European Innovation
Scoreboard 2002
C O R D I S f o c u s
S u p p l e m e n t
Issue no 19 - December 2002
www.cordis.lu/trendchart
PUBLISHED BY THE EUROPEAN COMMISSION • INNOVATION
This document originates from the European Commission’s “European Trend Chart on Innovation”
(Enterprise Directorate-General). Copyright of the document belongs to the European Commission.
Neither the European Commission, nor any person acting on its behalf, may be held responsible for the
use to which information contained in this document may be put, or for any errors which, despite
careful preparation and checking, may appear.
This CORDIS focus supplement includes the Commission Staff Working Paper “2002 European
Innovation Scoreboard”, SEC (2002) 1349, and a technical paper on “Indicators and Definitions”. Both
documents and more technical papers are available from: www.cordis.lu/trendchart
Executive Summary
3
1 Introduction
5
2 Main findings for EU Member States and
the Associate countries
7
2.1
Leading EU Member States
7
2.2
Current trends
8
2.3
Relative strengths and weaknesses
8
2.4
Convergence and divergence in EU innovation performance
9
2.5
Main changes since the 2001 EIS
10
2.6
The Associate countries
10
3 2002 EIS results for the EU regions
11
3.1.
Leading regions
11
3.2
A link between innovative and economic performance
12
4 2002 EIS results for the EU Candidate countries
14
4.1
Leading Candidate countries
14
4.2
Current trends in Candidate countries
14
Annexes
december 2002
Preface
european innovation scoreboard 2002
Table of Contents
16
Main data tables
17
Technical Annex
24
Technical Paper: Indicators and Definitions
25
1
december 2002
european innovation scoreboard 2002
Preface
The European Trend Chart on
Innovation
Innovation is a priority of all Member States and
of the European Commission. Throughout Europe, hundreds of policy measures and support
schemes aimed at innovation have been implemented or are under preparation. The diversity
of these measures and schemes reflects the
diversity of the framework conditions, cultural
preferences and political priorities in the Member States. The ‘First Action Plan for Innovation
in Europe’, launched by the European Commission in 1996, provided for the first time a common analytical and political framework for
innovation policy in Europe.
Building upon the Action Plan, the Trend Chart
on Innovation in Europe is a practical tool for
innovation policy makers and scheme managers
in Europe. Run by the European Commission
(Innovation Directorate of DG Enterprise), it
pursues the collection, regular updating and
analysis of information on innovation policies at
national and Community level, with a focus on
innovation finance; setting up and developing
innovative businesses; the protection of intellectual property rights; and the transfer of technology between research and industry.
The Trend Chart serves the “open policy coordination approach” laid down by the Lisbon
Council in March 2000. It delivers summarised
and concise information and statistics on innovation policies, performances and trends in the
European Union. It is also a European forum for
benchmarking and the exchange of good practices in the area of innovation policy.
2
The Trend Chart products
The Trend Chart on Innovation has been running since January 2000. It tracks innovation policy
developments in all EU Member States, plus
Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Iceland, Israel, Latvia, Liechtenstein, Lithuania, Norway, Poland, Romania, Slovak Republic
and Slovenia. The Trend Chart website
(www.cordis.lu/trendchart) provides access to
the following services and publications:
•
the European Innovation Scoreboard and
other statistical reports;
•
regular country reports for all countries
covered;
•
a database of policy measures across
Europe;
•
a “who’s who?” of agencies and
government departments involved in
innovation;
•
regular trend reports covering each of the
four main themes;
•
benchmarking reports from the Trend Chart
workshops;
•
a news service and thematic papers;
•
the annual reports of the Trend Chart.
The present report was prepared under a service contract with MERIT (Anthony Arundel and
Hugo Hollanders).
Contact: Peter Löwe: [email protected]
Weak innovation performance of the EU as a whole
The 2002 EIS confirms that the innovation performance of the EU is still low compared to its main
global competitors. Japan leads the EU in eight of the ten indicators for which comparable data are
available and the US leads for seven. For new S&E graduates and public R&D expenditures, the
EU and US averages are very close. The only significant EU lead within the triad is its lead over
Japan in home Internet access.
Encouraging trend results
Looking at trends, the situation is more encouraging. For five of eight comparable trend indicators
the EU trend has been improving faster than in the US. The US trend leads the EU for high
technology EPO patents and for business R&D, while there is an equal decline in both the US and
the EU for public R&D. Compared to Japan, the EU leads in all seven available trend indicators.
These overall positive trend results suggest that the EU may be catching up with its main competitors.
december 2002
Background
Since 2000, the European Commission has published the European Innovation Scoreboard
(EIS) as an instrument for the annual follow-up of the Lisbon strategy. This edition includes, for
the first time, data from Associate countries1, Candidate countries and from the EU regions, in
addition to the data on the EU Member States, the US and Japan. All data have been updated
except those for the four indicators based on the Community Innovation Survey (CIS). This
edition therefore contains data for 13 out of 17 indicators. Subject to the availability of data from
the latest CIS, the 2003 EIS is expected to offer again a summary innovation index of country
trends, similar to the one presented in 2001.
european innovation scoreboard 2002
Executive Summary
Persisting gaps in business R&D and high-tech patenting
However, the two major weaknesses diagnosed in 2001 continue to exist. In EPO high-tech
patents, EU growth has been substantial (up 55%) but US high-tech patenting in Europe is
growing still faster (up 67.8%). In business R&D, the lower rate of increase in the EU than in the
US is of particular concern, since this is a main indicator of future technology-based innovations.
World innovation leaders come from Europe
Looking at individual Member States, the 2002 EIS confirms that the world’s leading countries for
many innovation indicators are found within the EU. The leading innovative countries in the EU are
the smaller northern economies, including Finland, Sweden, Denmark and The Netherlands. The
UK is the most innovative of the larger economies. For seven of the ten comparable indicators,
the EU leaders are ahead of both the US and Japan. Ireland, France, Finland, the UK and Sweden
lead in new S&E graduates; Finland, Sweden and The Netherlands in public R&D; Sweden and
Finland in business R&D; Finland, Sweden and The Netherlands in high-technology EPO patents;
Luxembourg, Spain and The Netherlands in new capital raised; The Netherlands, Sweden and
Denmark in home Internet access; and Sweden, the UK and The Netherlands in ICT expenditures.
1
To simplify the terminology in this document, the term “Associate countries”
designates countries that are associated to the 6th RTD Framework Programme, in
addition to the Candidate countries.
continued ➜
3
december 2002
european innovation scoreboard 2002
Southern Europe catching up
Some of the southern European countries are showing rapid improvements. In Portugal and in
Greece both business and public R&D are improving much more rapidly than the EU average.
Spain is substantially above the average EU trend for employment in high technology services and
high technology patents. Italy does not exhibit major improvements.
The Associate countries
The 2002 EIS provides comparable data for Switzerland, Iceland and Norway. Switzerland and
Iceland are above the EU mean for 10 and 11 indicators respectively, comparable to the EU
innovative leaders. However, the trend results for Switzerland are behind the EU average for six of
eight indicators, suggesting that Switzerland may be losing its innovative advantage. The very good
results for Iceland for several indicators of business innovation (business R&D, patents, and
finance) are largely due to its proactive cluster and FDI policy in biotechnology. Norway is a middle
range country that does very well in several indicators for human resources, but lags behind the EU
average for business innovation. The trend results for Norway are behind the EU average for eight
of 11 indicators.
The Candidate countries
The Candidate countries perform favourably compared to the EU for tertiary education (with
Bulgaria, Cyprus, Estonia and Lithuania equal to or above the EU mean), employment in high-tech
manufacturing (with the Czech Republic, Hungary, Poland and Slovenia close to or above the EU
mean), ICT expenditures (with the Czech Republic, Estonia, Hungary and Slovakia above the EU
mean), and the stock of inward FDI (with the Czech Republic, Estonia, Hungary and Malta above
the EU mean). The mean trend for the Candidate countries exceeds the EU mean trend for five of
the ten comparable indicators, in particular for market and investment indicators.
Innovative regions in the EU
At the regional level, the scoreboard introduces seven innovation indicators. These indicators
provide coverage of human resources, employment in high-technology sectors, and the creation
of new knowledge through R&D and patents. Due to the limited availability of other regional data
these indicators are better at identifying regions with a strong research and innovation performance than regions with future potential, or regions that require diffusion-oriented policies. The
regional scoreboard indicators are, however, a first start at underpinning regional policy with
comparable data.
The available regional data suggest a positive relation between a region’s innovative performance
and its economic performance. The top ten leading European regions are distributed across seven
countries: Stockholm (S), Uusimaa (Suuralue) (FIN), Noord-Brabant (NL), Eastern region (UK),
Pohjois-Suomi (FIN), Ile-de-France (F), Bayern (D), South-East region (UK) Comunidad de Madrid
(E) and Baden-Württemberg (D).
4
The EIS contains 17 main indicators, selected to summarise the main drivers and outputs of innovations. These indicators are divided into four groups3 :
1) Human resources for innovation (5 indicators);
2) The creation of new knowledge (3 indicators of which one is divided into EPO and USPTO
patents);
3) The transmission and application of knowledge (3 indicators);
4) Innovation finance, outputs and markets (6 indicators).
The EIS complements the Enterprise Policy Scoreboard4 and other benchmarking exercises of the
European Commission. It mainly uses Eurostat data, or private data of sufficient reliability if official data
is not available. Six indicators are drawn from the European Commission’s Structural indicators5 .
The European Innovation Scoreboard (EIS)
was developed at the request of the Lisbon
European Council in 20002 . It focuses on
high-tech innovation and provides indicators for tracking the EU’s progress towards
the Lisbon goal of becoming the most competitive and dynamic knowledge-based
economy in the world within the next decade.
The EIS is one of the three main instruments of the European Trend Chart on Innovation8 . The two
others are the comprehensive database of innovation policies in Europe and the benchmarking
workshops for sharing best practices in innovation policy. In combination, these three instruments
provide the tools for “intelligent” policy benchmarking. The EIS points at strengths and weaknesses
of the national innovation performances at the aggregate level; the database, together with country
reports, provides comparable information on national policy measures; and the workshops offer a
learning environment to draw lessons on specific issues of common interest. This enables Member
States to set specific targets for each indicator, taking into account their specific “innovation paths”.
The 2001 EIS report proposed the development of regional indicators, indicators for the Candidate
countries, and supplementary innovation indicators to cover emerging areas of importance to innovation policy. The 2002 EIS has met all of these goals. It includes new data for:
■ Three countries associated with the Sixth EU R&D Framework Programme (Iceland, Norway
and Switzerland);
december 2002
All indicators have been updated based on data availability as of September 15, 20026 . Four
indicators could not be updated due to delays in the execution of the third Community Innovation
Survey.7 As a result, the 2002 EIS does not provide trend results for these indicators and it does not
contain a summary innovation index similar to the one offered in 2001. Subject to the availability of
new CIS data, the 2003 EIS is expected to offer again an updated composite innovation index and
a comparison between the index and average trends for each country, which was one of the most
interesting features of the 2001 EIS.
european innovation scoreboard 2002
1 Introduction
2
A first provisional EIS was published in September
2000: COM(2000) 567. The first full version of the
EIS was published in October 2001: SEC(2001)
1414.
3
Table A in the Annex provides a brief definition and
the source of each indicator. Full definitions of each
indicator are available in Technical Paper No 4:
Indicators and Definitions and in Technical Paper No
6: Methodological Report.
4
SEC(2002) 1213
5
These are indicators 1.1, 1.3, 2.1, 2.2, 4.4 and 4.5.
The EIS R&D indicators 2.1 and 2.2 are
disaggregated according to sector of spending and
do not reflect the recent changes in definition of the
Structural indicators made in October 2002:
COM(2002) 551. The Structural indicators on R&D
are now defined as disaggregated according to
source of finance. For EIS indicator 1.1, Science and
engineering graduates, the name differs from the
one of the corresponding Structural indicators:
Science and technology graduates. In the 2003 EIS
these redefinitions and changes in name will be
taken into account.
6
Tables C and F in the annex show the most recent
years available, in general 2000 or 2001. Reduced
accuracy can occur in those exceptional cases where
comparisons are made between data from different
years (lacking data points for a particular indicator
or country).
7
These are indicators 3.1, 3.2, 3.3 and 4.3.
8
For more information on Trend Chart, visit
www.cordis.lu/trendchart.
■ The EU regions, at the NUTS 1 level for Belgium, Germany and the UK, and the NUTS 2 level
for Austria, Finland, France, Greece, Ireland, Italy, The Netherlands, Portugal, Spain and
Sweden;
■ The EU Candidate countries (Bulgaria, Cyprus, the Czech Republic, Estonia, Hungary, Latvia,
Lithuania, Malta, Poland, Romania, Slovakia, Slovenia and Turkey).
5
december 2002
european innovation scoreboard 2002
EIS focus on “high” technology innovation
The EIS focuses on high technology innovation. For example, the patent, services employment,
venture capital, and value-added indicators are limited to high technology. The indicator for
manufacturing employment also includes “medium-high” technology sectors such as automobiles. The reason for this focus on high and medium-high technology sectors is that the EIS tries
to capture leading-edge generic innovations, such as in ICT or biotechnology that can drive
further innovation throughout an economy. The diffusion of these innovations across many
different sectors can lead to additional innovation. The latter process is captured by the EIS
through two diffusion indicators (3.2 and 3.3) obtained from the Community Innovation Survey
(CIS), plus the indicator for lifelong learning.
However, “medium-low” and “low” technology sectors such as petroleum refining, pulp and
paper, textiles, or food and beverages are highly innovative, drawing on many fields of knowledge. These sectors often innovate through the purchase of advanced manufacturing technology or by developing sophisticated production and delivery systems. The diffusion indicators in
the EIS are inadequate for fully capturing these activities. If the EIS focus is not borne in mind,
this may lead to biased policy conclusions, since several low technology sectors, such as food
and beverages, are of far greater economic significance than high technology sectors such as
aerospace or pharmaceuticals.
In order to address these limitations of the EIS, it is planned to complement the 2003 scoreboard by statistical analysis focusing on innovation among “medium-low” and “low” technology
sectors of economic significance in Europe.
The EIS is complemented by six technical papers:
1) Technical Paper No 1: Member States and Associate Countries
Detailed results for current and trend data, innovation leaders, relative strengths and
weaknesses per country, convergence and divergence analysis between Member States and
different groups of Member States, and country pages with trend diagrams and main policy
changes.
2) Technical Paper No 2: Candidate Countries
Detailed results for current and trend data, innovation leaders, relative strengths and
weaknesses per country, and country pages with both current and trend graphs.
3) Technical Paper No 3: EU Regions
Detailed results for currently available data, leading regions, two tentative composite
innovation indicators, indicator graphs, and preliminary steps towards the 2003 regional
scoreboard.
4) Technical Paper No 4: Indicators and Definitions
Full definitions and graphs for all indicators.
