Education expenditures / GDP-Education / Population-GERD / GDP-GERD /Population-GF Investment rate / GDP

Dimension 4 – S&T Opportunities- Researchers / Population-Scientific Papers/ Population-First University Degrees in S&E / Population

Dimension 5 - Economic structure-Value Added in High-Tech & Medium High-Tech Activities (% of MVA)-High-Tech & Medium High-Tech Exports (%)-Sales of home-based top 750 global R&D companies / GDP

Dimension 6 - External communication-(Exports + Imports) / GDP -(Inward + Outward stocks of FDI) / GDP-Bandwidth in international connections (bits per Capita)

Dimension 7 - Diffusion-Personal Computers / Population-Internet Users/ Population-Cellular Phones/ Population-ISO 9001 + ISO 14001 Certificates/ Population

Dimension 8 - Innovation-US Patents/ Population-EU Trademarks / Population

69 Countries in the analysis

Developed + emerging + developing economies

• OECD economies• “Asian tigers” included• All countries > 20 M inhabitants

• Sample: > 87% of the world population

2 time moments

2000-20012005-2006

Part 4 - Cluster analysis

The object of the analysis was a matrix with

69 countries in the sample as the individual ‘cases’

8 NIS dimensions as the ‘variables’ to be analysed

Cluster analysis apllied to 2000/1 and 2005/6• 9 different clustering algorithms• Results compared for stability

2000/1

• 2 Megaclusters• 4 main Clusters

Dendrogram using Average Linkage (Within Group) Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Indonesia 27 Pakistan 46 Nigeria 44 Myanmar 41 Viet Nam 69 Philippines 48 Ukraine 65 Ethiopia 19 Sudan 58 D.R. Congo 15 Algeria 1 Morocco 40 Iran (I.R.) 28 Kenya 32 Bangladesh 5 Tanzania 62 Hungary 25 Slovenia 55 Czech Republic 14 Slovak Republic 54 Latvia 34 Lithuania 35 Poland 49 Estonia 18 Malaysia 37 Malta 38 Greece 23 Portugal 50 Cyprus 13 Argentina 2 South Africa 56 Mexico 39 Thailand 63 Brazil 7 China 11 India 26 Colombia 12 Peru 47 Romania 51 Turkey 64 Venezuela 68 Bulgaria 8 Egypt 17 Chile 10 Russia 52 Finland 20 Sweden 59 Switzerland 60 United Kingdom 66 France 21 Germany 22 United States 67 Korea (Rep.) 33 Singapore 53 Japan 31 Ireland 29 Taiwan, China 61 Netherlands 42 Belgium 6 Luxembourg 36 Australia 3 New Zealand 43 Canada 9 Spain 57 Norway 45 Austria 4 Italy 30 Denmark 16 Hong Kong, China 24

Dendrogram using Average Linkage (Within Group) Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Indonesia 27 Pakistan 46 Nigeria 44 Myanmar 41 Viet Nam 69 Philippines 48 Ukraine 65 Ethiopia 19 Sudan 58 D.R. Congo 15 Algeria 1 Morocco 40 Iran (I.R.) 28 Kenya 32 Bangladesh 5 Tanzania 62 Hungary 25 Slovenia 55 Czech Republic 14 Slovak Republic 54 Latvia 34 Lithuania 35 Poland 49 Estonia 18 Malaysia 37 Malta 38 Greece 23 Portugal 50 Cyprus 13 Argentina 2 South Africa 56 Mexico 39 Thailand 63 Brazil 7 China 11 India 26 Colombia 12 Peru 47 Romania 51 Turkey 64 Venezuela 68 Bulgaria 8 Egypt 17 Chile 10 Russia 52 Finland 20 Sweden 59 Switzerland 60 United Kingdom 66 France 21 Germany 22 United States 67 Korea (Rep.) 33 Singapore 53 Japan 31 Ireland 29 Taiwan, China 61 Netherlands 42 Belgium 6 Luxembourg 36 Australia 3 New Zealand 43 Canada 9 Spain 57 Norway 45 Austria 4 Italy 30 Denmark 16 Hong Kong, China 24

C1

C2

C4

C3

-2

-1

0

1

2D1

D2

D3

D4

D5

D6

D7

D8

Series1

Series2

Series3

Series4

4 Main Clusters 2000

Dendrogram using Average Linkage (Within Group) Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Indonesia 27 Pakistan 46 Nigeria 44 Myanmar 41 Viet Nam 69 Philippines 48 Ukraine 65 Ethiopia 19 Sudan 58 D.R. Congo 15 Algeria 1 Morocco 40 Iran (I.R.) 28 Kenya 32 Bangladesh 5 Tanzania 62 Hungary 25 Slovenia 55 Czech Republic 14 Slovak Republic 54 Latvia 34 Lithuania 35 Poland 49 Estonia 18 Malaysia 37 Malta 38 Greece 23 Portugal 50 Cyprus 13 Argentina 2 South Africa 56 Mexico 39 Thailand 63 Brazil 7 China 11 India 26 Colombia 12 Peru 47 Romania 51 Turkey 64 Venezuela 68 Bulgaria 8 Egypt 17 Chile 10 Russia 52 Finland 20 Sweden 59 Switzerland 60 United Kingdom 66 France 21 Germany 22 United States 67 Korea (Rep.) 33 Singapore 53 Japan 31 Ireland 29 Taiwan, China 61 Netherlands 42 Belgium 6 Luxembourg 36 Australia 3 New Zealand 43 Canada 9 Spain 57 Norway 45 Austria 4 Italy 30 Denmark 16 Hong Kong, China 24

