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Lithuania’s Research, Development and Innovation System -
Benchmarking & Effectiveness Analysis
The World Bank1
May 2009
1 This report was prepared by Alex Ivaschenko, Economist, Europe and Central Asia Human Development (ECSHD) Division, under the guidance received from Alberto Rodriguez, Lead Education Specialist, ECSHD.
TABLE OF CONTENTS
EXECUTIVE SUMMARY:...............................................................................................................2
1. INTRODUCTION..........................................................................................................................5
2. RESEARCH, DEVELOPMENT AND INNOVATION (RDI) SYSTEM IN
LITHUANIA – SOME BASIC FACTS AND FINANCING ARRANGEMENTS.......................7
3. HOW LITHUANIA’S CURRENT RDI EFFORT COMPARES TO THAT OF
OTHER EU MEMBER COUNTRIES ON INPUTS AND OUTPUTS?.......................................9
4. EFFECTIVENESS OF THE LITHUANIA’S PUBLIC AND PRIVATE
SPENDING ON RDI – HOW WELL IS LITHUANIA DOING COMPARED TO
OTHER EU MEMBER COUNTRIES?.........................................................................................20
5. KEY CHALLENGES FACED BY THE RDI SYSTEM IN LITHUANIA............................24
6. CONCLUSIONS...........................................................................................................................25
ANNEX..............................................................................................................................................27
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Executive summary:
The objective of this report is to benchmark Lithuania’s progress and the current position in the Research, Development and Innovation (RDI) sector against that of other EU member countries. The findings of the report are based on the quantitative analysis, and are presented in a format of a policy brief. Most of the RDI indicators presented here are readily available and widely used, which makes it easy to replicate the analysis at some point in a future. At the same time, the analysis uses some econometric modeling which allows one to trace the progress of Lithuania conditional on such factors as the level of development and the size of the population.
This report also aims to complement a qualitative report that documents the progress of Lithuania in science, technology and innovation (STI). This other report summarizes recommendations of those studies, reports on the progress achieved to date, and points to priorities for the future. Hence, these two reports combined provide a policy maker with both quantitative and qualitative information on where Lithuania stands in its RDI effort, and what could be the possible future steps to improve the country’s performance on this front.
The analysis presented in the report has revealed several key findings. These findings, as well as some policy recommendations emanating from them, are formulated below:
As of 2007 Lithuania ranked 19th out of the 27 EU member countries on the Summary Innovation Index (SII). The analysis reveals that the level of Lithuania’s SII was consistent with its level of development (per capita GDP) and population size. However, much more can be done to put Lithuania’s performance above “average”. In other words, conditional on its level of development and the country’s natural circumstances, Lithuania has been doing fairly well on the innovation effort in general. Moreover, given the relatively low starting point, Lithuania shows the tendency to catch up with other EU member states. Nevertheless, more can be done to put Lithuania among “positive outliers” – countries that perform better than would be expected given their levels of development. In that regard, the example of the neighboring Estonia could be a good case to follow.
In “looking beyond averages”, or doing the analysis of the specific areas of the RDI both in terms of innovation inputs and outputs, we have identified: (i) the areas where the country is doing quite well (i.e., positives), and (ii) areas where a much more substantial effort is need to improve on things (i.e., must improvements ). In terms of positives, the following could be mentioned:
The analysis indicates that Lithuania has generally strong foundations to be a knowledge-based economy. Lithuania is positioned quite well in comparison to the EU average on the quantitative indicators related to the knowledge base (i.e., innovation inputs). In fact, it leads over the EU on the share of the science and engineering (S & E) graduates, share of population with tertiary education, and youth education attainment level. However, it lags behind on participation in life-
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long learning, and the quality of education remains an issue to be addressed. There are also some historically strong niche RDI markets, such as a semi-conductor industry, where the country may be positioned well to produce new inventions. The international studies also indicate that Lithuania is also positioned quite well in the international context on the quality of education indicators, although those studies measure the math and science capabilities of the general school students.2 According to the 2007 Trends in International Mathematics and Science Study (TIMSS), Lithuania’s 4th and 8th graders scored above international average on the mathematics test. However, the math and science scores (for pupils age 15) from the 2006 Program of International School Assessment (PISA) indicate that while Lithuania is not much lower than the EU25 averages, it is noticeably behind the leading countries in the EU. The analysis of the degree of Lithuania’s integration into the framework of the Bologna process also indicates that the country has made substantial progress, but some gaps remain.
Lithuania spends a respectful share of its GDP on the public investments in R&D. Lithuania occupies an 8th place among the EU27 member countries on the share of GDP spent on public R&D. The analysis indicates that given its level of development, Lithuania actually over performs on the public RDI spending as a share of GDP. The 2007-2013 EU Structural Funds (SF) earmarked for R&D will further substantially increase the budget envelope available for public and private R&D, and the simulations we perform indicate that these funds could give a good push for Lithuania to reach a new higher trajectory in its RDI effort.