5) Technical Paper No 5: Thematic Scoreboard “Lifelong Learning for Innovation”
Prototype of a complementary scoreboard on “Lifelong Learning for Innovation”.
6) Technical Paper No 6: Methodological Report
Overview of five different methods for constructing composite indices, and review of the
similarities and differences between the EIS and other European Commission scoreboards.
All technical papers are available from the Trend Chart website (www.cordis.lu/trendchart).
6
2.1 Leading EU Member States
Looking at the EU as a whole, the EU leads for three of the 10 indicators for which US data are
available (S&E graduates, public R&D and new capital raised). Excluding patenting in the US, where
the US is expected to perform better than Europe, the largest US lead over the EU is in the share of
manufacturing value-added from high technology (155% higher than the EU), followed by high
technology EPO patents (78% higher), and the share of the working-age population with some form
of tertiary education (72% higher).
The 2002 EIS results for Member States,
US and Japan, and the three Associate countries are given in Tables B and D of the
Annex. Full details are available in Technical
Paper No 1: Member States and Associate
Countries.
december 2002
Table 1 gives, for each indicator, the EU mean, the three EU leaders and the results for the US and
Japan where available. As in 2001, the smaller European countries dominate the leading slots for the
14 indicators. Sweden appears 11 times (11 in 2001), Finland 9 times (7 in 2001), The Netherlands five times (6 in 2001), Denmark four times (4 in 2001) and Ireland two times (2 in 2001).
Of the larger EU economies, the UK leads with four slots (5 in 2001), followed by Germany with
three (3 in 2001). France appears once and Italy not at all. These results confirm the main findings
from the 2001 scoreboard: the innovative leaders in the EU are concentrated in the Nordic countries plus The Netherlands, while the larger economies, with the exception of the UK, perform only
near the average or are lagging behind.
Table 1. Innovation leaders among the EU Member States
No
Indicator1
EU Mean2
3
EU performance leaders
US
JP
1.1
S&E graduates / 20–29 years
10.3
23.2 (IRL)
18.7 (F)
17.8 (FIN)
10.2
12.5
1.2
Population with tertiary education
21.2
32.5 (FIN)
29.7 (S)
28.6 (UK)
36.5
29.9
1.3
Participation in lifelong learning
8.5
21.7 (UK)
21.6 (S)
20.8 (DK)
—
—
1.4
Employment in med/high-tech manufacturing
7.6
11.2 (D)
1.5
Employment in high-tech services
3.6
5.1 (S)
7.9 (S)
7.4 (FIN)
—
—
4.9 (DK)
4.8 (UK)
—
—
2.1
Public R&D / GDP
0.67
0.98 (FIN)
0.94 (S)
0.88 (NL)
0.66
0.87
2.2
Business R&D / GDP
1.28
2.84 (S)
2.68 (FIN)
1.80 (D)
2.04
2.11
95.1 (S)
57.9 (NL)
49.5
36.6
91.9
80.0
2.3.1 High-tech EPO patents / population
27.8
137.6 (FIN)
2.3.2 High-tech USPTO patents / population
12.4
47.3 (S)
41.6 (FIN)
22.7 (DK)
4.1
High-tech venture capital / GDP
0.24
0.57 (FIN)
0.46 (DK)
0.44 (B)
4.2
New capital raised / GDP
1.7
10.8 (L)
4.4
Home Internet access
4.5
ICT expenditure / GDP
4.6
High-tech manufacturing value added
37.7
6.93
10.1
7.9 (E)
6.0 (NL)
european innovation scoreboard 2002
2 Main findings for EU Member States
and Associate countries
—
—
0.8
0.0
63.8 (NL)
60.7 (S)
58.6 (DK)
46.7
34.0
9.85 (S)
8.62 (UK)
8.30 (NL)
8.22
8.98
25.4 (IRL)
19.3 (FIN)
15.3 (S)
25.8
13.8
1: The four CIS indicators could not be updated and are therefore not included in this table.
2: The EU mean sums the numerator and denominator across all EU countries.
3: Unweighted average. Available data are insufficient for calculating a weighted mean.
For seven of the ten comparable indicators, the EU leaders are ahead of both the US and Japan.
Ireland, France and Finland lead in S&E graduates, Finland, Sweden and The Netherlands in public
R&D, Sweden and Finland in business R&D, Finland, Sweden and The Netherlands in high-technology EPO patents, Luxembourg, Spain and The Netherlands in new capital raised, The Netherlands,
Sweden and Denmark in home Internet access, and Sweden, the UK and The Netherlands in ICT
expenditures. The US lead in USPTO patents remains valid even for the leading EU countries, and the
US leads all EU countries for high-tech value added in manufacturing and for tertiary education9 .
9
This comparison is between the EU leading countries with the entire United States. A comparison of
EU Member States with highly innovative American
States, such as California or Massachusetts, could be
instructive.
7
european innovation scoreboard 2002
2.2 Current trends
Table 2 provides average trend results for twelve indicators for which reliable trend data are available,
for eight indicators for the US, and for seven indicators for Japan10 . Table 2 also gives the three EU
leaders for each trend. The trends for ten of the twelve indicators have improved for the entire EU.
The largest increases are for home Internet access (plus 271%) and for high technology patents at
both the EPO (plus 97%) and at the USPTO (plus 44%). There has been a slightly negative trend for
public R&D and for employment in medium/high technology manufacturing sectors (due to a longterm increase in service sector employment).
Table 2. Trends in innovation performance
No
Indicator
1.1
S&E graduates / 20 – 29 years
13.7
82.4 (P)
50.6 (S)
40.0 (I)
-6.1
—
1.2
Population with tertiary education
17.9
41.5 (A)
20.5 (FIN)
19.3 (E)
4.6
-1.8
december 2002
EU Mean
EU trend leaders
53.1 (B)
35.5 (EL)
25.1 (NL)
—
—
2.7 (D)
—
—
24.8 (UK)
—
—
8.8 (B)
-2.0
7.0
32.8 (P)
7.0
3.8
190.4 (IRL)
151.9
57.1
77.1 (DK)
1.3
Participation in lifelong learning
21.4
1.4
Employment in med/high-tech manufacturing
-2.1
1.5
Employment in high-tech services
18.3
38.5 (E)
25.1 (NL)
2.1
Public R&D / GDP
-2.0
34.0 (EL)
25.6 (P)
2.2
Business R&D / GDP
5.4
46.0 (EL)
35.4 (FIN)
2.3.1 High-tech EPO patents / pop
97.2
2.3.2 High-tech USPTO patents / pop
7.4 (DK)
327.8 (L)
305.6 (P)
43.9
116.4 (E)
95.7 (S)
605.4 (P)
561.1 (IRL)
Home Internet access
4.5
ICT expenditure / GDP
14.8
20.9 (EL)
4.6
High-tech manufacturing value added
23.2
54.4 (FIN)
US
4.4 (FIN)
271.4
4.4
JP
41.9
21.6
411.5 (I)
55.7
125.9
18.0 (A)
18.0 (L)
5.2
14.4
36.1 (F)
35.4 (DK)
—
—
The trend in the EU has been improving faster than in the US for five of the eight comparable
indicators and for all seven comparable indicators for Japan. The US trend leads the EU for high
technology EPO patents and for business R&D, while there is an equal decline in both the US and the
EU for public R&D. These generally positive results suggest that the EU may be catching up with its
main competitors, although the lower rate of increase in the EU than in the US for business R&D is
of concern, since this is a main indicator of future technology-based innovations.
10 Trends are calculated as the percentage change in
each indicator between the last year for which data
are available and the average over the previous
three years, after a one-year lag. For example, when
the most recent data are for 2001, the trend is
based on the percentage change between 2001
and the average for 1997 to 1999 inclusive. The
results for 2000 are excluded in order to provide a
one-year lag. There are several exceptions to this
rule due to a lack of adequate data. Technical Paper
No 1: Member States and Associate Countries,
provides the specific years used to calculate the
trends for each indicator per country. Trend data
cannot be calculated for the four CIS indicators and
for indicator 4.2 (New capital raised). For indicator
4.1 (venture capital) trend data are not reported as
these are considered less reliable because of the
highly volatile financial markets in the past year.
11 Poor trend results for home Internet access in
countries with high current access levels are ignored, since these countries may already be close to
saturation and unable to increase access by very
much. Patent trends based on very low absolute
patent counts are also not included in Table 3, since
these trends are highly volatile from year to year.
8
(% change)
The pattern of trend leaders in Table 2 differs from the one of performance leaders in Table 1.While
the performance leaders are dominated by the Nordic countries, the trend results are much more
diversified, with all 15 EU Member States being a trend leader for at least one indicator. Of note, two
of the EU’s least innovative countries, Portugal and Greece, are trend leaders for five and four
indicators respectively, along with Finland. Spain is also leading for three indicators, along with
Denmark. All other countries are leading for two indicators, except for Germany, France and the UK,
which are only leading for one indicator each.
2.3 Relative strengths and weaknesses
Table 3 summarises the relative strengths and weaknesses of each Member State. The results are
limited to a maximum of three current indicator values or trends that are at least 20% (above or
below) the EU mean11 . In some cases a country is weak in all relevant indicators, such as for
education, R&D, or patenting. These are treated as a single indicator.
All countries have some strengths, although these are limited to trends for the less innovative
countries of Greece, Italy and Portugal. The strengths of the innovative leaders are dominated by
current conditions, except for Finland which also has a strong trend for business R&D. The positive
trend for home Internet access is a strength for six countries (Austria, Spain, France, Ireland, Italy
and Portugal), illustrating the strong convergence for this indicator (see section 2.4 below).
Of concern, several countries suffer from weak education indicators. Even two of the innovative
leaders, Denmark and The Netherlands, have relative weaknesses in either the trend or the current
level of S&E graduates. Germany, Italy and Portugal are weak in several of the education indicators.
Table 3. Relative strengths and weaknesses of Member States
Major relative weaknesses
Austria
Current home Internet access (4.4);
trend for education (1.1 and 1.2)
Current patents (US and EPO),
current innovation finance (4.1 and 4.2)
Belgium
Current innovation finance (4.1 and 4.2), tertiary
education (1.2); trend for lifelong learning (1.3)
Trend for home Internet access (4.4) and EPO patents.
Denmark
Current lifelong learning (1.3),
US patents, venture capital (4.1)
Current new capital raised (4.2),
trend for new S&E graduates (1.1).
Germany
Current patenting (US and EPO), business R&D (2.2),
medium/high-tech manufacturing employment (1.5)
Current innovation finance (4.1 and 4.2), manufacturing
high-tech value-added (4.6); trend for home Internet
access (4.4), education (1.1, 1.2, 1.3)
Spain
Current new capital raised (4.2); trends for US
patents, home Internet access (4.4)
Current patents (US and EPO) and R&D (2.1 and 2.2)
Greece
Trend for R&D (2.1 and 2.2)
Trends for patents (US and EPO) and home Internet access (4.4)
France
Current S&E graduates (1.1); trend for home Internet
access (4.4)
Current lifelong learning (1.3) and new capital raised (4.2);
trend for lifelong learning
Finland
Current patents (US and EPO), venture capital (4.1)
and lifelong learning (1.3); trend for business R&D (2.2)
Current new capital raised (4.2)
Ireland
Current S&E graduates (1.1) and manufacturing
high-tech value-added (4.6); trend for EPO patents
and home Internet access (4.4)
Current R&D (2.1 and 2.2), patents (US and EPO), and
lifelong learning (1.3)
Italy
Trend for S&E graduates (1.1) and home Internet
access (4.4)
Current education (1.1, 1.2, 1.3), R&D (2.1, 2.2) and
patents (US and EPO); trend for EPO patents
Luxembourg
Current new capital raised (4.2)
Current S&E graduates (1.1), patents (US and EPO),
lifelong learning (1.3)
Netherlands
Current new capital raised (4.2), patents
(US and EPO),lifelong learning (1.3)
Current S&E graduates (1.1)
Portugal
Trends for home Internet access (4.4),
S&E graduates (1.1), R&D (2.1 and 2.2)
Current patents (US and EPO), finance (4.1 and 4.2),
education (1.1, 1.2, 1.3)
Sweden
Current patents (US and EPO), finance (4.1 and 4.2),
lifelong learning (1.3)
Trend for high-tech manufacturing value-added (4.6)
UK
Current education (1.1, 1.2, 1.3), high-tech
manufacturing value-added (4.6)
Current new capital raised (4.2); trend for EPO patents
european innovation scoreboard 2002
Major relative strengths
december 2002
Country
2.4 Convergence and divergence in EU innovation performance
To achieve the Lisbon goal, the lagging EU economies will need to catch up in innovative performance. This raises two questions: by how much does trend performance vary between the EU
Member States, and have these trends been converging? Table 4 shows the variation for each
indicator and the convergence for the twelve indicators with reliable trend data12.
The highest variation between the Member States is in new capital raised, high technology patenting
and participation in lifelong learning. The lowest variation is for ICT expenditure and both employment indicators in high-tech services and medium-high and high-tech manufacturing. Of interest, the
variation in the indicator for public R&D is less than half the variation for private R&D. The former
indicator is also converging over time, as EU Member States adopt similar policies for funding R&D.
Conversely, business R&D is diverging13 . Generally, all indicators that are the most strongly influenced by public policy are converging, while the indicators that are influenced by the private sector
are diverging. However, only three indicators are showing very high rates of divergence or convergence. These are high technology patents in the US, which is strongly diverging, and participation in
lifelong learning and home Internet access, both of which are strongly converging. For home
Internet access this is due to lower growth rates for countries with high levels of home access, as
these countries reach saturation, and higher growth rates for countries such as Portugal and Spain
with low initial levels of home Internet access.
12 Convergence is expressed as the percentage change
in the standard deviation across EU countries over
the time period. It increases as the change in the
standard deviation declines. The original trend data
are given in Annex Table C for all 15 EU Member
States, the US and Japan, and the three Associate
countries.
13 Business R&D is diverging as the leading countries
are growing faster than the EU average. In this case
divergence helps increase the EU mean and as such
is a desirable development.
9
Technical Paper No 1 on Member States and Associate Countries further explores patterns of
convergence and divergence within three groups of countries: leading innovators (including Denmark, Finland, The Netherlands, Sweden and the UK), middle range innovators (Austria, Belgium,
Germany, France and Ireland), and lagging innovators (Spain, Greece, Italy and Portugal).
december 2002
european innovation scoreboard 2002
Table 4. Variation and convergence of indicators between Member States
No.