<C1Sudan Ethiopia D.R. Congo Kenya Nigeria Myanmar Pakistan Indonesia

Peru Colombia Bulgaria Egypt Turkey India Romania Ukraine Venezuela Argentina Russia

Iran (I.R.) Tanzania Bangladesh Algeria Morocco Viet Nam Philippines Ukraine

Latvia Lithuania Poland Estonia Slovak Republic Slovenia Hungary Czech Republic

South Africa Thailand Chile Brazil China Latvia Mexico Greece Cyprus Malaysia Portugal MaltaC2A C2>

Dendrogram using Average Linkage (Within Group) Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Indonesia 27 Pakistan 46 Nigeria 44 Myanmar 41 Viet Nam 69 Philippines 48 Ukraine 65 Ethiopia 19 Sudan 58 D.R. Congo 15 Algeria 1 Morocco 40 Iran (I.R.) 28 Kenya 32 Bangladesh 5 Tanzania 62 Hungary 25 Slovenia 55 Czech Republic 14 Slovak Republic 54 Latvia 34 Lithuania 35 Poland 49 Estonia 18 Malaysia 37 Malta 38 Greece 23 Portugal 50 Cyprus 13 Argentina 2 South Africa 56 Mexico 39 Thailand 63 Brazil 7 China 11 India 26 Colombia 12 Peru 47 Romania 51 Turkey 64 Venezuela 68 Bulgaria 8 Egypt 17 Chile 10 Russia 52 Finland 20 Sweden 59 Switzerland 60 United Kingdom 66 France 21 Germany 22 United States 67 Korea (Rep.) 33 Singapore 53 Japan 31 Ireland 29 Taiwan, China 61 Netherlands 42 Belgium 6 Luxembourg 36 Australia 3 New Zealand 43 Canada 9 Spain 57 Norway 45 Austria 4 Italy 30 Denmark 16 Hong Kong, China 24

C4

C3

Cluster 1 2000 Cluster 2 2000 Cluster 3 2000 Cluster 4 2000 Sudan Ethiopia D.R. Congo Kenya Nigeria Myanmar Pakistan Indonesia Iran (I.R.) Tanzania Bangladesh Algeria Morocco Viet Nam Philippines Ukraine

Peru Colombia Bulgaria Egypt Turkey India Romania Ukraine Venezuela Argentina Russia South Africa Thailand Chile Brazil China

Latvia Mexico Lithuania Greece Cyprus Poland Estonia Malaysia Portugal Slovak Republic Malta Slovenia Hungary Czech Republic

New Zealand Italy Australia Spain Canada Austria Belgium Luxembourg Taiwan, China Ireland Hong Kong, China Denmark Netherlands

Korea (Rep.) Norway France Singapore United States Germany Japan Finland United Kingdom Switzerland Sweden

2000: Cluster 2 and Subgroup 2A

-0,9

-0,4

0,1

0,6D1

D2

D3

D4

D5

D6

D7

D8

Series1

Series2Cluster 2 Group 2A

2005/6

Again• 2 Megaclusters• 4 main Clusters

2005/6

But… Catching Up is Visible . 5 of the 8 in previous group 2A

move now to Cluster 3 . In 3 (out of 9) clustering

simulations the number of countries moving to C3 is 5+11

Dendrogram using Average Linkage (Within Group) Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Czech R. 14 Hungary 25 Slovak R. 54 Slovenia 55 Spain 57 Austria 4 Italy 30 Estonia 18 Australia 3 New Zealand 43 Canada 9 Norway 45 Finland 20 Hong Kong 24 Sweden 59 Switzerland 60 Germany 22 United Kingdom 66 Korea (R. of) 33 United States 67 France 21 Taiwan 61 Japan 31 Singapore 53 Belgium 6 Ireland 29 Netherlands 42 Denmark 16 Luxembourg 36 Ethiopia 19 Sudan 58 Bangladesh 5 Colombia 12 Venezuela 68 Peru 47 Algeria 1 Kenya 32 Morocco 40 Iran (I.R.) 28 Myanmar 41 Nigeria 44 D.R. Congo 15 Egypt 17 Pakistan 46 Indonesia 27 Viet Nam 69 Philippines 48 Tanzania 62 Latvia 34 Lithuania 35 Bulgaria 8 Greece 23 Portugal 50 Poland 49 Chile 10 Romania 51 Cyprus 13 Malaysia 37 Malta 38 Mexico 39 Turkey 64 Thailand 63 Brazil 7 South Africa 56 Ukraine 65 China 11 India 26 Argentina 2 Russia 52

C3

C4

C1

C2 (n=21)