Lithuania is doing well on the SMEs’ participation in the innovation diffusion activities. Lithuania is somewhat behind EU average on the share of Small and Medium Enterprises (SMEs) with in-house innovation activities and the SMEs innovation expenditures (as % of turnover). However, even unconditional for county circumstances, it does better than the EU average on the share of SMEs having cooperation agreements on innovation activities with other enterprises, and on the expenditures on information and communication technology (ICT) as a percent of GDP. Nevertheless, Lithuania’s SMEs are behind in the area of organizational innovation.
Lithuania performs quite well in the area of knowledge absorption and we believe that this focus should be further encouraged. We find that in absolute terms Lithuania is still behind the EU average on the adoption of new knowledge. However, conditional on its level of economic development and population size the country is doing fairly well, which is not to say that it cannot do better. The country is doing quite well on the adoption of new technology as measured by the share of exports of machinery & equipment in the total exports. The share and volume of this type of exports has also increased significantly in the last few years.
In terms of must improvements, the following should be mentioned:
2 In the absence of the data, it is not clear how Lithuania compares to other countries on the quality of university education.
3
The conditions need to be created (or improved) for the private sector R&D spending to increase. The country is currently well behind the EU average on the private sector R&D expenditures, even conditional on it’s level of development and population size. As a share of GDP, private spending accounts for only 0.2% in Lithuania versus an average of 1.2% in the EU. However, this position may well be improved wit the appropriate use of the EU Structural Funds. Various measures to improve the institutional environment and incentives for more of the private spending on RDI, such as the recently introduces tax incentives, may also be prove to performance boosters, but need to be closely monitored in terms of their impact and effectiveness.
The area where Lithuania is clearly behind the EU average is the creation of new knowledge, as evident from the intellectual property indicators. This holds true conditional on the population size and per capita. These findings suggests that while identifying and exploring some niche markets for the creation of knowledge could be a good idea for the country, Lithuania with its small size and limited resources would at present hardly be able to compete with other innovation giants across the wide spectrum of high-tech products.
In terms of the general direction of developing the RDI sector, the following could be recommended:
Lithuania would benefit significantly from having an overall RDI strategy. Such a strategy is lacking at the moment. This strategy should be linked to the country’s natural circumstances and industrial specialization. As a sister qualitative report rightly acknowledges, given the size of the economy (and population), Lithuania will always depend on its ability to learn from others and adapt technologies available elsewhere in the world to local needs. It may still choose to have concentrated knowledge production efforts, but the areas for these efforts need to be clearly defined and thought through.
A greater focus on the adoption and diffusion of the latest knowledge and technologies could be a viable strategy to go forward. On many knowledge adoption indicators Lithuania already performs at the level consistent with its spending and other input indicators. Given the country’s solid foundations for a knowledge-based economy coupled with favorable business climate and the EU support in the form of the Structural Funds for RDI, the practical and viable approach for Lithuania could be a greater focus on the adoption and diffusion of the latest knowledge available elsewhere in the world, rather than the concentrated effort on the creation of new knowledge.
In the current environment of the financial crisis, Lithuania’s reliance on the EU Structural Funds for R&D will be very important, because the public and private resources available for the sector will be significantly constrained, at least in the short term. We estimate that under the current economic forecast the total R&D spending envelope over 2008-13 would downsize by a cumulative of about EUR 335 million (compared to its total expected value under no crisis scenario).
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1. Introduction
The objective of this report is to benchmark Lithuania’s progress and the current position in the Research, Development and Innovation (RDI) sector against that of other EU member countries. The findings of the report are based on the quantitative analysis, and we try to present those findings in a user friendly and concise format. Most of the RDI indicators presented here are readily available and widely used, which makes it easy to replicate the analysis at some point in a future. At the same time, the analysis uses some econometric modeling which allows one to trace the progress of Lithuania conditional on such factors as the level of development and the size of the population.
This report also aims to complement a qualitative report that documents the progress of Lithuania in science, technology and innovation (STI) in areas singled out by three major international reports prepared by the Norwegian Research Council (1996), the World Bank (2003) and the CREST-OMC panel (2007). This other report summarizes recommendations of those studies, reports on the progress achieved to date, and points to priorities for the future. Hence, these two reports combined provide a reader with both quantitative and qualitative information on where Lithuania stands in its RDI effort, and what could be the possible future steps to improve the country’s performance on this front.
In analyzing the RDI system, we focus on the indicators that cover the following 3 key segments of the system: (i) Knowledge creation (public and private R & D and inventions); (ii) Knowledge adoption (consuming the results of domestic and foreign R&D effort/inventions; purchase of new technology & equipment); and (iii) Knowledge diffusion (the spreading of knowledge and inventions through the favorable information technologies (IT) and business environment).