Indicator
1.1
S&E graduates / 20-29 years
1.2
1.3
1.4
Member State variation1
Convergence 2
Medium 57.5
Converging -7.9
Population with tertiary education
Low 31.0
Converging -7.4
Participation in lifelong learning
High 86.9
Converging -17.0
Employment in med/high-tech manufacturing
Low 30.4
Diverging 1.5
1.5
Employment in high-tech services
Low 29.9
— 0.7
2.1
Public R&D / GDP
Low 27.7
Converging -8.9
2.2
Business R&D / GDP
Medium 63.1
Diverging 9.7
2.3.1 High-tech EPO patents / pop
High 130.9
2.3.2 High-tech USPTO patents / pop
High 109.7
Medium 61.3
— 0.4
Diverging 27.2
4.1
High-tech venture capital / GDP
4.2
New capital raised / GDP
High 178.8
— —
4.4
Home Internet access
Low 38.2
4.5
ICT expenditure / GDP
Low 21.5
— 0.1
4.6
High-tech manufacturing value-added
Medium 55.7
Converging -6.7
— —
Converging -62.1
1: Coefficient of variation or CV (standard deviation/mean*100) among the EU Member States for the most recent available data, using unweighted means. The classification of “low”, “medium”,
and “high” variation is based on the clustering of the CVs. All low CVs are below 40, the medium CVs lie between 50 and 70, and the high CVs are above 80.
2: The percentage change in the standard deviation across EU countries over the first and second time period. The first time period equals the average over the three years before the one-year
lag. The second time period is the most recent year for which data are available. A percentage change within plus or minus 1% is assumed to be neither converging nor diverging.
2.5 Main changes since the 2001 EIS
All indicators in the 2002 EIS have been updated by a minimum of one year compared to the 2001
EIS (with the exception of the four CIS indicators, which are not discussed here), while for some
countries the data for R&D expenditures has been updated by two years. Over this time, there has
been no significant change in five indicators (1.1 to 1.4) plus public R&D, while the remaining seven
indicators have shown marked improvements. Of note, business R&D recovered in the late 1990s,
from a gradual decline earlier on, increasing to 1.28% of GDP, although the EU still lags the US rate
of 2.04%. Other indicators that show a notable increase include high technology EPO patents (up
55%), home Internet access (up 35%), and the high technology value-added share of manufacturing (up 23%). The two financial indicators also improved, with high technology venture capital
increasing from 0.11% of GDP in 2000 to 0.24% in 2001, and capital raised on new stock markets
increasing from 1.1% of GDP to 1.7% of GDP.
2.6 The Associate countries
Results for the Associate countries of Switzerland, Iceland and Norway are given in Annex Tables B
and D. Data coverage for these three countries is very good, with no missing indicators for Norway,
and two for Iceland and Switzerland14 . Both Switzerland and Iceland are above the EU mean for 10
and 11 indicators respectively15 , which would place them among the innovative leaders. However,
the trend results for Switzerland are behind the EU average for six of eight indicators, suggesting that
Switzerland is losing its innovative advantage.
14 Full data details are given in Technical Paper No 1:
Member States and Associate Countries.
15 Excluding the CIS indicators.
10
The very good results for Iceland for several indicators of business innovation (business R&D,
patents and finance) are largely due to a successful policy of attracting FDI in biotechnology. This is
also apparent in the excellent trend results for Iceland for these indicators plus the growth in
employment for high technology services. Norway is a middle range country that does very well in
several indicators for human resources, but lags behind the EU average for business innovation. The
trend results for Norway are behind the EU average for eight of eleven indicators. Only for USPTO
high technology patents is Norway improving much faster than the EU average.
3 2002 EIS results for the EU Regions
european innovation scoreboard 2002
This year’s EIS introduces seven innovation indicators plus per capita GDP at the regional level
(NUTS 1 or NUTS 2) for the EU Member States 16 . Regional level data is of value for two reasons.
First, innovation policies are often developed and implemented at the regional and even municipal
level, in addition to national and EU level policies. Regional indicators can help inform these policies.
Second, and more importantly, many innovative activities are strongly localised into clusters of
innovative firms and public institutions such as research institutes and universities. Policy needs to be
directed at supporting these clusters and, where feasible, encouraging new clusters of innovation in
other regions. This will often require different types of policy actions. The effective design and
implementation of such policies therefore depend on identifying both highly innovative regions and
less innovative regions that might have future potential. Other regions, due to an economic basis in
tourism, agriculture or resource extraction, may need diffusion-oriented policies that focus on the
adoption rather than the creation of new technology.
december 2002
The seven regional indicators as listed in Table 5 are a first start at providing useful data for regional
policy. They provide coverage of human resources, employment in high-technology sectors, and the
creation of new knowledge through R&D and patents. However, due to data limitations17 , the
regional indicators are better at identifying strong innovative regions than regions with future potential, or regions that require diffusion-oriented policies.
Table 5. Regional indicators: Definitions and year
Year
1
No.
Short definition
1.2
Population with tertiary education (% of 25 – 64 years age class)
2001
1.3
Participation in lifelong learning (% of 25 – 64 years age class)
2001
1.4
Employment in medium-high and high-tech manufacturing
(% of total workforce)
2000
1.5
Employment in high-tech services (% of total workforce)
2000
2.1
Public R&D expenditures (GERD - BERD) (% of GDP)
1999
2.2
Business expenditures on R&D (BERD) (% of GDP)
1999
2.3.1 EPO high-tech patent applications (per million population)
2000
1: Most recent year for a minimum of five countries.
The choice for what constitutes a region is in line with the European Commission’s guidelines18 :
NUTS 1 for Austria, Finland, France, Greece, Ireland, Italy, The Netherlands, Portugal, Spain and
Sweden, and NUTS 2 for Belgium, Germany and the UK19. As the NUTS classification is mainly
designed to suit political and administrative needs, this classification is not the best for measuring
innovative performance at a regional level. An alternative regional concept is used by the PAXIS
project20 , which identified 15 “economic areas” showing excellence in innovation. These areas do
not in all cases comply with the existing NUTS classifications. The concept of an “economic area”,
linking innovative cities, might be better suited for a regional innovation scoreboard21 . However,
constraints in data availability made it impossible to choose a different regional dimension.
16 Full details on the regional innovation scoreboard
are given in Technical Paper No 3: EU Regions.
17 Regional data are available from Eurostat only for
the innovation indicators listed in Table 5. Furthermore, the Community Innovation Survey does not
provide reliable regional data, due to not including
the region in the survey sample design. The transmission and application of knowledge will thus be
difficult to proxy.
18 European Commission, The Regions and the New
Economy: Guidelines for Innovative Actions under the
ERDF in 2000-06, Brussels, 2001.
19 For Denmark there is no breakdown into NUTS 1 or
2 regions. For Luxembourg there is no NUTS
breakdown.
20 The Pilot Action of Excellence on Innovative Startups.
3.1. Leading regions
As noted earlier, a Summary Innovation Index has not been calculated for the national EIS because the
four CIS indicators could not be updated. However, the CIS to date is a poor source of regional indicators
because the region was not included in the sampling frame, although this may change in the future.
Therefore, a regional composite innovation index can be calculated based on the seven indicators for
which data are available. Two tentative summary indicators are provided: the RNSII, which identifies
leading regions within each country, and the RRSII, which compares each region against the EU mean22 .
21 One might argue that directly promoting these
“highly innovative regions or areas” leads to an
overall larger increase in innovation through
spillovers to neighbouring less innovative regions
than by directly promoting these less innovative
regions. Empirical evidence about the size of these
(possible) spillovers is incomplete to make any
definite statement.
22 These composite indicators are of an experimental
nature. The definitions are given in the Technical
Annex.
11
Table 6. Leading Innovation Regions by Country (based on 7 indicators)
Country
% regions >
country mean
Leading regions (RNSII)
2
9
22%
Wien (1.45)
Kärnten (1.29)
Belgium
3
67%
Vlaams Gewest (1.11)
Reg. Bruxelles (1.09)
Germany
16
25%
Berlin (1.35)
Bayern (1.34)
Baden-Württemberg (1.34)
Spain
18
28%
Comunidad de Madrid (2.01)
Cataluña (1.34)
Comunidad Foral de Navarra (1.30)
Greece
13
15%
Attiki (1.39)
Kriti (1.04)
France
22
14%
Ile-de-France (1.60)
Midi-Pyrenées (1.31)
Finland
6
33%
Uusimaa (Suuralue) (1.30)
Pohjois-Suomi (1.07)
Piemonte (1.35)
Lazio (1.35)
Utrecht (1.06)
Limburg (1.02)
Italy
20
20%
Lombardia (1.44)
2
50%
Southern & Eastern (1.12)
12
33%
Noord-Brabant (1.59)
Portugal
7
29%
Lisboa E Vale Do Tejo (1.39)
Centro (P) (1.01)
Sweden
8
25%
Stockholm (1.46)
Oestra Mellansverige (1.00)
12
25%
Eastern region (1.48)
South East region (1.35)
Ireland
Netherlands
UK
Rhône-Alpes (1.12)
South West region (1.21)
1: These are indicators 1.2, 1.3, 1.4, 1.5, 2.1, 2.2 and 2.3.1. Some regional indicators are not available or incomplete: 2.1 and 2.2 for Austria, 2.1 for Belgium and Sweden, 1.3, 2.1 and 2.2 for
Ireland, 2.1 and 2.2 for The Netherlands, and 1.4, 1.5 and 2.3.1 for Greece, Italy, Portugal and Spain.
2: The RNSII (Regional National Summary Innovation Index) is calculated as the average of the indicator values indexed to the country mean. An index value above (below) 1.00 indicates that
the region is performing above (below) the country mean. RNSIIs should not be compared across countries.
Table 6 identifies the leading regions within each country, using the RNSII. Some of the leading
regions perform far above the country mean, most notably in Spain, France and The Netherlands. In
most countries only a few regions are above the country mean, showing that the innovative capabilities of the country are strongly concentrated in a few regions.
december 2002
european innovation scoreboard 2002
Austria
No. of
regions
1
The RRSII tries to locate “local” leaders by taking into account both the region’s relative performance
within the EU and the region’s relative performance within the country23 . The top ten leading regions
are as follows: Stockholm (S), Uusimaa (Suuralue) (FIN), Noord-Brabant (NL), Eastern region (UK),
Pohjois-Suomi (FIN), Ile-de-France (F), Bayern (D), South East region (UK), Comunidad de Madrid
(E) and Baden-Württemberg (D). The appearance of the Comunidad de Madrid proves that also
within “lagging” countries, there can be innovation leaders on a regional level.
3.2 A link between innovative and economic performance
Figure 1 suggests a positive relation between a region’s innovative performance as measured by its
RRSII and its economic performance. The high per capita income levels for Hamburg (D) and other
regions, however, show that other factors can also generate high incomes. Conversely, as demonstrated by Noord-Brabant (NL), a strong innovative performance is not necessarily correlated with
high average incomes.
23 The RRSII is designed to pinpoint “local leaders”.
Regions in highly performing countries will always
look more favourable when compared directly to
regions from less performing countries. Locating
regions which do relatively well despite their
country’s innovation weaknesses seems worthwhile
and interesting. The experimental nature of the RRSII
might call for a redesign in the 2003 EIS.
24 Based on France’s 2001 Summary Innovation Index
(see also section 2.3 in this document).
12
Figure 1 also shows the spread between regions within countries. Finland, France, The Netherlands
and Sweden show the largest spread between the “best” and the “worst” performing region. In
countries with a high innovation performance (Finland, The Netherlands, Sweden and the UK) more
than half of the regions perform above the EU mean. For the middle rank countries, national
innovation performance seems to be below the EU mean due to a lack of a sufficient number of
innovative regions and not so much to the level of innovative performance in these countries’ leading
regions. Ile-de-France, for example, is among the leading regions within Europe, while France as a
country is not24 .
Figure 1. Innovative and economic performance on a regional level
220
HAMBURG (D)
180
ILE DE FRANCE (F)
160
UUSIMAA
(FIN)
120
100
NOORD-BRABANT (NL)
80
AT
B
D
60
EL
E
F
40
FIN
I
NL
20
P
S
UK
0
0
20
40
60
80
100
120
140
160
180
200
220
240
Revealed Regional Summary Innovation Index (RRSII)
Technical Paper No 3: EU Regions provides more detailed results for currently available data;
leading regions by country; indicator graphs; the two tentative composite innovation indicators;
and preliminary steps towards the 2003 regional scoreboard. This paper is available from
www.cordis.lu/trendchart
european innovation scoreboard 2002
STOCKHOLM
(S)
140
december 2002
Relative per capita GDP
200
13
Thirteen “Candidate countries” are currently
involved in the EU enlargement process.
EU accession negotiations are currently
conducted with twelve of them: Bulgaria
(BG), Cyprus (CY), Czech Republic (CZ),
Estonia (EE), Hungary (HU), Latvia (LV),
Lithuania (LT), Malta (MT), Poland (PL),
Romania (RO), Slovakia (SK) and Slovenia
(SI). It is expected that they will be concluded with ten in December 2002, while
they continue with Bulgaria and Romania.
Negotiations have not yet started with Turkey (TR).
december 2002
european innovation scoreboard 2002
4 EIS 2002 results for the EU Candidate
countries
A 2001 report for the European Commission replicated the 2001 EIS for six Candidate countries25
(Cyprus, Czech Republic, Estonia, Hungary, Poland and Slovenia) and found serious problems with
data availability, particularly for the indicators on the transmission and application of knowledge and
for innovation finance, outputs and markets26 . In order to improve data availability, a questionnaire
was distributed among the members of the “Group of Senior Officials in Innovation Policy” from the
Candidate countries. This provided additional results for nine countries: Bulgaria, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Malta, Slovakia and Turkey. On average, the 2002 EIS has
data for 64% of the indicators, ranging from a low of 43% for Cyprus to a high of 81% for Turkey27 .
The 2002 EIS results for the Candidate countries are given in Annex Table D, with trend results in
Annex Table E. Table D includes the reference year for each country and indicator, since data
limitations mean that the results are often older than the comparative results for the EIS for the EU
Member States. For comparison, both Tables D and E include the EU average. Table D also includes
two alternative indicators that are possibly more appropriate for economies in transition than the
indicators for the EU Member States and one alternative indicator for reasons of data availability.
These alternatives include all patent applications at the EPO (2.3.1A) versus high technology patents
only (2.3.1) and the stock of inward foreign direct investment as a percentage of GDP (4.6A)
instead of the share of manufacturing value-added from high technology products (4.6). For reasons
of data availability, Internet access is based on the percentage of the population with any Internet
access (4.4A) instead of home Internet access.
4.1 Leading Candidate countries
Table 7 identifies the innovation leaders among the Candidate countries and gives the EU and
Candidate country means. The table only provides the alternative indicators for EPO patents, Internet
access, and inward FDI. None of the Candidate countries are above the EU mean for five of 13
available indicators: high technology services employment, private R&D, all EPO patents, high technology USPTO patents and Internet access.
25 European Commission – DG Enterprise, Innovation
policy issues in six candidate countries: The challenges,
EUR 17036, 2001.
26 Most Candidate countries carry out innovation
surveys. The Czech Republic, Latvia, Lithuania,
Slovakia and Slovenia have already carried out
surveys based on CIS II, Poland and Romania have
carried out surveys based on CIS I. Hungary has
launched a pilot innovation survey in 2000. For CIS
III, several countries (Czech Republic, Estonia,
Lithuania, Malta, Slovenia and Slovakia) have already
launched their questionnaire. Cyprus, Hungary and
Latvia planned do this in September or the 3rd
quarter of 2002. Romania has planned the launching of the questionnaire for the 1st quarter of 2003,
Bulgaria is planning a test survey for 2003.