6/9

Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Czech R. 14 Hungary 25 Slovak R. 54 Slovenia 55 Spain 57 Austria 4 Italy 30 Estonia 18 Malaysia 37 Malta 38 Chile 10 Romania 51 Cyprus 13 Greece 23 Portugal 50 Poland 49 Latvia 34 Lithuania 35 Bulgaria 8 Luxembourg 36 Singapore 53 Hong Kong 24 Germany 22 United Kingdom 66 Taiwan 61 Korea (R. of) 33 United States 67 France 21 Japan 31 Australia 3 New Zealand 43 Canada 9 Norway 45 Belgium 6 Ireland 29 Netherlands 42 Denmark 16 Sweden 59 Switzerland 60 Finland 20 China 11 India 26 Argentina 2 Philippines 48 Brazil 7 South Africa 56 Mexico 39 Turkey 64 Thailand 63 Russia 52 Ukraine 65 Myanmar 41 Nigeria 44 D.R. Congo 15 Egypt 17 Pakistan 46 Indonesia 27 Viet Nam 69 Tanzania 62 Ethiopia 19 Sudan 58 Bangladesh 5 Colombia 12 Venezuela 68 Peru 47 Algeria 1 Kenya 32 Morocco 40 Iran (I.R.) 28

C3

C4

C2 (n=11)

C1

3/9

Cluster 1 2006 Cluster 2 2006 Cluster 3 2006 Cluster 4 2006 Philippines Viet Nam Iran (I.R.) Morocco Venezuela Tanzania Colombia Indonesia Algeria Egypt Pakistan Peru Kenya Nigeria Bangladesh Myanmar Sudan Ethiopia D.R. Congo

Malta Portugal Malaysia Poland Lithuania Latvia Cyprus Greece Bulgaria China Mexico Russia Chile Romania Thailand Turkey Ukraine South Africa Brazil

Hong Kong Finland Norway Austria Canada Spain Italy Australia Slovenia New Zealand Czech R. Estonia Hungary Slovak R.

Singapore Sweden Luxembourg Denmark Switzerland Netherlands United Kingdom Japan Taiwan United States Germany Belgium Korea (R. of) France Ireland

X

Y

-1,8

-0,8

0,2

1,2D1

D2

D3

D4

D5

D6

D7

D8

Series1

Series2

Series3

Series4

4 Main Clusters 2006

-0,75-0,5

-0,250

0,25D1

D2

D3

D4

D5

D6

D7

D8

Series1

Series2

Series3

C2

C2Y

C2X

China Mexico Russia Thailand Turkey Ukraine South Africa Brazil India Argentina

Malta Portugal Malaysia Poland Lithuania

Latvia Cyprus Greece Bulgaria Chile Romania

Overall Comparison of NIS Evolution

• Possibility of establishing a ranking

• Rank measure ≡ NIS map area

Global 2000 Global 2006 Sweden Switzerland United Kingdom Finland Netherlands Japan Denmark Hong Kong, China Germany United States Singapore France Norway Ireland Taiwan Korea (Rep.) Luxembourg Belgium Austria Canada Spain Australia Czech Republic Italy New Zealand Hungary Slovenia Malta Portugal Slovak Republic Malaysia Estonia Poland Cyprus Greece Lithuania Latvia Mexico China Brazil Chile Thailand Argentina Russia South Africa

1,21 1,13 1 0,96 0,95 0,95 0,94 0,86 0,81 0,78 0,75 0,74 0,71 0,67 0,65 0,64 0,61 0,58 0,56 0,53 0,46 0,4 0,36 0,34 0,25 0,21 0,2 0,16 0,06 0,06 0,04 -0,08 -0,13 -0,15 -0,16 -0,2 -0,27 -0,27 -0,29 -0,3 -0,32 -0,34 -0,4 -0,4 -0,4

Singapore Sweden Luxembourg Denmark Switzerland Hong Kong Netherlands Finland United Kingdom Japan Taiwan Norway United States Germany Belgium Korea (R. of) France Ireland Austria Canada Spain Italy Australia Slovenia New Zealand Czech R. Estonia Hungary Malta Slovak R. Portugal Malaysia Poland Lithuania Latvia Cyprus Greece Bulgaria China Mexico Russia Chile Romania Thailand Turkey

1,03 1 0,98 0,94 0,93 0,84 0,82 0,79 0,78 0,77 0,76 0,65 0,65 0,64 0,61 0,57 0,54 0,54 0,46 0,45 0,39 0,37 0,35 0,31 0,3 0,26 0,25 0,22 0,12 0,11 0,02 -0,02 -0,07 -0,08 -0,09 -0,1 -0,14 -0,21 -0,24 -0,26 -0,29 -0,31 -0,31 -0,32 -0,35

Part 5 > Conclusions

Methodological aspects

Quantification possible, but...

Need of appropriate indicatorse.g. on networking, on innovation

in low and medium tech sectors, even detailed R&D data lacking

Further conclusions: policy application

Responds to policy demand for guidance• Comparability/benchmarking• Summary measures

Scoreboards have been produced• But criticized: loss of information, simplification