The analysis presented in this report effectively tries to answer the two key questions: (i) How Lithuania’s RDI effort compares to that of other EU member countries (i.e., benchmarking)?, and (ii) Does Lithuania gets an expected return for its investments in the public RDI (compared to other EU member countries)? In other words, is the investment in public R&D effective?
The benchmarking analysis is important because it: (i) provides an opportunity to measure the country’s position relative to that of other countries, and also to capture changes over time; (ii) gives a chance to identify the areas where the largest gaps exist, and thus provides information to policy makers needed to formulate policy priorities; (iii) allows one to utilize (and distinguish among) various frameworks for benchmarking that are already there, including: (i) The Lisbon Review (Measuring Europe’s Progress in Reforms); (ii) European Innovation Scoreboard (initiative of the EC under the Lisbon Strategy); (iii) Knowledge Assessment Methodology (an interactive benchmarking tool created by the World Bank).
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The analysis of the RDI effectiveness is important because it: (i) identifies if the RDI funds are well spent, and how they can be spent better; (ii) discusses if the balance is right between public and private spending.
The remainder of the report is structured as follows. Section 2 presents a short general description of the RDI system in Lithuania in terms of its basic structure and financing arrangements. Section 3 analyzes how Lithuania’s RDI effort compares to that of other EU member countries on both RDI inputs and outputs. Section 4 looks at the effectiveness of the Lithuania’s public spending on RDI. Section 5 discusses some of the key challenges faced by the RDI system. Section 6 concludes with a summary of key findings and policy recommendations.
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2. Research, development and innovation (RDI) system in Lithuania – some basic facts and financing arrangements
The R&D sector in Lithuania consists of mostly public research institutes plus the R&D undertaken by the private sector. The public research institutes are divided into two types: (i) university research institutes – established to carry out research of high international quality; they focus mainly on basic research and provide the research basis for university education and doctoral studies; there are currently (as mid-2008) 18 such institutes; (ii) state research institutes, which are established to carry out long-term research of international quality important for the Lithuanian science, economy and culture and for international cooperation; they conduct research involving groups of specialized scientists and requiring data collection and specialized experimental instruments; there are currently 17 such entities. The private research institutes are virtually non-existent.3 The private R&D is undertaken by the private sector, but it currently accounts for only 25% of the total R&D expenditures. It is important to note that currently the Lithuanian Government has plans for consolidating and reforming the public R&D system, but concrete steps in that directions have not been really taken yet.4
Total R&D expenditures in Lithuania currently constitute 0.8% of the GDP, and fall short of the eventual target for the EU member states. Lithuania increased the spending on R&D from around 0.5% of the GDP in 1995 to 0.8% of the GDP in 2007. Coupled with the growing economy, that also meant that R&D expenditures increased significantly in real terms. However, R&D expenditures in Lithuania fall short of the EU member states target rate of 3% of the GDP. Moreover, the gap is even higher in terms of the real R&D expenditures per capita, since Lithuanian’s per capita GDP is lower than the average per capita GDP for the EU member states.
Public R&D expenditures dominate the structure of the total R&D expenditures. Public R&D expenditures account for 0.6% of the GDP, or 75% of the total R&D expenditures. The remainder of the R&D expenditures is contributed by the private sector.5 The contribution share of the public expenditures to the total R&D expenditures has been effectively unchanged for the last 10 years.
The share of public R&D expenditures on applied research and experimental development increased over the last few years. The share of R&D expenditures on applied research and experimental development increased from 58.3% in 2000 to 67.7% in 2007. Most of this increase is driven by the rising share of expenditures on the experimental research.
3 The one we are aware of, the Applied Research Institute for Prospective Technologies (ProTech), is a non-profit research institute founded in 2005 with an objective of facilitating the environment for industrially oriented technologies development. 4 We provide more discussion on this later in the report where we discuss the main challenges faced by the Lithuanian RD sector. 5 It is important to note that private R&D expenditures refer to the research done by the private sector, and not by the private research institutes, which, as we mentioned, are virtually absent in Lithuania.
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A large influx of funds for R&D and innovation will be coming through the EU Structural Funds (SF) allocation for 2007-2013.6 The total 2007-2013 EU SF in Education and Science administered through the Ministry of Education and Science (MoES) are 984 million EUR. Of these funds, EUR 118 million is earmarked for development of research capabilities, and EUR 372 million is allocated for scientific research and infrastructure. These two R&D related components thus sum up to EUR 490 million.7 The other stream of EU SF for support of R&D and Innovation is provided through the funds administered by the Ministry of Economy (MoE). These 2007-2013 funds for R&D and Innovation amount to EUR 304 million. Hence, the total EU SF budget envelope provided through those two ministries in direct support of the R&D and Innovation is equal to EUR 794 million.