27 Full (data) details are given in Technical Paper No 2:
Candidate Countries.
28 Data availability differs among countries, making it
impossible to calculate trends using the same
year(s). As such, the trend results have to be interpreted with caution.
14
The Candidate countries perform favourably compared to the EU for the share of the active population with tertiary education (with Bulgaria, Cyprus, Estonia and Lithuania equal to or above the EU
mean), the employment share for high-tech manufacturing (with the Czech Republic, Hungary,
Poland and Slovenia close to or above the EU mean), ICT expenditures (with the Czech Republic,
Estonia, Hungary and Slovakia above the EU mean), and the stock of inward FDI (with the Czech
Republic, Estonia, Hungary and Malta above the EU mean).
Innovative capabilities in the Candidate countries are dominated by less than half of the countries,
with 88% of the leading slots in Table 7 taken by six countries: Estonia (8), the Czech Republic and
Slovenia (7 each), Lithuania and Hungary (5 each), and Malta (4). Latvia occurs twice, and Cyprus,
Slovakia and Turkey once. Poland, Romania and Bulgaria are never among the top three Candidate
countries.
4.2 Current trends in Candidate countries
Trend results for the Candidate countries are summarised in Table 8. Data are available for only ten
indicators, although for indicators 1.1 (new S&E graduates) and 1.3 (lifelong learning) data are only
available for six or fewer Candidate countries28 . The full results are given in Annex Table G.
Table 7. Innovation leaders among the 13 Candidate countries
CC mean
3
1.1
S&E graduates / 20 - 29 years
10.3
6.6
13.1 (SI)
CC leaders
9.4 (LT)
6.8 (EE)
29.4 (EE)
26.8 (CY)
1.2
Population with tertiary education
21.2
17.5
45.0 (LT)
1.3
Participation in lifelong learning
8.5
5.4
16.3 (LV)
9.7 (MT)
5.3 (EE)
1.4
Employment in med/high-tech manufacturing
7.6
5.4
9.2 (CZ)
8.8 (HU)
8.7 (SI)
1.5
Employment in high-tech services
3.6
2.6
3.4 (EE)
3.2 (HU)
2.1
Public R&D / GDP
0.67
0.41
0.68 (SI)
0.54 (CZ)
0.53 (EE/LT/TR)
2.2
Business R&D / GDP
1.28
0.32
0.83 (SI)
0.81 (CZ)
0.45 (SK)
152.7
7.1
20.6 (SI)
16.1 (HU)
12.1 (CZ)
12.4
0.5
2.3.1A All EPO patents / population
2.3.2 High-tech USPTO patents / population
4.1
High-tech venture capital / GDP
4.4A
Home Internet access / 100 population
4.5
ICT expenditure / GDP
4.6A
Inward FDI / GDP
0.24
0.27
2.6 (MT)
3.2 (CZ)
0.6 (CZ)
0.5 (LT)
0.90 (LT)
0.62 (LV)
0.15 (SI)
30.0 (SI)
25.4 (MT)
31.4
14.8
30.1 (EE)
8.0
6.0
9.6 (EE)
30.3
31.3
84.7 (MT)
9.5 (CZ)
8.9 (HU)
53.2 (EE)
43.4 (HU)
1: The CIS indicators have not been updated for the EU and are therefore not included in this table.
2: Weighted mean based on summing the numerator and denominator across all EU countries (for indicator 1.1 the EU mean is an unweighted mean).
3: Unweighted average for countries for which data are available. Available data are insufficient for calculating weighted means.
Table 8. Trends in innovation performance (% change) in the Candidate countries
EU mean2
CC mean3
S&E graduates / 20 - 29 years
13.7
14.3
53.2 (LT)
38.2 (EE)
-14.4 (HU)
1.2
Population with tertiary education
17.9
7.3
17.8 (BG)
14.2 (RO)
-1.1 (SI)
1.3
Participation in lifelong learning
21.4
2.9
22.2 (RO)
7.9 (LV)
-7.5 (LT)
-7.0 (EE)
1.4
Employment in med/high-tech manufacturing
-2.1
10.2
105.7 (LV)
20.0 (EE)
-21.4 (RO)
-15.4 (LT)
1.5
Employment in high-tech services
18.3
10.4
30.4 (SI)
24.3 (CY)
-11.9 (LT)
-8.6 (RO)
2.1
Public R&D / GDP
-2.0
3.7
57.8 (TR)
26.0 (CZ)
-34.1 (RO)
-27.0 (SK)
2.2
Business R&D / GDP
7.0
8.1
85.8 (TR)
83.7 (LV)
-43.6 (RO)
-37.4 (BG)
4.4A
Home Internet access / 100 population
155.3
148.7
255.2 (MT)
226.1 (BG)
4.5
ICT expenditure / GDP
14.8
26.2
40.5 (PL)
38.9 (SK)
4.6A
Inward FDI / GDP
99.3
79.3
195.1 (SK)
180.9 (BG)
No.
Indicator
1.1
1
CC leaders
european innovation scoreboard 2002
EU mean
2
Indicator
CC decreases
-0.1 (EE)
december 2002
1
No.
-3.3 (CY)
1: The CIS indicators have not been updated for the EU and are therefore not included in this table.
2: Weighted mean based on summing the numerator and denominator across all EU countries (for indicator 1.1 the EU mean is an unweighted mean).
3: Unweighted average for countries for which data are available. Insufficient data are available for calculating weighted means.
The mean trend for the Candidate countries exceeds the EU mean trend for five of the ten comparable indicators. However, a striking feature of the trend results for the Candidate countries is that
there are many negative values for the human resources indicators and for R&D, due in part to deep
structural changes in several of the economies. The trend averages for the Candidate countries are
much higher for the market and investment indicators in group four, where only Cyprus, for inward
FDI, has a negative trend. Due to the prevalence of negative trends, Table 8 gives both the two
leading countries and the two countries with the largest negative trends. For the indicators in groups
one and two, the means for the Candidate countries are often relatively low, based on the average
between large increases in some countries and large decreases in others.
Almost all Candidate countries are trend leader for at least one indicator, with Bulgaria and Latvia
leading for 3 indicators and Estonia, Romania, Slovakia and Turkey for 2 indicators. Bulgaria is leading
for population with tertiary education, home Internet access and inward FDI, while Latvia is leading for
participation in lifelong learning, employment in medium/high-tech manufacturing and business
R&D. Although Romania is the worst affected by decreases in both R&D and employment indicators,
it is improving at an above average rate for two education indicators. Estonia is leading for S&E
graduates and employment in medium/high-tech manufacturing, Slovakia is leading for ICT expenditures and inward FDI, and Turkey is leading for both R&D indicators. As a note of caution, this
message on trends may look over-optimistic. Many leading trends for individual countries are derived from very low initial values, so that even after rapid growth the trend leaders are often below
the indicator average for the Candidate countries.
15
european innovation scoreboard 2002
Annexes
Main Data Tables
Table A: European Innovation Scoreboard 2002:
Data Definitions and Sources
17
Table B: European Innovation Scoreboard 2002:
Member States and Associate Countries
18
december 2002
Table C: European Innovation Scoreboard 2002:
Most recent years used (Member States
and Associate Countries)
19
Table D: European Innovation Scoreboard 2002:
Trends (Member States and Associate Countries)
20
Table E: European Innovation Scoreboard 2002:
Candidate Countries
21
Table F: European Innovation Scoreboard 2002:
Most recent years used (Candidate Countries)
22
Table G: European Innovation Scoreboard 2002:
Trends (Candidate Countries)
16
23
Technical Annex
24
Technical Paper: Indicators and Definitions
25
17
EUROSTAT, Labour Force Survey (Structural Indicator 1.5)
EUROSTAT, Labour Force Survey
New S&E graduates (‰ of 20–29 years age class)
Population with tertiary education (% of 25 – 64 years age class)
Participation in lifelong learning (% of 25 – 64 years age class)
Employment in medium-high and high-tech manufacturing (% of total workforce)
Employment in high-tech services (% of total workforce)
Knowledge creation
Public R&D expenditures (GERD – BERD) (% of GDP)
Business expenditures on R&D (BERD) (% of GDP)
1.1
1.2
1.3
1.4
1.5
2.
2.1
2.2
SMEs involved in innovation co-operation (% of manufacturing SMEs)
Innovation expenditures (% of all turnover in manufacturing)
Innovation finance, output and markets
High technology venture capital investment (% of GDP)
Capital raised on parallel markets plus by new firms on main markets (% of GDP)
Sales of “new to market” products (% of all turnover in manufacturing)
Home Internet access (% of all households)
Home Internet access (per 100 population)
ICT expenditures (% of GDP)
Share of manufacturing value-added in high-tech sectors
Inward FDI stock (% of GDP)
3.2
3.3
4.
4.1
4.2
4.3
4.4
4.4A
4.5
4.6
4.6A
UNCTAD (UN Conference on Trade and Development)
EUROSTAT, Structural Business Statistics
EUROSTAT (Structural Indicator 2.7); WITSA/IDC: Digital Planet
EUROSTAT/Eurobarometer
EUROSTAT (Structural Indicator 2.3a)
EUROSTAT, Community Innovation Survey
World Federation of Exchanges (FIBV)
European Private Equity and Venture Capital Association (EVCA)
EUROSTAT, Community Innovation Survey
EUROSTAT, Community Innovation Survey
EUROSTAT, Community Innovation Survey
december 2002
european innovation scoreboard 2002
1: Full definitions are available in Technical Paper No 4: Indicators and Definitions. Indicators 2.3.1A, 4.4A and 4.6A are alternative indicators used for Candidate countries only.
2: For some of the Associate and Candidate countries national estimates are used (as collected from the Group of Senior Officials in Innovation Policy). Tables B and E give these national estimates in italics.
3: For reasons of comparability the data are taken from the “Mid-Year Survey of Pan-European Private Equity & Venture Activity”, see Technical Paper 4 for more explanations.
SMEs innovating in-house (% of manufacturing SMEs)
3.1
USPTO (US Patent and Trademark Office)
2.3.2 USPTO high-tech patent applications (per million population)
Transmission and application of knowledge
EUROSTAT
2.3.1A EPO patent applications (per million population)
3.
EUROSTAT
2.3.1 EPO high-tech patent applications (per million population)
EUROSTAT, R&D statistics (Structural Indicator 2.1); OECD
EUROSTAT, R&D statistics (Structural Indicator 2.1); OECD
EUROSTAT, Labour Force Survey
EUROSTAT, Labour Force Survey
EUROSTAT, Education statistics (Structural Indicator 2.4)
Human resources
2
1.
Source
Short definition of indicator
No.
1
3
Annex Table A: European Innovation Scoreboard 2002 Data Definitions and Sources
18
european innovation scoreboard 2002
Empl high-tech services
Public R&D / GDP
Business R&D / GDP
1.5
2.1
2.2
1.28
0.67
3.61
7.57
1.14
0.65
3.03
6.48
7.8
New-to-market products
Home Internet access / household37.7
ICT expenditures / GDP
Manuf high-tech value-added share10.1 9.0
4.3
4.4
4.5
4.6
8.2
D
8.3
DK
9.9
E
3.8
EL
18.7
F
17.8
FIN
5.6
I
23.2
IRL
1.8
L
6.93
6.5
1.73
6.30
47.2
5.6
0.60
5.2
10.7
7.32
36.4
2.6
2.37
0.44
2.1
8.9
29.4
13.9
21.9
1.45
0.56
4.08
6.7
6.89
38.4
7.1
0.95
0.07
3.9
14.7
58.7
16.4
43.7
1.80
0.72
3.21
6.57 11.21
7.3
10.7
7.42
58.6
5.1
0.14
0.46
4.8
37.4
59.0
22.7
32.2
1.32
0.75
4.94
6.99
20.8
5.6
4.41
24.7
9.8
7.92
0.19
2.4
7.0
21.6
1.4
3.1
0.52
0.44
2.62
5.46
4.7
—
5.09
9.9
—
1.57
0.16
1.6
6.5
20.1
0.4
0.6
0.19
0.48
1.70
2.22
1.4
2.68
0.98
4.40
7.44
19.3
13.2
7.35
30.1
7.9
0.82
0.24
3.9
12.0
36.0
14.0
19.3
6.74
50.2
7.3
0.38
0.57
4.3
19.9
27.4
41.6
27.8 137.6
1.36
0.77
4.08
7.16
2.7
6.8
5.17
33.5
13.5
0.67
0.20
2.6
4.7
44.4
4.1
6.2
0.53
0.53
3.05
7.42
5.1
—
—
9.6
24.5
4.6
19.8
—
—
3.06
2.03
5.3
25.4
5.23
47.6
8.4
—
8.10
43.0
—
1.21 10.81
0.31
3.3
23.2
62.2
6.1
25.3
0.88
0.33
4.11
7.28
5.2
1 Weighted means based on summing the numerator and denominator across all EU countries. Unweighted mean for indicator 1.1.
2 Data in italics are national estimates taken from the questionnaires distributed to the ‘Group of Senior Officials in Innovation Policy’.
3 Data for the Member States for indicators 3.1, 3.2, 3.3 and 4.3 have not been updated as new data from the Community Innovation Survey are not available.
3
New capital
4.2
0.14
3.5
High-tech venture capital / GDP 0.24
3.7
4.1
3
Innovation expenditure
12.9
59.1
3.3
11.2
44.0
SMEs innov co-op
3
SMEs innov in-house 3
3.2
3.1
8.1
Empl med/high-tech
manufacturing
1.4
8.5
2.3.2 USPTO high-tech patents / pop 12.4
Lifelong learning
1.3
9.7
B
5.8
NL
6.2
P
11.6
S
16.2
UK
10.2
US
12.5
JP
2.5
CH 2
2
8.4
IS
2
7.9
NO
9.7
8.30
63.8
6.9
5.97
0.23
3.8
13.8
51.0
18.6
57.9
1.14
0.88
4.16
4.29
16.3
5.3
5.44
26.1
7.2
0.22
0.03
1.7
4.5
21.8
0.0
0.9
0.17
0.58
1.43
3.57
3.3
15.3
9.85
60.7
6.9
3.07
0.39
7.0
27.5
44.8
47.3
95.1
2.84
0.94
5.13
7.90
21.6
14.8
8.62
49.3
6.7
1.01
0.24
3.2
15.7
35.8
15.1
27.5
1.21
0.66
4.75
7.18
21.7
25.8
8.22
46.7
—
0.81
—
—
—
—
91.9
49.5
2.04
0.66
—
—
—
13.8
8.98
34.0
—
0.00
—
—
—
—
80.0
36.6
2.11
0.87
—
—
—
14.1
7.80
—
3.4
5.17
0.24
8.5
18.8
64.3
21.2
—
1.95
0.69
4.10
8.10
18.3
—
9.30
69.7
7.2
2.53
0.49
—
22.7
44.7
21.5
49.0
1.86
1.04
5.50
1.75
23.5
4.8
5.65
58.2
4.1
1.19
0.33
2.7
20.5
36.9
8.3
15.2
0.95
0.75
4.37
4.18
14.2
21.22 14.52 27.82 23.84 26.48 23.06 17.08 22.98 32.47 10.29 22.24 18.28 24.02 10.17 29.71 28.63 36.51 29.85 25.40 23.75 33.81
7.1
A
17.0
Pop with 3rd education
1.2
1
10.3
EU
27.8
New S&E grads
1.1
2.3.1 EPO high-tech patents / pop
Indicator
No.
Annex Table B: European Innovation Scoreboard 2002 Member States and Associate Countries
december 2002
19
2001
1996
1996
1996
2000
1998
1996
1996
2000
2000
2001
2001
1996
1996
1996
2000
2000
2000
2001
1998
1998
1998
2000
2000
2001
2001
Manuf high-tech value-added share1999 1999 1999 1999 1999 1999
4.6
2001
1998
1998
1998
2000
2000
1999
1999
2001 2001
1996 1996
1996 1996
1996 1996
2000 2000
2000 2000
2000 2001
2000 2001
2001 2001
2001
1996
1996
1996
2000
2000
2001
1999
2001
2001
1996
1996
1996
2000
2000
1999
1999
2001
2001
2001
1998
1998
2000
2000
— 2001
— 1996
1996
1996
2000
2000
— 1999
— 1999
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
—
2001
2001
—
1999 1999
2001 2001
2001 2001
1996 1996
1999
2001
2001
1996
1999
2001
2001
1996
december 2002
2001
2001
1996
1996
1996
2000
2000
1999
1999
2001
2001
2001
1996
1996
1996
2000
2000
1999
1999
2000
2001
2000
2001
1996
1996
1996
2000
2000
2001
2001
2001
2001
2001
—
—
—
—
2000
2000
2000
2000
2001
—
2000
—
—
—
—
2000
2000
2000
2000
2001
—
2000
1996
1999
2001
2001
1996
1999
2001
2001
1996
1999
2001
2001
1996
1997
2001
2000
—
1997
2001
2000
—
european innovation scoreboard 2002
— 1999
2001
2001
— 1996
2001
1: Data for the Member States for indicators 3.1, 3.2, 3.3 and 4.3 have not been updated as new data from the Community Innovation Survey are not available.
2: Unweighted average of last two years.
2001
2001
1998
ICT expenditures / GDP
2001
1996
4.5
2001
1998
Home Internet access / household
1996
4.4
1996
New-to-market prod
4.3
1996
New capital
1
2001
1996
1996
1996
2000
2000
2000
2000
2001
1997
2001
2000
JP
2001
1999
1999
1999
2000
—
2000
2000
2001
1999
2001
2000
CH
IS
NO
1997
2001 2001
—
1998 1997
1998 1997
2000 2000
2000 2000
2001 1999
2001 1999
2001 2001
2001 2001
2001 2001
2000 2000
1999
2000
—
1999
— 1999
2001 2001
2001 2001
1998 1997
00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01 00/01
2001
1996
1996
1996
2000
2000
1998
2001
2001
4.2
2
High-tech venture capital / GDP
4.1
1
Innovation exp
1
SMEs innov co-op
3.3
3.2
SMEs innov in-house 1
2000
2.3.2 USPTO high-tech patents / pop
3.1
2000
2.3.1 EPO high-tech patents / pop
2001
1999
2001
2001
2001
2000
US
Business R&D / GDP
1998
2001
2001 2001
2000
2000
UK
2.2
2001
2001
2001
1997
2000
S
Public R&D / GDP
2001
2001
2001
2000
P
2.1
2001
2001
2001 2001
2000
NL
Empl high-tech services
2001
2001
2000
L
1.5
2001
2001
1999
IRL
Empl med/high-tech manufacturing2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2000 2001 2001 2001 2001 2001 2001
1997
2001
1999 1999
I
1.4
2001
2000
1993
FIN
Lifelong learning
2001
2000
F
1.3
2001
1999
EL
2000
2000
E
Pop with 3rd education
2000
DK
1.2
2000
D
2000
B
New S&E grads
A
1.1
EU
Indicator
No
Annex Table C: European Innovation Scoreboard 2002 Most recent years used (Member States and Associate Countries)
20
european innovation scoreboard 2002
17.9
Pop with 3rd education
Lifelong learning
Empl med/high-tech
manufacturing
Empl high-tech services
Public R&D/GDP
Business R&D/GDP
1.2
1.3
1.4
1.5
2.1
2.2
—
85.4
23.2
47.3 2
Innovation exp
High-tech venture capital/GDP
New capital
New-to-market prod
Home Internet access/
household
ICT expenditures/GDP
Manuf high-tech
value-added share
Country average
4.1
4.2
4.3
4.4
4.5
4.6
—
—
—
—
12.2
-2.8
16.6
2.7
-3.7
6.8
—
—
—
—
—
—
44.4
—
—
—
—
—
—
49.9
58.5 103.4
9.7
8.8
22.3
DK
18.8
4.2
38.5
-0.2
6.8
19.3
33.8
E
—
—
—
—
—
—
—
—
—
—
—
—
77.1 116.4
65.9 114.0
8.7
2.4
18.0
7.4
6.7
2.8
-9.6 -12.6
D
18.0
40.1
—
14.7
22.7
17.5
17.8
28.9
35.4
6.2
55.2
12.0
9.6
35.4
1.5
7.2
4.4
17.0
20.5
25.9
FIN
--
—
—
—
—
—
24.2
—
—
—
—
—
—
68.1
85.2 107.2
-1.5
-9.3
11.7
0.7
-1.2
16.4
8.7
F
21.7
-1.8
—
—
5.3
IRL
-5.8
—
—
—
—
—
—
25.3
—
—
—
--
—
—
28.2
25.1
6.7
-7.9
NL
—
—
9.0
—
—
—
—
—
—
—
—
—
—
—
—
—
23.5
29.6
—
20.9
48.8
36.1
14.6
38.6
54.4
7.2
50.2
15.3
17.6
77.5
23.9
-2.4
54.0
—
18.0
31.6
29.3
11.9
10.6
50.6
S
32.8
25.6
10.6
0.1
—
—
—
—
—
—
—
14.2
91.6
17.6
— -18.6
9.7
7.0
-2.0
—
—
—
4.6
-6.1
US
—
—
—
—
—
—
35.7
37.2
25.4
13.2
—
—
—
—
—
—
21.6
57.1
3.8
7.0
—
—
—
-1.8
—
JP
23.0
—
5.2
31.4
—
14.4
55.7 125.9
—
—
—
—
—
—
41.9
70.4 151.9
-0.5
6.8
24.8
-6.7
13.0
14.1
10.5
UK
34.0 256.0
—
—
—
—
—
—
95.7
86.3
6.8
3.4
23.7
-7.6
6.5 -15.0
6.9
82.4
P
87.7 305.6
6.6
-7.0
25.1
13.4 -12.0
20.5
1.4
28.6
L
28.0 190.4 327.8
2.3
8.2 -13.9
16.0
-0.9
0.7
14.6
40.0
I
96.0 405.9 162.8 411.5 561.1 177.4 214.3 605.4
—
—
—
—
—
—
-8.2
43.7
46.0
34.0
14.6
-2.3
35.5
4.0
—
EL
18.1
-4.8
NO
25.9 -13.4
8.8
18.3
IS
26.9
7.2
1.9
19.8
—
—
—
—
—
—
—
75.3
—
—
—
—
—
—
—
—
—
22.2 336.3
— 523.0
— 116.4
— -14.2
12.0
6.6
1.0
-8.5
—
—
—
—
—
—
—
94.6
47.6
-0.9
2.6
17.4
1.7 -13.9 -17.0
-3.1
10.9
3.5
CH
1: Trends are calculated as the percentage change between the last year for which data are available and the average over the preceding three years, after a one-year lag. Due to short time series, for some indicators a different average has been used.
2: Calculated as the unweighted average of Member States’ averages.
14.8
271.4 402.1 203.3 115.7 171.3 349.1
—
—
—
—
—
3.3
—
SMEs innov co-op
—
3.2
—
64.3
93.5
—
—
21.5
SMEs innov in-house
43.9
2.3.2 USPTO high-tech patents/pop
53.1
7.7
—
B
-0.5 -10.2
41.5
36.5
A
3.1
97.2
2.3.1 EPO high-tech patents/pop
5.4
-2.0
18.3
-2.1
21.4
13.7
New S&E grads
1.1
EU
Indicator
No.
Annex Table D: European Innovation Scoreboard 2002 Trends (Member States and Associate Countries) 1
december 2002
21
Empl hi-tech services
Public R&D / GDP
Business R&D / GDP
1.5
2.1
2.2
44.0
SMEs innov in-house
SMEs innov co-op
Innovation exp
Hi-tech venture capital / GDP
New capital
New-to-market prod
Home Internet access / household
3.1
3.2
3.3
4.1
4.2
4.3
4.4
30.3
26.4
23.7
—
—
22.1
—
—
—
—
—
—
—
—
6.0
—
0.05
0.20
1.83
1.03
3.1
26.76
—
CY
42.6
—
9.5
13.6
—
—
—
0.021
—
—
—
0.58
12.1
—
0.81
0.54
3.22
9.16
—
11.59
4.00
CZ
53.2
—
9.6
30.1
9.8
6.0
—
—
2.4
13.0
33.2
—
6.9
—
0.15
0.53
3.38
4.79
5.3
29.42
6.83
EE
43.4
14.85
8.9
14.8
2.6
—
—
0.035
—
—
—
0.30
16.1
1.51
0.36
0.45
3.24
8.80
3.0
13.96
4.49
HU
20.6
22.35
5.9
6.8
3.0
—
—
0.900
—
12.0
51.0
0.54
1.1
—
0.07
0.53
2.01
3.18
3.7
45.03
9.35
LT
december 2002
1: Data in italics are national estimates collected from the Group of Senior Officials in Innovation Policy.
2: Indicators 2.3.1A, 4.4A and 4.6A are alternative indicators.
3: The EU mean is calculated using WITSA/IDC data and is thus not comparable with the mean for the MS Scoreboard as shown in Annex Table B.
4.6A Inward FDI / GDP
Manuf hi-tech value-added share
4.6
5.90
3.8
8.0 3
ICT expenditures / GDP
4.5
10.1
7.5
31.4
—
—
—
—
—
—
—
0.12
3.2
—
0.11
0.41
2.71
5.50
—
21.29
4.73
BG
4.4A Home Internet access / pop
37.7
6.5
1.73
0.242
3.7
11.2
12.4
152.7
27.8
1.28
0.67
3.61
7.57
2.3.2 USPTO hi-tech patents / pop
2.3.1A EPO patents / pop
EPO hi-tech patents / pop
Empl med/hi-tech manufacturing
1.4
2.3.1
Lifelong learning
1.3
8.5
21.22
Pop with 3rd education
1.2
EU
10.26
Indicator
New S&E grads
2
1.1
No
84.7
22.44
4.1
25.4
—
37.8
3.68
—
—
4.9
15.4
2.60
—
—
—
—
3.06
7.14
9.7
7.00
6.12
MT
21.3
—
5.9
9.8
8.0
—
0.23
0.045
4.1
—
4.1
0.05
2.3
—
0.25
0.45
—
7.54
5.2
11.73
5.90
PL
17.7
—
2.2
4.5
—
—
—
—
—
—
—
0.04
0.9
—
0.30
0.10
1.43
4.91
1.1
9.97
—
RO
15.5
—
4.7
30.0
24.0
—
—
0.150
3.9
—
16.9
0.50
20.6
—
0.83
0.68
2.71
8.74
3.7
14.12
13.10
SI
—
SK
24.2
—
7.5
16.7
—
—
—
—
—
—
—
0.19
5.9
—
0.45
0.24
3.03
6.75
—
10.66
european innovation scoreboard 2002
29.1
—
7.9
7.2
2.0
—
—
0.624
—
—
—
—
2.5
—
0.20
0.29
2.19
1.72
16.3
18.15
5.52
LV
Annex Table E: European Innovation Scoreboard 2002 Candidate Countries 1
4.7
6.55
3.6
3.8
—
9.4
0.69
0.130
—
18.0
24.6
0.02
—
0.06
0.27
0.53
—
1.19
3.2
8.00
5.47
TR
22
european innovation scoreboard 2002
Lifelong learning
Empl med/hi-tech manufacturing
Empl hi-tech services
Public R&D / GDP
Business R&D / GDP
1.3
1.4
1.5
2.1
2.2
SMEs innov co-op
Innovation exp
Hi-tech venture capital / GDP
3.2
3.3
4.1
1: Indicators 2.3.1A, 4.4A and 4.6A are alternative indicators.
2: Unweighted average of last two years.