The EU SF also allocates, through the MoE, substantial funds for increase in Business Productivity and Improvement of Business Environment. These funds over 2007-2013 amount to EUR 460.5 million and support various measures aimed at adoption of new technologies by the business sector. The largest program under these funds is the EUR 179 million initiative that provides grants to businesses for the purchase of the new equipment.8 Those grants are administered on a competitive basis, and any manufacturing firm (local or joint venture) employing more than 10 employees9 is eligible to apply.10
Lithuania has also put various efforts to improve the quality of institutional environment for R&D. The new Corporate Tax Law that was adopted last year makes provisions that businesses can deduct expenses on R&D from taxable income. There exists a national support for patenting. This takes the form of the funds from the state budget channeled through the Ministry of Economy to cover expenses related to patenting. Any entity in Lithuania (research institute, company, physical person) can apply for those funds. However, the applications for those funds are few and far between. This provides on-the-ground evidence that Lithuania with its small population size and limited R&D resources compared to many other countries, may not be best position for the creation of knowledge (except a few niche markets such as semi-conductors, laser technology, etc.). Instead, adoption of knowledge could be a better way to go. Whether 6 This period means that by the end-2013 the funds have to be contracted. Two more years are then given to disburse money (i.e., all payment claims have to be submitted) to the selected projects. Due to the preparatory work for the design of the activities and announcement of the bid proposals, the funds will effectively start to be allocated in 2009. 7 The other 2007-2013 SF for the education sector are geared towards: (i) support of life-long learning (EUR 255 million), and (ii) infrastructure for education, vocational training and studies (EUR 240 million). 8 Another EUR 58 million in grants support various initiatives aimed at adoption of new managerial practices, exploration of new business opportunities, etc. The remainder EUR 126 million are loans managed by the European Investment Fund (EIF) to support financial engineering and related measures (micro credits, venture funds, investment guarantees, etc.). 9 The classification of businesses by employment size in Lithuania is as follows: (i) <10 employees – micro enterprise; (ii) 10-250 employees – small and medium enterprise (SME), with 10-50 regarded small, and 51-250 regarded as medium; (iii) > 250 employees – large enterprise.10 The proposals are ranked according to a very clear set of criteria on a 0 to 100% scale (with a cut-off of 50% - any proposal with an aggregate score of below 50% is rejected). It appears, based on the information we have, that the procedures for the call for proposals and proposal selection are very transparent, with all the results publicly available and published on the MoE website.
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this is indeed the strategy that should be pursued will be discussed in a greater detail later in the report.
3. How Lithuania’s current RDI effort compares to that of other EU member countries on inputs and outputs?
To map the road ahead, and to measure future successes or failures, it is crucial to benchmark Lithuania’s RDI effort to that of other EU member countries. In what follows we present the main findings emanating from this analysis. We first compare Lithuania to other EU member countries using the Summary Innovation Index (SII) that was developed by the European Innovation Scoreboard (EIS).11 The methodological approach we take is different from just comparing Lithuania’s level of performance to that of other countries. Instead, the central question we try to answer is: How well is Lithuania doing conditional on its level of economic development, population size, quality of the institutional environment, etc.? In the analysis we also look at Lithuania’s performance in specific dimensions of the SII, as described below.
SII is a summary innovation measure that combines the innovation indicators that are assigned to five dimensions and grouped in two main themes: inputs and outputs. Innovation inputs cover three innovation dimensions: Innovation drivers measure the structural conditions required for innovation potential; Knowledge creation measures the investments in R&D activities, considered as key elements for a successful knowledge-based economy; and Innovation & entrepreneurship measures the efforts towards innovation at firm level. Innovation outputs cover two innovation dimensions: Applications measures the performance, expressed in terms of labor and business activities; and their value added in innovation sectors; and Intellectual property measures the achieved results in terms of successful know –how. Those 5 main categories are broken down into the list of 25 indicators (see Table A1, Annex).12
On the Summary Innovation Index in 2007 Lithuania ranks 19th out of the 27 EU member countries. The Lithuania’s SII in 2007 was 0.27. The group of countries with a lower index consists of mostly the Eastern European countries (Latvia, Bulgaria, Romania, Hungary, Poland, and Slovakia) plus Greece and Portugal (Figure 1).
However, conditional on Lithuania’s per capita GDP, the country performs, in terms of the SII, as would be expected given its level of development. Lithuania’s per capita GDP at 2005 PPP USD 14,085 places it higher than Turkey, Bulgaria, Romania, and Latvia. Lithuania seats very close to the regression line of the SII on per capita GDP, indicating that Lithuania is doing as would be expected given its current level of
11 The EIS is the instrument developed at the initiative of the European Commission, under the Lisbon Strategy, to evaluate and compare the innovation performance for the EU Member States. It includes innovation indicators and trend analyzes for the EU27 Member States. The EIS report and its annexes, accompanying thematic papers and the indicators’ database are available at: http://www.proinno-europe.eu (click “INNO-Metrics” tab). 12 Further details on the EIS indicators and the methodology of their aggregation into the SII index can be found in the PRO INNO Europe Paper N 6 “EIS 2007: Comparative Analysis of Innovation Performance”, available at http://www.proinno-europe.eu/metrics.