4.6A Inward FDI / GDP
Manuf hi-tech value-added share
4.6
2000
2000
2001
ICT expenditures / GDP
—
4.5
Home Internet access / household
4.4
—
2001
New-to-market prod
4.3
—
—
—
—
—
4.4A Home Internet access / pop
New capital
4.2
2
SMEs innov in-house
1997
2.3.2 USPTO hi-tech patents / pop
3.1
2000
EPO patents / pop
2.3.1A
—
EPO hi-tech patents / pop
2.3.1
2000
2000
2001
2001
—
2001
Pop with 3rd education
1.2
BG
2000
Indicator
New S&E grads
1
1.1
No
2000
—
—
2001
—
—
—
—
—
—
—
—
2000
—
1999
1999
2001
2001
2000
2001
—
CY
2000
—
2001
2001
—
—
—
1999
—
—
—
2000
2000
—
2000
2000
2001
2001
—
2001
1999
CZ
2000
—
2001
2001
2001
2000
—
—
2000
2000
2000
—
2000
—
2000
2000
2001
2001
2001
2001
2000
EE
2000
2000
2001
2001
2000
—
—
2001
—
—
—
2000
2000
2000
2000
2000
2001
2001
2001
2001
1999
HU
2000
1999
2000
2001
2001
—
—
2001
—
1998
1998
1998
2000
—
2000
2000
2001
2001
2001
2001
2000
LT
2000
—
2000
2001
2000
—
—
2001
—
—
—
—
2000
—
2000
2000
2001
2001
2001
2001
2000
LV
2000
1998
2000
2001
—
2000
00/01
—
—
1998
1998
2001
—
—
—
—
2001
2001
2001
2001
2000
MT
2000
—
2001
2001
2001
—
99/00
1999
1999
—
1999
2000
2000
—
2000
2000
—
1999
2001
2001
1999
PL
2000
—
2001
2001
—
—
—
—
—
—
—
1995
2000
—
1999
1999
2001
2001
2001
2001
—
RO
2000
—
2001
2001
2001
—
—
1999
1999
—
1999
2000
2000
—
1999
1999
2001
2001
2001
2001
1999
SI
2000
—
2001
2001
—
—
—
—
—
—
—
1999
2000
—
2000
2000
2001
2001
—
2001
—
SK
Annex Table F: European Innovation Scoreboard 2002 Most recent years used (Candidate Countries)
december 2002
2000
2000
2001
2001
—
1997
00/01
2001
—
1997
1997
1997
—
1998
2000
2000
—
2000
1996
1999
1995
TR
23
5.4
97.2
Lifelong learning
Empl med/hi-tech manufacturing
Empl hi-tech services
Public R&D / GDP
Business R&D / GDP
1.3
1.4
1.5
2.1
2.2
2.3.1 EPO hi-tech patents / pop
SMEs innov co-op
Innovation exp
Hi-tech venture capital / GDP
New capital
New-to-market prod
Home Internet access / household
3.2
3.3
4.1
4.2
4.3
4.4
Manuf hi-tech value-added share
4.6
99.3
23.2
14.8
155.3
271.4
—
—
—
—
—
—
43.9
—
-2.0
18.3
-2.1
180.9
25.8
17.5
226.1
—
—
—
—
—
—
—
—
—
—
-37.4
11.5
—
—
—
17.8
7.2
BG
-3.3
—
—
99.1
—
—
—
—
—
—
—
—
—
—
—
—
24.3
-4.6
—
16.4
—
CY
86.8
—
33.8
154.2
—
—
—
—
—
—
—
—
—
—
12.9
26.0
-0.1
5.1
—
7.1
—
CZ
117.1
—
13.8
148.8
—
—
—
—
—
—
—
—
—
—
26.0
-2.8
22.8
20.0
-7.0
-0.1
38.2
EE
25.1
18.3
32.2
199.0
175.3
—
—
97.7
—
—
—
-39.3
—
9.6
26.4
10.5
17.5
6.6
-1.1
5.7
-14.4
HU
89.0
—
—
189.4
—
—
—
6.0
—
—
—
—
—
—
-30.4
17.9
-11.9
-15.4
-7.5
7.4
53.2
LT
26.5
—
—
89.5
—
—
—
—
—
—
—
—
—
—
83.7
-14.6
8.4
105.7
7.9
4.2
0.1
LV
97.4
-5.6
—
255.2
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
1.3
MT
83.6
—
40.5
106.3
—
—
—
—
—
—
—
49.9
—
—
-14.0
5.9
—
—
—
0.4
—
PL
70.2
—
34.7
83.7
—
—
—
—
—
—
—
—
—
—
-43.6
-34.1
-8.6
-21.4
22.2
14.2
—
RO
28.1
—
22.6
164.3
—
—
—
—
—
—
—
-40.1
—
—
9.7
-10.5
30.4
1.6
—
-1.1
—
SI
195.1
—
38.9
63.7
—
—
—
—
—
—
—
—
—
—
-30.3
-27.0
10.5
2.1
—
8.2
—
SK
34.3
37.0
1.9
153.3
—
—
—
—
—
—
—
—
—
—
85.8
57.8
—
2.0
—
—
—
TR
december 2002
european innovation scoreboard 2002
1: Trends are calculated as the percentage change between the last year for which data are available and the average over the preceding three years, after a one-year lag. Due to short time series, for some indicators a different average has been used.
2: Indicators 2.3.1A, 4.4A and 4.6A are alternative indicators.
4.6A Inward FDI / GDP
ICT expenditures / GDP
4.5
4.4A Home Internet access / pop
SMEs innov in-house
USPTO hi-tech patents / pop
3.1
2.3.2
2.3.1A EPO patents / pop
17.9
Pop with 3rd education
1.2
21.4
13.7
New S&E grads
EU
1.1
No. 2 Indicator
Annex Table G: European Innovation Scoreboard 2002 Trends (Candidate Countries) 1
Technical Annex
december 2002
european innovation scoreboard 2002
A.1 Calculating averages
•
For most indicators the EU mean is
calculated as a weighted average, i.e. by
summing the numerator and denominator
across all EU countries. For indicator 1.1,
however, the EU mean is calculated as an
unweighted average, i.e. as the average of
the indicator values of the EU countries.
•
The aggregate trend per country is
calculated as the unweighted average of
the trend values of the various indicators.
•
The EU trend per indicator is calculated as
the trend growth rate of the weighted EU
mean. The aggregate EU trend is
calculated as the unweighted average of
the aggregate trends of the EU countries.
1997 to 1999 inclusive. The results for 2000
are excluded in order to provide a one-year lag.
There are several exceptions to this rule due to
a lack of adequate data. Technical Paper No 1:
Member States and Associate Countries, and
Technical Paper No 2: Candidate Countries, provide the specific years used to calculate the trends
for each indicator per country.
A.3 Definition of RRSII
The Revealed Regional Summary Innovation Index tries to take into account both the region’s
innovative performance relative to the EU mean
and the region’s relative performance within the
country. For this two indices are calculated of
which the mean value is then taken to give the
RRSII:
A.2 Calculating trend data
Trends are calculated as the percentage change
between the last year for which data are available and the average over the preceding three
years, after a one-year lag. The three-year average is used to reduce year-to-year variability;
the one-year lag is used to increase the difference between the average for the three base
years and the final year and to minimise the problem of statistical/sampling variability.
•
The average of the indicator values
indexed to the country mean (RNSII:
Regional National Summary Innovation
Index).
•
The average of the indicator values
indexed to the EU mean (REUSII:
Regional European Summary Innovation
Index).
For example, when the most recent data are for
2001, the trend is based on the percentage
change between 2001 and the average for
The RRSII is thus calculated as the average of
the RNSII and the REUSII.
More detailed explanations on methodological questions can be found in Technical Paper N°6
“Methodological Report”. This paper is available from www.cordis.lu/trendchart
24
Technical Paper
Indicators and Definitions
population)
2.3.2 USPTO high-tech patent applications per
million population
And one alternative indicator for the Candidate countries:
2.3.1A All EPO patent applications (per million
population) (replacing EPO high-tech patent
applications)
The data sources are also indicated with each graph
(mostly EUROSTAT). For Accession and Candidate
countries most data comes from a survey conducted
especially for the 2002 EIS in co-operation with the
“Group of Senior Officials in Innovation Policy”. This
national data is used wherever EUROSTAT data is
not yet available.
The EIS indicators are divided into four categories,
containing 17 main indicators and 3 additional indicators for the Candidate countries, all selected to summarise the main drivers and outputs of innovations:
•
knowledge, comprising 3 main indicators:
3.1
3.2
1.1
3.3
1.2
1.3
•
New capital raised on stock markets (% of
GDP)
4.3
“New to market” products (% of sales by
manufacturing firms)
Home Internet access (% of all households)
4.5
ICT expenditures (% of GDP)
4.6
Percentage of manufacturing value-added
Employment in medium-high and high-tech
Employment in high-tech services (% of total
The creation of new knowledge, comprising 3
EPO and USPTO patents:
Public R&D expenditures (GERD - BERD)
(% GDP)
2.2
4.2
4.4
main indicators of which one is divided into
2.1
GDP)
Participation in lifelong learning (% of 25-64
workforce)
•
High-tech venture capital investment (‰ of
64 years age classes)
manufacturing (% of total workforce)
1.5
Innovation finance, outputs and markets,
comprising 6 main indicators:
Population with tertiary education (% of 25-
year olds)
1.4
Innovation expenditures (% of all turnover in
manufacturing)
New S&E graduates (‰ of 20-29 years age
class)
Manufacturing SMEs involved in innovation
co-operation
Human resources for innovation, comprising
5 main indicators:
SMEs innovating in-house (% of
manufacturing SMEs)
4.1
•
The transmission and application of
Business expenditure on R&D (BERD) (%
GDP)
european innovation scoreboard 2002
The European Innovation Scoreboard 2002
is complemented by six Technical Papers
(see page 6). This Technical Paper No 4: Indicators and Definitions presents the full definitions of all
indicators, years used, a brief interpretation justifying
why the indicator has been selected, and indicator
graphs showing the EIS 2002 figures for all countries.
2.3.1 EPO high-tech patent applications (per million
december 2002
Introduction
from high technology
And two alternative indicators for the Candidate
countries:
4.4A Internet access (% of population) (replacing
home Internet access per household)
4.6A Stock of inward FDI (% of GDP) (replacing
percentage of manufacturing value-added
from high technology)
For each indicator the following pages will provide
the full definition, a brief interpretation and indicator
graphs showing the EIS 2002 performance of all
countries.
25
1 Human Resources
Definition
1.1 New S&E graduates (‰ of 20 - 29 years age class)
The reference population is all age classes between 20 and 29
years inclusive. Tertiary graduates in Science & Engineering
(S&E) are defined as all post-secondary education graduates
(ISCED classes 5a and above) in life sciences (ISC42), physical
sciences (ISC44), mathematics and statistics (ISC46), computing (ISC48), engineering and engineering trades (ISC52),
manufacturing and processing (ISC54) and architecture and
building (ISC58). Due to a change in definition a comparison
with the 2001 Scoreboard results is not possible. This indicator is identical to Structural indicator 2.4: Science and technology graduates.
23.2
16.2
20
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
17.8
25
18.7
12.5
10.2
9.3
4.5
4.0
HU
5.5
4.7
LV
1.8
2.5
BG
5.9
5.5
PL
6.8
6.1
MT
Interpretation
3.8
5
7.9
8.4
5.6
I
6.2
5.8
NL
8.2
7.1
8.3
9.7
10.3
11.6
10
13.1
15
9.9
european innovation scoreboard 2002
1.1 New S&E graduates (‰ of 20-29 years age class)
CZ
TR
EE
SI
LT
JP
US
CH
IS
NO
L
EU
EL
P
A
D
B
DK
E
S
UK
FIN
F
IRL
december 2002
0
Sources: EUROSTAT, Education statistics; GSO survey for CH, BG, EE, HU, LT, LV, MT and TR; years used: 2000 for all countries, except
1999 for CZ, DK, F, FIN, HU, I, PL and SI, 1996 for JP, 1995 for TR, and 1993 for EL.
1.2
Population with tertiary education (% of 25-64 years age classes)
Definition
1.2 Population with tertiary education (% of 25 - 64 years age class)
45.0
36.5
Interpretation
8.0
10
7.0
10.7
10.0
SK
RO
11.6
14.0
11.7
PL
HU
CZ
14.1
18.1
29.4
23.8
23.8
25.4
29.9
33.8
21.2
10.2
P
14.5
10.3
15
I
23.0
22.2
F
IRL
18.3
23.1
E
20
17.1
24.0
23.8
D
25
NL
25.4
B
26.5
28.6
27.8
UK
30
29.7
35
32.5
40
The percentage of the total working age population (25-64
years age classes) with some form of post-secondary education (ISCED 5 and 6).
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
SI
45
21.3
50
5
TR
MT
LV
BG
EE
CY
LT
JP
US
IS
CH
NO
EU
A
L
EL
DK
CH
S
FIN
0
Sources: EUROSTAT, Labour Force Survey; GSO survey for CH and MT; years used: 2001 for all countries, except 2000 for D, JP, L,
S and US, 1999 for TR, and 1997 for IRL.
26
The indicator is a measure of the supply of new graduates with
training in Science & Engineering (S&E). Due to problems of
comparability for educational qualifications across countries,
this indicator uses broad educational categories. This means
that it covers everything from graduates of one-year diploma
programmes to PhDs. A broad coverage can also be an advantage, since graduates of one-year programmes are of value to
incremental innovation in manufacturing production and in
the service sector.
This is a general indicator of the supply of advanced skills. It is
not limited to science and technical fields because the adoption of innovations in many areas, particularly in the service
sectors, depends on a wide range of skills. Furthermore, it includes the entire working age population, because future
economic growth could require drawing on the non-active
fraction of the population. International comparisons of educational levels, however, are notoriously difficult due to large
discrepancies in educational systems, access, and the level of
attainment that is required to receive a tertiary degree. Therefore, differences among countries should be interpreted cautiously.
Participation in lifelong learning (% of 25-64 year olds)
The reference population is all age classes between 25 and 64
years inclusive. A reference period of four weeks has been chosen in order to avoid distortion of information due to recall
problems. The reference period is the last four weeks preceding the survey, except for France, The Netherlands (until 1999)
and Portugal for which information is collected only if education or training is under way on the date of the survey. Education includes initial education, further education, continuing
or further training, training within the company, apprenticeship, on-the-job training, seminars, distance learning, evening
classes, self-learning, etc., as well as other courses followed for
general interest: language, data-processing, management, art/
culture, health/medicine courses. Before 1998, education was
related only to education and vocational training which was
relevant for the current or possible future job of the respondent. This indicator is identical to Structural indicator 1.7.
30
23.5
3.1
3.0
3.7
3.2
5.3
5.2
3.7
8.5
1.1
2.7
1.4
4.7
3.3
5.2
5
5.1
5.2
7.3
5.3
7.8
9.7
15
10
16.3
14.2
16.3
18.3
20.8
20
19.3
21.7
25
21.6
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
RO
CY
HU
TR
SI
LT
PL
EE
LV
MT
NO
IS
CH
EU
F
EL
P
E
I
D
IRL
L
B
A
NL
DK
FIN
S
UK
0
Sources: EUROSTAT, Labour Force Survey; GSO survey for CH, LV, MT and TR; years used: 2001 for all countries, except 2000 for
CY, 1999 for CH, 1997 for A and IRL, and 1996 for TR.
1.4
Interpretation
A central characteristic of a knowledge economy is continual
technical development and innovation. Under these conditions, individuals need to continually learn new ideas and skills
- or to participate in lifelong learning. All types of learning are
valuable, since it prepares people for “learning to learn”. The
ability to learn can then be applied to new tasks with social or
economic benefits. The limitation of the indicator to a brief
window of four weeks could reduce comparability between
countries due to differences in adult education systems. Little
is known at this time about such differences, but differences in
the timing of national holidays, preferred times for adult education courses, the average length of adult courses, and other
unknown factors could influence the results and reduce comparability. Technical Paper No 5 of the 2002 EIS further elaborates on the issue of “Lifelong Learning for Innovation”.
european innovation scoreboard 2002
Definition
1.3 Participation in life-long learning (% of 25 - 64 years age class)
december 2002
1.3
Employment in medium-high and high-tech manufacturing
(% of total workforce)
Definition
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
The medium-high and high technology sectors include chemicals NACE (24), machinery (NACE 29) office equipment (NACE
30), electrical equipment (NACE 31), telecom equipment
(NACE 32), precision instruments (NACE 33), automobiles
(NACE 34), and aerospace and other transport (NACE 35). The
total workforce includes all manufacturing and service sectors.
7.1
1.4 Employment in medium-high and high-tech manufacturing (% of total workforce)
Interpretation
1.0
CY
1.7
1.2
TR
2
1.8
2.0
L
3.2
4.8
EE
5.5
4.9
4.2
3.6
2.2
4
EL
4.3
6
RO
6.8
8.7
7.5
8.1
7.6
6.5
A
5.5
6.6
B
7.2
7.0
7.3
7.2
7.4
8
7.4
7.9
9.2
10
8.8
12
11.2
14
The percentage of employment in medium-high and high
technology manufacturing sectors is an indicator of the share
of the manufacturing economy that is based on continual
innovation through creative, inventive activity. The use of total
employment gives a better indicator than using the share of
manufacturing employment alone, since the latter will be affected by the hollowing out of manufacturing in some countries.
LV
LT
BG
SK
MT
SI
PL
CZ
HU
IS
CH
NO
EU
P
NL
E
F
DK
UK
IRL
I
FIN
S
D
0
Sources: EUROSTAT, Labour Force Survey; GSO survey for MT, PL and TR; years used: 2001 for all countries, except 2000 for S and
TR, and 1999 for PL.
27
1.5
Employment in high-tech services (% of total workforce)
Definition
1.5 Employment in high-tech services (% of total workforce)
1.4
1.8
1.7
1.4
2
2.0
2.2
2.7
3.0
2.6
2.7
3.4
3.2
A
3.1
3.0
I
3.2
Interpretation
3.6
3.1
3.1
L
3.2
3
This indicator focuses on three leading edge sectors that produce high technology services: post and telecommunications
(NACE 64); information technology including software development (NACE 72); and R&D services (NACE 73). The total
workforce includes all manufacturing and service sectors.
4.1
4.4
4.1
4.1
4.2
4.1
4.4
4
The high technology services both provide services directly to
consumers, such as telecommunications, and provide inputs
to the innovative activities of other firms in all sectors of the
economy. The latter can increase productivity throughout
the economy and support the diffusion of a range of innovations, particularly those based on ICT.
1
RO
LT
CY
SI
LV
SK
BG
CZ
MT
EE
HU
CH
IS
NO
EU
P
EL
E
D
F
B
NL
IRL
UK
FIN
S
0
DK
european innovation scoreboard 2002
december 2002
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
4.8
5.1
5
4.9
5.5
6
Sources: EUROSTAT, Labour Force Survey; GSO survey for MT; years used: 2001 for all countries, except 2000 for S.
2 Knowledge creation
2.1
Public R&D expenditures (GERD - BERD) (% GDP)
Definition
2.1 Public R&D expenditures (GERD - BERD) (% of GDP)
The indicator is the percentage of GDP due to public R&D
spending. The latter is defined as the difference between total
R&D expenditures (GERD) and business enterprise expenditures (BERD). It thus includes higher education expenditure in
R&D (HERD), government expenditure in R&D (GORD) and
private non-profit expenditure in R&D (PNRD). Note that this
definition has changed compared to the 2001 EIS as it now
also includes private non-profit expenditure in R&D (PNRD).
This indicator was identical to the initial Structural indicator
2.2: R&D expenditure. The definition of Structural indicator
2.2 was changed in October 20021 : the R&D indicators are
now disaggregated by source of finance rather than the sector
carrying out the R&D expenditure. This change in definition
could not be taken into account in the 2002 EIS due to time
constraints.
1.04
Low (Below 20% of EU mean)
0.87
0.10
0.20
0.20
0.45
0.29
0.24
0.40
0.41
0.53
0.45
0.53
0.53
0.44
0.54
0.66
0.68
0.75
0.67
0.80
High (Over 20% of EU mean)
Average
0.33
0.48
0.56
0.53
0.60
0.58
0.66
0.65
0.75
0.80
0.72
0.88
0.77
0.94
1.00
0.98
1.20
Interpretation
RO
CY
SK
LV
HU
BG
PL
EE
LT
TR
SI
CZ
JP
US
NO
IS
CH
EU
E
IRL
EL
I
B
P
A
UK
D
DK
F
NL
S
FIN
0.00
Sources: EUROSTAT, R&D statistics; GSO survey for CH, IS, BG, CZ, EE, HU, LT, LV and TR; years used: 2001 for D, E, FIN, IS, UK, 2000
for BG, CH, CZ, DK, EE, F, HU, JP, LT, LV, PL, SK, TR and US, 1999 for B, CY, EL, I, IRL, NL, NO, P, RO, S and SI, and 1998 for A.
In addition to the production of basic and applied knowledge
in universities and higher education institutions, publicly
funded research offers several other outputs of direct importance to private innovation: trained research staff and new
instrumentation and prototypes.
1
28
COM(2002): 551.
2.2 Business expenditure on R&D (BERD) (% GDP)
This indicator measures the R&D expenditure (from all sources
of funding) of the business sector (manufacturing and services) as a percentage of GDP. This indicator was identical to the
initial Structural indicator 2.2: R&D expenditure. The definition of Structural indicator 2.2 was changed in October 20021 :
the R&D indicators are now disaggregated by source of finance rather than the sector carrying out the R&D expenditure. This change in definition could not, due to time constraints, be taken into account in the 2002 EIS.
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
2.68
3.00
2.84
3.50
0.07
0.05
LT
CY
0.15
0.11
BG
0.25
0.20
0.30
0.45
0.27
0.83
The indicator captures the formal creation of new knowledge
within firms. It is particularly important in the science-based
sectors (pharmaceuticals, chemicals and some areas of electronics) where most new knowledge is created in or near R&D
laboratories.
0.81
0.36
0.19
0.50
0.17
0.53
0.52
1.00
2.11
2.04
1.86
0.95
1.14
1.28
Interpretation
0.88
1.21
1.14
1.50
1.36
1.45
2.00
1.32
1.80
1.95
2.50
1
EE
LV
PL
TR
RO
SK
HU
SI
CZ
JP
US
NO
IS
CH
EU
P
EL
I
E
A
IRL
NL
UK
F
DK
B
D
S
FIN
0.00
COM(2002): 551.
Sources: EUROSTAT, R&D statistics; GSO survey for CH, IS, BG, CZ, EE, HU, LT, LV and TR; years used: 2001 for D, E, FIN, IS, UK, 2000
for B, BG, CH, CZ, DK, EE, F, HU, JP, LT, LV, PL, SK, TR and US, 1999 for CY, EL, IRL, NL, NO, P, RO, S and SI, and 1998 for A.
european innovation scoreboard 2002
Definition
2.2 Business expenditures on R&D (BERD) (% of GDP)
Interpretation
2.3.1 EPO high tech patent applications (per million population)
160
140
137.6
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
120
This indicator complements indicator 2.2 on business R&D in
that patenting captures new knowledge created anywhere
within a firm and not just within a formal R&D laboratory. The
indicator also measures specialisation of knowledge creation
in fast-growing technologies.
december 2002
2.3.1 EPO high-tech patent applications (per million population)
95.1
100
80
57.9
60
49.5
49.0
43.7
40
32.2
36.6
27.8 27.5 25.3
20
27.8
21.9 19.8
17.0
15.2
6.2
3.1 0.9 0.6
2.6 1.5 0.1
0
FIN
S
NL
D
DK
F
UK IRL
B
L
A
I
E
P
EL
EU
IS
NO
US
JP
MT HU TR
Sources: EUROSTAT; GSO survey for HU, MT and TR; years used: 2000 for all countries, except 1999 for MT, and 1998 for TR.
Definition
The indicator is defined as the number of patent applications
(reference year is year of filing) at the EPO in high-technology
patent classes per million population. The national (and regional) distribution of the patent applications is assigned according to the address of the inventor. The high technology
patent classes include pharmaceuticals, biotechnology, information technology, and aerospace. The following IPC subclasses are included:
• B41J: typewriters; selective printing mechanisms, i.e.
mechanisms printing otherwise than from a form;
correction of typographical errors
• G06C: digital computers in which all the computation
is effected mechanically
• G06D: digital fluid-pressure computing devices
• G06E: optical computing devices
• G06F: electric digital data processing
• G06G: analogue computers
• G06J: hybrid computing arrangements
• G06K: recognition of data; presentation of data; record
carriers; handling record carriers
•
•
•
•
•
•
•
•
•
•
•
•
G06M: counting mechanisms; counting of objects not
otherwise provided for
G06N: computer systems based on specific
computational models
G06T: image data processing or generation, in general
G11C: static stores
B64B: lighter-than-air aircraft
B64C: aeroplanes; helicopters
B64D: equipment for fitting in or to aircraft; flying
suits; parachutes; arrangements or mounting of power
plants or propulsion transmissions
B64F: ground or aircraft-carrier-deck installations
B64G: cosmonautics; vehicles or related equipment
C12M: apparatus for enzymology or microbiology
C12N: micro-organisms or enzymes; compositions
thereof; propagating, preserving, or maintaining
micro-organisms; mutation or genetic engineering;
culture media
C12P: fermentation or enzyme-using processes to
synthesise a desired chemical compound or
composition or to separate optical isomers from a
racemic mixture
•
•
•
•
•
•
•
•
•
•
•
•
•
C12Q: measuring or testing processes involving
enzymes or micro-organisms
H01S: devices using stimulated emission
H01L: semiconductor devices; electric solid state
devices not otherwise provided for
H04B: transmission
H04H: broadcast communication
H04J: multiplex communication
H04K: secret communication; jamming of
communication
H04L: transmission of digital information, e.g.
telegraphic communication
H04M: telephonic communication
H04N: pictorial communication, e.g. television
H04Q: selecting
H04R: loudspeakers, microphones, gramophone pickups or similar acoustic electromechanical transducers;
deaf-aid sets; public address systems
H04S: stereophonic systems
29
2.3.1A EPO patent applications (per million population)
Definition
2.3.1A EPO patent applications (per million population)
The indicator is defined as the number of all patent applications at the EPO per million population. The national (and
regional) distribution of the patent applications is assigned
according to the address of the inventor.
180
160
152.7
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
Interpretation
This indicator complements indicator 2.2 on business R&D in
that patenting captures new knowledge created anywhere
within a firm and not just within a formal R&D laboratory.
120
100
Candidate countries
80
This indicator is used as an alternative for indicator 2.3.1 as the
numbers for high-technology EPO patent applications are too
small.
60
40
20.6
16.1
20
12.1
6.9
6.0
5.9
3.2
2.5
2.3
1.1
0.9
0
EU
SI
HU
CZ
EE
CY
SK
BG
LV
PL
LT
RO
Source: EUROSTAT; years used: 2000 for all countries.
december 2002
european innovation scoreboard 2002
140
2.3.2 USPTO high-tech patent applications per million population
Definition
2.3.2 USPTO high-tech patent applications (per million population)
The indicator is defined as the number of patent applications
at the US Patent and Trade Mark Office (USPTO) in high-technology patent classes, per million population. The high technology patent classes are the same as those for indicator 2.3.1.
110
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
91.9
100
80.0
90
80
Interpretation
Indicator 2.3.1 on EPO patent applications favours European
versus American and Japanese firms. The present indicator provides the equivalent for American firms and measures US
patenting activity by European inventors.
70
47.3
50
41.6
60
21.5
21.2
IS
CH
0.1
0.1
0.0
0.0
BG
PL
RO
TR
0.3
0.2
SK
SI
HU
0.5
0.5
LT
2.6
0.6
MT
JP
US
NO
CZ
8.3
12.4
0.0
P
A
NL
DK
S
FIN
0
EU
1.4
0.4
E
I
EL
4.6
4.1
L
8.1
6.1
10
IRL
14.0
13.9
F
B
16.4
15.1
D
20
UK
22.7
30
18.6
40
Sources: USPTO; GSO survey for CH and MT; years used: 2000 for all countries, except 2001 for MT, 1999 for SK, 1998 for LT, 1997
for BG and TR, and 1995 for RO.
30
3 Transmission and application of knowledge
Definition
3.1 SMEs innovating in-house (% of manufacturing SMEs)
64.3
Innovative manufacturing firms are defined as those who introduced new products or processes either:
• In-house or
• In combination with other firms.
Note: This indicator does not include new products or processes developed by other firms (option 1 in the CIS questionnaires; compare question 2 in the CIS 2 questionnaire and
question 2.1 in the CIS 3 questionnaire). Only SMEs with 20249 employees are taken into account in CIS 2. Small and
medium-sized enterprises (SMEs) are characterised as those
enterprises with 20-249 employees.
51.0
44.7
24.6
16.9
Interpretation
15.4
E
33.2
36.9
44.0
P
20
20.1
21.8
21.6
24.5
30
27.4
29.4
40
35.8
36.0
44.8
50
44.4
51.0
59.0
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
58.7
62.2
60
59.1
70
4.1
10
0
IRL
A
DK
D
NL
S
I
F
UK
B
FIN
L
EL
EU
CH IS
NO
LT EE
TR
SI
MT PL
Sources: EUROSTAT, Community Innovation Survey; GSO survey for CH, IS, NO, EE, LT, MT and TR; years used: 1996 for all countries,
except 2000 for EE, 1999 for CH, LT, PL and SI, 1998 for E, EL, IS, MT and NL, and 1997 for NO and TR. Note that this indicator
has not been updated in the 2002 Scoreboard for the Member States, as results from CIS3 are not yet available.
3.2
The CIS defines innovative manufacturing firms quite broadly
as those who introduced new products or processes developed by 1) other firms, 2) in-house, or 3) in combination with
other firms. The present indicator is more focused in two respects. It is limited to SMEs because almost all large firms innovate and because countries with an industrial structure
weighted to larger firms would tend to do better. And it is
limited to firms with in-house innovative activities that either
develop product or process innovations themselves or in combination with other firms.
european innovation scoreboard 2002
SMEs innovating in-house (% of manufacturing SMEs)
december 2002
3.1
Manufacturing SMEs involved in innovation co-operation
Definition
3.2 SMEs involved in innovation co-operation (% of manufacturing SMEs)
The indicator is the percentage of all manufacturing SMEs (including non-innovators) with 20 or more employees that had
any co-operation agreements on innovation activities with
other enterprises or institutions in the three years before the
survey (compare question 11 in the CIS 2 questionnaire and
question 8.1 in the CIS 3 questionnaire).
37.4
35
P
13.0
4.9
I
12.0
18.0
Interpretation
11.2
4.7
5
4.5
7.0
6.5
9.6
10
8.9
12.9
12.0
15
14.7
15.7
20
13.8
19.9
25
22.7
23.2
30
18.8
27.5
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
20.5
40
0
DK
S
IRL FIN UK
D
NL
A
F
L
B
E
EL
EU
IS
NO CH
TR
EE
LT
MT
Complex innovations, particularly in ICT, often depend on the
ability to draw on diverse sources of information and knowledge, or to collaborate on the development of an innovation.
This indicator measures the flow of knowledge between public
research institutions and firms and between firms and other
firms. The indicator is limited to SMEs because almost all large
firms are involved in innovation co-operation. This indicator
also captures technology-based small manufacturing firms,
since most are involved in co-operative projects. However, the
indicator will miss high-technology firms with no product
sales, such as many biotechnology firms, because these firms
are assigned to the service sector.