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development (Figure 1). Nevertheless, this fact does not provide a room for complacency. For instance, the neighboring Estonia, with the SII of 0.37 in 2007, is doing much better than would be expected given its per capita GDP. This can be clearly seen from the same Figure, where Estonia is located much higher above the regression line.13 By the same token, there is also a group of more developed EU countries such as Finland, Denmark, Switzerland, and Germany which are positioned well above the average (Figure 1). Indeed, these EU member countries together with Sweden and Japan are classified by the EIS as the innovation leaders. We also would like to note that in the regression which controls for both per capita GDP and the country’s population size Lithuania also comes up as performing as would be expected given those variables.
Figure 1: Summary Innovation Index (SII) versus per capita GDP – Lithuania versus 27 EU member states
BE
BG
CZ
DKDE
EE
IE
EL
ES
FR
ITCY
LV
LT
LU
HU
MT
NLAT
PL PT
RO
SI
SK
FI
UK
CH
.2.3
.4.5
.6.7
.8S
umm
ary
Inno
vatio
n In
dex
(SII)
, 200
7
10000 20000 30000 40000 50000 60000 70000GDP per capita, 2005 PPP US$
sii_2007 Fitted values
Source: Constructed by the author
Lithuania shows a tendency of catching up with other EU member states on the level of innovation. Lithuania’s SII grew at the average annual growth rate of 5% between 2003 and 2007 – from the score of 0.23 to 0.27. This growth rate puts Lithuania among the top performers among the EU member states (Figure 2). However, the faster growth rate would in a way be expected given that Lithuania started from a relatively modest level on the innovation front. Indeed, among the other top SII growth performers one would find Latvia, Poland, and Bulgaria (Figure 2) – countries lagging behind the other EU member states on the levels of the SII.
13 In econometric terms, one can call the points above the regression line the “positive outliers”, and those below the regression line the “negative outliers”.
10
Figure 2: Growth rate in the Summary Innovation Index (SII) during 2003-2007 versus per capita GDP – Lithuania versus 27 EU member states
BE
BG
CZ
DK
DE
EE
IEEL ES FR
IT
CY
LV
LT
LUHUMT
NL
AT
PL
PT
RO
SISK
FI
UKCH
-3-2
-10
12
34
56
SII
avg.
ann
ual g
row
th ra
te, 2
003-
07, %
10000 20000 30000 40000 50000 60000 70000GDP per capita, 2005 PPP US$
Avg. annual change in SII, % Fitted values
Source: Constructed by the author
Now that we established the Lithuania’s position in terms of the levels and trends of the Innovation Index, it is important to “look beyond averages” – that is to analyze how well Lithuania is positioned relative to the EU average in terms of various input and output indicators related to the innovation production and adoption. This analysis is performed both in terms of: (1) analyzing the absolute (unconditional) difference between Lithuania and EU average for a specific indicator; and (2) analyzing the conditional (on the level of development and population size) difference between Lithuania and EU average for a specific indicator.
The analysis indicates that Lithuania is positioned quite well in comparison to the EU average on the quantitative indicators related to the knowledge base. In fact, it leads over the EU on the share of the science and engineering (S & E) graduates, share of population with tertiary education, and youth education attainment level.14 However, it lags behind on participation in life-long learning and broadband internet penetration rate (Figure 3).15 The regression analysis indicates that conditional on the level of development and the population size Lithuania is doing in line with the EU average on the input indicators related to the knowledge base.16
14 The detailed definitions of all indicators mentioned here are available at the Europe Innovation Scoreboard (EIS) 2007 Report, available at: http://www.proinno-europe.eu/admin/uploaded_documents/European_Innovation_Scoreboard_2007.pdf15 Note that all cobweb diagrams (Figures 3-7) show absolute (unconditional) distance between Lithuania and EU average for a specific indicator, while the results of the regression analysis effectively discuss the conditional (on the level of development and population size) distance between Lithuania and EU average for a specific indicator.