Sources: EUROSTAT, Community Innovation Survey; GSO survey for CH, IE, NO, EE, LT, MT and TR; years used: 1996 for all countries,
except 2000 for EE, 1999 for CH, 1998 for E, EL, IS, LT, MT and NL, and 1997 for NO and TR. Note that this indicator has not been
updated in the 2002 Scoreboard for the Member States, as results from CIS3 are not yet available.
31
3.3
Innovation expenditures (% of all turnover in manufacturing)
Definition
3.3 Innovation expenditures (% of all turnover in manufacturing)
9
This indicator includes all manufacturing firms with 20 or more
employees. Innovation expenditures include the full range of
innovation activities: in-house R&D, extramural R&D, machinery and equipment linked to product and process innovation,
spending to acquire patents and licences, industrial design,
training, and the marketing of innovations. Total innovation
expenditure by all firms in each country is divided by total
turnover. This includes firms that do not innovate, whose innovation expenditures are zero by definition (compare question 6 in the CIS 2 questionnaire and question 4.1 in the CIS
3 questionnaire).
8.5
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
8
7.0
december 2002
european innovation scoreboard 2002
7
6
4.8
5
4.3
3.9
4
4.1
3.9
3.8
3.5
3.7
3.3
3.9
3.2
3
2.6
2.7
2.4
2.4
2.1
2
1.7
1.6
1
0
S
DK
FIN
D
F
NL
A
IRL
UK
I
E
B
P
EL
EU
CH
NO
PL
SI
EE
Sources: EUROSTAT, Community Innovation Survey; GSO survey for CH, NO and EE; years used: 1996 for all countries, except 2000
for EE, 1999 for CH, PL and SI, 1998 for D, E and EL, and 1997 for NO. Note that this indicator has not been updated in the 2002
Scoreboard for the Member States, as results from CIS3 are not yet available.
Several of the components of innovation expenditure, such as
investment in equipment and machinery and the acquisition
of patents and licences, measure the diffusion of new production technology and ideas. Overall, the indicator measures
total expenditures on many different activities of relevance to
innovation. The indicator partly overlaps with indicator 2.2
on R&D expenditures. A better version would exclude R&D,
but concerns over data reliability have prevented this option.
4 Innovation finance, output and markets
4.1
High-tech venture capital investment (‰ of GDP)
Definition
4.1 High technology venture capital investment (‰ of GDP)
The percentage of GDP due to venture capital in high technology firms active in the following sectors: computer related
fields, electronics, biotechnology, medical/health, industrial
automation, financial services. Venture capital is the sum of
early stage capital (seed and start-up) plus expansion capital.
1.100
0.900
0.900
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
1.000
0.800
0.624
The data for this indicator were taken from EVCA’s “Mid-Year
Survey of Pan-European Private Equity & Venture Activity”.
More recent data for high-tech venture investments including replacement and buyout capital are available in EVCA’s
“Yearbook: Annual Survey of Pan-European Private Equity &
Venture Capital Activity”. The Yearbook, however, does not
provide disaggregated data to calculate high-tech venture
capital investments according to the EIS definition and these
data have thus not been used.
0.021
0.045
0.035
0.150
0.130
0.239
0.486
0.326
0.242
0.034
0.139
0.100
0.068
0.188
0.160
0.228
0.200
0.197
0.236
0.300
0.235
0.309
0.440
0.400
0.386
0.500
0.457
0.600
0.567
0.700
0.000
FIN DK
B
S
IRL
F
UK NL
I
E
EL
A
D
P
EU
IS NO CH
LT LV
SI
TR PL HU CZ
Sources: European Private Equity & Venture Capital Association (EVCA); GSO survey for HU, LT, LV and TR; years used: 2001 for
all countries, except 2000 for D, and 1999 for CZ, PL and SI.
32
Interpretation
Interpretation
One of the main barriers to innovation is the ability of new
technology-based firms to raise adequate funding. This indicator measures the supply of private venture capital to these
firms. The total supply of capital will be higher because of bank
and private-placement financing. The main disadvantage is
that there are many alternative methods of financing new technology-based start-up firms that are not covered by this indicator. Firms can also go abroad to raise venture capital. An
additional concern is the lack of information on the accuracy
of the venture capital data.
New capital raised on stock markets (% of GDP)
Definition
This indicator is the amount of new capital raised by domestic
firms on domestic stock markets as a percentage of GDP. It
excludes investment funds and unit trusts. And, in order to
focus the indicator on new innovative firms, the indicator
excludes capital raised by existing firms on the main stock
exchanges. Three types of new capital are included:
• capital raised by newly-admitted firms to the main
stock exchanges
• capital raised on parallel markets by already listed firms
• capital raised on parallel markets by newly-admitted
firms.
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
7.92
10
3.68
L
E
NL
S
B
EL IRL UK
FIN
P
DK EU
CH IS
NO
US
JP
MT TR
0.23
0.81
1.19
A
0
0.69
2.53
1.73
I
0.14
F
0.38
0.67
0.60
D
0.22
0.95
0.82
1.21
2
1.01
2.37
3.07
4
1.57
6
5.17
5.97
8
0.00
12
10.81
4.2 Capital raised on parallel markets plus by new firms on main markets as a % of GDP
PL
Interpretation
New capital is a major source of investment for many firms, but
particularly for fast growing firms in high technology sectors.
The indicator is strongly influenced by volatility in capital
markets: it includes stocks that have little to do with technology. Firms raising capital in foreign markets will distort the
results.
december 2002
Source: World Federation of Stock Exchanges (FIBV); years used: average of 2000 and 2001 for all countries, except average of
1999 and 2000 for PL.
The focus on new capital that is probably raised by innovative
firms in high technology sectors differentiates this indicator
from the Structural indicator “Capital raised on stock markets”, which includes all capital raised on stock markets, including capital raised on the main markets. Parallel stock exchanges focus on high technology sectors.
european innovation scoreboard 2002
4.2
4.3
“New to market” products (% of sales by manufacturing firms)
Definition
4.3 “New to market” products (% of all turnover in manufacturing)
40
The amount of product sales (or total turnover), by manufacturing firms with more than 20 employees, from innovations
that are new to the firm’s market. These are limited to products
that are both new to the firm itself and new to the firm’s market. (Compare question 5 in the CIS 2 questionnaire and question 1.4 in the CIS 3 questionnaire).
37.8
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
35
30
Interpretation
25
20
15
13.5
9.8
10
8.4
9.4
7.9
7.3
7.2
7.1
6.9
6.9
6.7
5.6
6.5
7.2
5.1
6.0
4.1
5
2.6
3.4
This is a direct output measure of innovation that is not distorted by market speculation (as would the market value of a
firm). The product must be new to the firm, which in many
cases will also include innovations that are world firsts. The
main disadvantage is that there is some ambiguity in what
constitutes a “new to market” innovation. Smaller firms or
firms from less developed countries could be more likely to
include innovations that have already been introduced onto
the market elsewhere.
0
I
E
IRL
F
FIN
P
D
S
NL
UK
A
DK
B
EU
IS
NO
CH
MT
TR
EE
Sources: EUROSTAT, Community Innovation Survey; GSO survey for CH, IS, NO, EE, MT and TR; years used: 1996 for all countries,
except 2000 for EE, 1999 for CH and MT, 1998 for D, E and IS, and 1997 for NO and TR. Note that this indicator has not been
updated in the 2002 Scoreboard for the Member States as results from CIS3 are not yet available.
33
4.4
Home Internet access (% of all households)
Definition
4.4 Home Internet access (% of all households)
Percentage of households who have Internet access at home.
All forms of use are included. Population considered is equal
to or over 15 years old. This indicator is identical to Structural
indicator 2.3: Level of Internet access.
80
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
69.7
70
63.8
58.6
50
Interpretation
58.2
50.2
49.3
47.6 47.2
Internet use by the domestic population is a measure of the
ability to access an enormous wealth of data online, including
business-to-consumer e-commerce and government-to-citizen online services. In the future, much more sophisticated
measures of Internet use will be needed. Better data is needed
on what the Internet is used for and if the population is aware
of several efficiency enhancing uses.
46.7
43.0
38.4
40
37.7
36.4
34.0
33.5
30.1
30
26.1
24.7
24.0
20
9.9
10
9.8
8.0
3.0 3.0 2.6
0
NL
S
DK FIN UK IRL
A
L
D
B
I
F
P
E
EL
EU
IS
NO
US
JP
SI
EE
PL
LT
LV
HU
Sources: EUROSTAT/Eurobarometer; GSO survey for EE, HU and LV; years used: 2001 for all countries, except 2000 for JP, HU and
LV.
december 2002
european innovation scoreboard 2002
60.7
60
4.4A Internet access (% of population)
Definition
4.4A Internet access (% of population)
Percentage of population with any form of Internet access. All
forms of use are included. Population considered is equal to or
over 15 years old.
35
31.4
30.1
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
30.0
30
Interpretation
Internet use by the domestic population is a measure of the
ability to access an enormous wealth of data online, including
business-to-consumer e-commerce and government-to-citizen online services. In the future, much more sophisticated
measures of Internet use will be needed. Better data is needed
on what the Internet is used for and if the population is aware
of several efficiency enhancing uses.
25.4
25
22.1
20
16.7
14.8
15
13.6
9.8
10
7.5
Candidate countries
7.2
6.8
4.5
5
3.8
0
EU
EE
SI
MT
Source: EUROSTAT; years used: 2001 for all countries.
34
CY
SK
HU
CZ
PL
BG
LV
LT
RO
TR
This indicator is used as an alternative for indicator 4.4 due to
better data availability.
4.5 ICT expenditures (% of GDP)
Definition
4.5 ICT expenditures (% of GDP)
High (Over 20% of EU mean)
11
4
3.60
4.07
5
3.80
5.90
PL
4.70
5.90
LT
7.90
5.65
7.50
8.90
9.62
8.01
9.50
8.98
9.30
7.80
6.93
Interpretation
4.41
5.17
5.09
I
EL
5.44
5.23
6
IRL
6.74
6.30
7.32
7
6.89
7.42
8
7.35
8.10
9
8.30
Low (Below 20% of EU mean)
8.22
9.85
Average
8.62
10
2.20
3
2
1
TR
RO
BG
MT
SI
SK
LV
HU
CZ
EE
EU*
JP
US
NO
IS
CH
E
EU
P
A
FIN
B
D
F
DK
L
UK
S
NL
0
ICT is a fundamental feature of knowledge based economies
and the driver of current and future productivity improvements. An indicator for ICT investment is crucial for capturing
innovation in knowledge-based economies, particularly due
to the diffusion of new IT equipment, services and software.
One disadvantage of this indicator is that it is ultimately obtained from private sources (IDC), with a lack of good information on the reliability of the data. Another disadvantage is that
some expenditures are for final consumption and may have
few productivity or innovation benefits. It would be preferable
to have data on ICT investment rather than ICT expenditure,
but reliable investment data are not yet available.
december 2002
Sources: EUROSTAT; WITSA/IDC (Digital Planet) for Candidate countries and EU; GSO survey for IS and MT; years used: 2001 for
all countries, except 2000 for LT, LV, MT, JP and US.
european innovation scoreboard 2002
This indicator measures total expenditures on Information and
Communication Technology (ICT) as a percentage of GDP. ICT
includes office machines, data processing equipment, data
communication equipment, and telecommunications equipment, plus related software and telecom services. This indicator is identical to Structural indicator 2.7.
12
4.6
Percentage of manufacturing value-added from high technology
4.6 Share of manufacturing value-added in high-tech sectors
Definition
The percentage of total value-added in manufacturing in four
high technology industries: pharmaceuticals (NACE 24.4),
office equipment (NACE 30), telecommunications and related
equipment (NACE 32), and aerospace (NACE 35.3).
30
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
25.4
25
25.8
22.4 22.3
Interpretation
20
19.3
15.3 14.8
15
14.8
14.1
13.2
10.7 10.7
10
9.7
13.8
10.1
9.0
6.8 6.7
6.6
5.6 5.3
5.9
4.8
5
Value-added is the best measure of manufacturing output,
whereas other indicators such as total production can be biased by “screwdriver” plants with little value-added. The requirement for good data on value-added creates a lag of two
or more years longer than for GDP and other economic data.
The main disadvantage of the main indicator is that a hollowing-out of manufacturing, as in the UK, can lead to relatively
good results, if low and medium technology industries no
longer survive.
0
IRL FIN
S
UK
F
B
DK NL
A
I
D
E
P
EU
CH NO
US
JP
MT LT
HU TR BG
Sources: EUROSTAT, Structural Business Statistics; GSO survey for CH, NO, BG, EE, HU, LT, MT, TR; years used: 1999 for all countries,
except 2000 for BG, HU and TR, 1998 for LT and MT, and 1997 for JP and US.
35
4.6A Stock of inward FDI (% of GDP)
Definition
4.6A Inward FDI stock (% of GDP)
The indicator is defined as the stock in inward Foreign Direct
Investment (FDI) as a percentage of GDP. UNCTAD defines FDI
“as an investment involving a long-term relationship and reflecting a lasting interest and control by a resident entity in
one economy (foreign direct investor or parent enterprise) in
an enterprise resident in an economy other than that of the
foreign direct investor (FDI enterprise or affiliate enterprise or
foreign affiliate). FDI implies that the investor exerts a significant degree of influence on the management of the enterprise
resident in the other economy. Such investment involves both
the initial transaction between the two entities and all subsequent transactions between them and among foreign affiliates, both incorporated and unincorporated.”
100
90
High (Over 20% of EU mean)
Average
Low (Below 20% of EU mean)
84.7
december 2002
european innovation scoreboard 2002
80
36
70
60
53.2
50
43.4
42.6
40
30.3
29.1
30
26.4
24.2
23.7
21.3
20.6
20
17.7
Interpretation
15.5
10
4.7
0
EU
MT
EE
HU
CZ
LV
BG
SK
Source: UNCTAD (World Investment Report); years used: 2000 for all countries.
CY
PL
LT
RO
SI
TR
The inflow of FDI steers production towards higher value-added
goods, or increases production efficiency. Both can depend
on the transfer of foreign technology and provide a potential
for conducting industrial research in the host country. Stock
data are a better proxy for the rate of penetration of FDI and
also neutralise large variations in annual inflows.
Candidate countries
This indicator is used as an alternative for indicator 4.6.
For more information and free subscription see
CORDIS at:www. cordis.lu
or contact the Innovation helpdesk:
E-mail:[email protected]
© European Commission, 2002.
Reproduction is authorized, provided that the source is acknowledged.
LEGAL NOTICE: Neither the European Commission nor any person acting on behalf of the Commission is
responsible for the use which might be made of the information contained in this document.
European Commission, Enterprise Directorate-General, Communication and Awareness Unit, L-2920 Luxembourg.
15
16
NB-AH-02-S19-EN-C
EUR
OFFICE FOR OFFICIAL PUBLICATIONS
OF THE EUROPEAN COMMUNITIES
L-2985 LUXEMBOURG