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Figure 3: Innovation input indicators - knowledge base
9.6
12.9
23.0
16.5
7.8
4.9
18.9
26.8
8.4
8.8
0
10
20
30New S&E graduates
Tertiary education
Broadband rateLife-long learning
Youth education level
EU
Lithuania
Source: Constructed by the author
The international studies on the quality of education indicate that Lithuania is also positioned quite well in the international context on the quality of education indicators, as measured by the math and science scores. According to the 2007 Trends in International Mathematics and Science Study (TIMSS), Lithuania’s 4th and 8th graders scored above international average on the mathematics and science tests. Moreover, Lithuania’s 8th graders’ average math score increased from 472 in 1995 to 506 in 2007, or by 7.2%; at the same time, the 8th graders’ average science score increased from 464 in 1995 to 519 in 2007, or by 11.9%.17 Lithuania is also doing quite well on the math and science scores controlling for its level of development (Figure 4, Panels A & B). Lithuania’s 2007 math and science scores were on par with those of the USA. However, there is no room for complacency, since in Lithuania (similar to the USA) only 6% of the 8th graders achieve the advanced score (625) in mathematics, compared to 26% in Japan, 40% in Singapore, and 45% in Taipei (the highest score). With regard to science scores, in Lithuania 8% the 8th graders (vs. 10% in the USA) achieved the advanced score (625), compared to 17% in Japan, and 32% in Singapore (the highest score).18
16 The regression equation takes the following form: Input/Output indicator = f (per capita GDP, population size, R&D as % of GDP, Ease of Doing Business Rank; Lithuania dummy). The log specification is used. In the regression specification with output indicators as dependent variables we also, as am alternative specification, we also include public and private expenditures (as a % of GDP). Controlling for those variables leads to similar conclusions. 17 The increases for both scores are statistically significant increase at the 5% level. 18 More details can be found in the TIMSS 2007 Report: http://nces.ed.gov/pubs2009/2009001.pdf
12
Figure 4: Math and Science scores for the 8thgrade (TIMSS 2007) versus per capita GDP – Lithuania versus selected countries
Panel A: Math scores
AU
BG
CZ
HU
IT
LT
MT
NORO
SE
SI
TR
UKUS
400
450
500
550
600
Mat
h sc
ore,
8th
gra
de (T
IMS
S 0
7)
10000 20000 30000 40000 50000GDP per capita, 2005 PPP US$
Math score for 8th grade, TIMSS 07 Fitted values
Panel B: Science scores
AU
BG
CZHU
IT
LT
MT
NO
RO
SE
SI
TR
UK
US
400
450
500
550
600
Mat
h sc
ore,
8th
gra
de (T
IMS
S 0
7)
10000 20000 30000 40000 50000GDP per capita, 2005 PPP US$
Science score for 8th grade, TIMSS 07 Fitted values
Source: Constructed by the author based on TIMSS 2007.
To provide better comparisons across EU member countries, we also report the results of the PISA 2006 survey.19 PISA summarizes performance on a science scale that provides an overall picture of students’ accumulated understanding of science at age 15, which is near the end of compulsory education.20 The assessment focuses on how well
19 PISA is the OECD Program for International Program Assessment. PISA 2006 focused on students’ competency in science (but also measuring proficiency in reading and mathematics). The full report describing the PISA 2006 survey results is available at: http://www.pisa.oecd.org/dataoecd/30/17/39703267.pdf20 A summary score measures performance in each of the science competencies ( identifying scientific issues, explaining phenomena scientifically and using scientific evidence), knowledge domains (knowledge about science and knowledge of science), and content areas (“Physical systems”, “Living systems”, and
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the students can extrapolate from what they have learnt and apply their knowledge in novel settings.
The results from PISA indicate that conditional on its level of development Lithuania is doing quite well on the math and science scores (Figure 5, Panels A & B). However, in terms of absolute levels, the country is below EU25 averages of 492 and 497, respectively. It is important to note, however, that neither TIMSS no PISA measures the quality of higher (university) education, which is a prerequisite for developing scientists.
Figure 5: Math and Science scores (PISA 2006) versus per capita GDP – Lithuania versus other EU member countries
Panel A: Math scores (PISA 2006)
ATBE
BG
CHCZ DE
DK
EE
EL
ES
FI
FRHU
IE
IT
LTLV
NL
PL
PT
RO
SI
SK
UK
400
450
500
550
600
Sci
ence
sco
re (P
ISA
06)
10000 20000 30000 40000GDP per capita, 2005 PPP US$
science_score_pisa06 Fitted values
Panel B: Science scores (PISA 2006)
ATBE
BG
CHCZ DE
DK
EE
EL
ES
FI
FRHU
IE
IT
LTLV
NL
PL
PT
RO
SI
SK
UK
400
450
500
550
600
Sci
ence
sco
re (P
ISA
06)
10000 20000 30000 40000GDP per capita, 2005 PPP US$
science_score_pisa06 Fitted values
Source: Constructed by the author based on PISA 2006.
“Earth and space systems”).
14
In the context of discussing the RDI sector it is also important to understand where Lithuania is positioned on convergence to the European higher education standards. Lithuania is participating in the Bologna Process(or Bologna accords),21 which aims to create the European higher education area by making academic degree standards and quality assurance standards more comparable and compatible throughout Europe, in particular under the Lisbon Recognition Convention. The implementation of the Bologna Process in Lithuania has been overseeing by the National Bologna Follow-up group that was set up in mid-2004.22
The analysis of the degree of Lithuania’s integration into the framework of the Bologna process indicates that the country has made substantial progress, but some gaps remain. Lithuania scores highly in all three areas of the Bologna framework (quality assurance, the two-cycle degree system, and recognition of degrees and periods of study). However, more work needs to be done in specific sub-areas. For instance, when it comes to the quality assurance, Lithuania scores 3 out of 5 on the level of international participation, co-operation and networking. It also requires better integration (access) between the first cycle and the second cycle of the education system (Table A2, Annex).
Unfortunately, currently there are no comparable assessments of the quality of tertiary education across EU countries. Hence, it is not very clear where Lithuania is in this regard. OECD is currently in the process of developing the framework for the assessment of the quality of tertiary education. Following the 2006 OECD Ministerial Conference in Athens, OECD had the ambitious goal to develop a 'PISA for Tertiary Education' (working title 'AHELO').23 OECD is now preparing the PIAAC exercise which measures adult competencies and explicitly covers tertiary education outcomes.
21 The Bologna Process aims to create a European Higher Education Area by 2010, in which students can choose from a wide and transparent range of high quality courses and benefit from smooth recognition procedures. The Bologna Declaration of June 1999 has put in motion a series of reforms needed to make European Higher Education more compatible and comparable, more competitive and more attractive for Europeans and for students and scholars from other continents. The three priorities of the Bologna process are: (1) Introduction of the three cycle system (bachelor/master/doctorate); (2) quality assurance; and (3) Recognition of qualifications and periods of study.22 Lithuania’s participation in Bologna Process is the following document: http://www.ond.vlaanderen.be/hogeronderwijs/bologna/links/National-reports-2005/National_Report_Lithuania_05.pdf23 The feasibility study is available at: http://www.oecd.org/document/22/0,3343,en_2649_35961291_40624662_1_1_1_1,00.html
15
Lithuania clearly lags behind the EU average on the private sector expenditures on R&D. Indeed, while the private R&D expenditure makes on average 1.2% of the GDP in the EU, it only accounts for 0.2% of the GDP in Lithuania. At the same time, the Lithuania’s public expenditures on R&D relative to GDP are close to the EU average – at about 0.7%. However, the share of enterprises receiving public funding for innovation is much smaller in Lithuania (Figure 6). The regression analysis confirms that given per capita GDP and population size Lithuania’s public R&D expenditure (as a share of GDP) is consistent with the EU average, while the private R&D expenditure is lower.
Figure 6: Innovation input indicators – R & D expenditures
9.0
1.2
0.7
3.6
0.2
0.6
0.1
1.0
10.0Public R&D expenditure
Private R&D expenditureEnterprises receiving public
funding for innovation
EU
Lithuania
Source: Constructed by the author
Lithuania is doing quite well relative to the EU average on the SMEs’ participation in the innovation activities. Lithuania is somewhat behind EU average on the share of SMEs with in-house innovation activities and the SMEs innovation expenditures (as % of turnover). However, it does better than the EU average on the share of SMEs having cooperation agreements on innovation activities with other enterprises, and on the expenditures on information and communication technology (ICT) as a percent of GDP. Nevertheless, Lithuania’s SMEs are behind in the area of organizational innovation24 (Figure 7). The regression analysis confirms that Lithuania does above average when it comes to the SMEs having cooperation agreements on innovation activities with other enterprises, and performs on other indicators in this group as would be expected.
24 Organizational innovation refers mostly to: (i) new or significantly improved knowledge management systems; (ii) major change to the organization of work within the enterprise, and (iii) new or significant changes in business relations with other firms or public institutions.
16
Figure 7: Innovation input indicators – innovation & entrepreneurship
34.0
2.2
9.1
21.6
6.4
23.6
1.6
14.8
14.6
7.8
1.0
10.0
100.0SMEs innovating in-house
Innovative SMEs cooperatingwith others
Innovation expendituresICT expenditures
SMEs with organizationalinnovation
EU
Lithuania
Source: Constructed by the authorNote: logarithmic scale is used fro the purposes of exposition, although all the numbers in the graph are actual numbers.
Lithuania is trailing behind the EU average on the output indicators related to the application of new knowledge, but the existing gap seems to be possible to bridge. In Lithuania, the share of employment in high-tech services is 2.2% (versus 3.3% in the EU), sales of new-to-market products as a share of overall turnover is 4.4% (versus the EU’s 7.3%), and sales of new-to-firm products as a percent of total turnover is 5.3% (versus EU’s 6.2%). The important area where Lithuania is much more behind is the exports of high-tech products in the total exports – 4.7% versus the EU’s average of 16.7% (Figure 8). The regression analysis indicates that conditional on per capita GDP and population size Lithuania performs fine on those output indicators.
17
Figure 8: Innovation output indicators – application of new knowledge
6.2
3.3
16.7
7.3
6.6
5.3
2.24.7
4.42.4 1.0
10.0
100.0Employment in high-tech services
Exports of high-tech products
Sales of new-to-market productsSales of new -to-firm products
Employment in high-techmanufacturing
EU
Lithuania
Source: Constructed by the authorNote: logarithmic scale is used fro the purposes of exposition, although all the numbers in the graph are actual numbers.
The area where Lithuania is clearly behind the EU average, even after controlling for population size, is the creation of new knowledge, as evident from the intellectual property indicators. The number of the European Patent Office (EPO) patent applications (per million of population) in Lithuania is a mere 5.8 versus the EU average of 128. The number of patents (per million of population) granted by the US patent and Trademark Office (USPTO) for Lithuania is 0.5 versus the EU average of 52.2. Lithuania is also well behind on other new knowledge output indicators, such as triad patents, trademarks, and industrial designs (Figure 9).
Controlling for population size and per capita GDP, Lithuania still comes across as an underachiever on the output indicators. The actual number of Lithuania’s EPO patent applications is 5.8 versus the regression-based prediction value of 8.6 (Figure 10). The regression analysis clearly indicates that when it comes to the knowledge creation the population size does matter – an increase in population by 1% leads to an average 0.25% larger number of patents. In other words, with few exceptions like small but rich Scandinavian countries and Luxemburg, smaller countries like Lithuania seem to be positioned worse than larger countries in the knowledge production (Figure 10).
18
Figure 9: Innovation output indicators – creation of new knowledge (intellectual property)
109.4
20.8
52.2
128.0
108.2
4.4
0.1
0.5
5.8
20.9
0.0
0.1
1.0
10.0
100.0
1000.0EPO patents
USPTO patents
Triad patentsTrademarks
Industrial designs
EU
Lithuania
Source: Constructed by the authorNote: logarithmic scale is used fro the purposes of exposition, although all the numbers in the graph are actual numbers; all indicators are per million of population.
Figure 10: Actual versus predicted number of the EPO patents (per million of population) in the EU countries
0 50 100 150
FranceItaly
SpainPoland
RomaniaGreece
PortugalBelgium
Czech RepublicHungaryBulgariaSlovakiaLithuania
LatviaSloveniaEstonia
actual EPO patents predicted EPO patents
Source: Constructed by the authorNote: countries are ranked by population size from smallest (top) to largest (bottom).
19
4. Effectiveness of the Lithuanian public and private spending on RDI – how well is Lithuania doing compared to other EU member countries?
Now that we benchmarked Lithuania against other EU member countries on a broad measure of innovation and various input and output indicators (and also controlling for the country’s level of GDP and population size), the next important question we ask is: Does Lithuania gets an expected “bang for buck” for its investments in the public R&D (compared to other EU member countries)? In other words, the question is whether Lithuania gets an adequate output for the money it spends on the public R&D, which, as we previously established, constitutes 75% of the total spending on the R&D.
Lithuania occupies an 8th place among the EU27 member countries on the share of GDP spent on public R&D. Indeed, Lithuania’s 0.61% of the GDP spent on public R&D looks pretty good compared to many other countries. The analysis indicates that richer EU member countries also tend to spend a higher share of the GDP on the public R&D. Considering Lithuania’s level of GDP, the share of the GDP that it spends on the public R&D actually stands out among EU27 countries with a similar or even higher GDP levels (Figure 11).
Figure 11: Public spending on R&D as a share of GDP versus per capita GDP – Lithuania versus 27 EU member states
AT
BE
BG
CH
CY
CZ
DE DK
EE
EL
ES
FI
FR
HU
IE
IT
LT
LU
LV
MT
NL
PLPT
RO
SI
SK
UK
.1.2
.3.4
.5.6
.7.8
.91
Pub
lic R
&D
spe
ndin
g, %
of G
DP
, 200
5
10000 20000 30000 40000 50000 60000 70000GDP per capita, 2005 PPP US$
public_RD_pct_GDP Fitted values
Source: Constructed by the author
20
However, Lithuania is amongst the worst performers when it comes to the private spending on R&D. Indeed, with the private spending of 0.16% of the GDP Lithuania is doing only marginally better than Cyprus and Bulgaria (Figure 12).
Figure 12: Private spending on R&D as a share of GDP versus per capita GDP – Lithuania versus 27 EU member states
AT
BE
BG
CH
CY
CZ
DEDK
EE
EL
ES
FI
FR
HU
IE
IT
LT
LU
LV
MT
NL
PLPT
RO
SI
SK
UK
0.5
11.
52
2.5
Priv
ate
R&
D s
pend
ing,
% o
f GD
P, 2
005
10000 20000 30000 40000 50000 60000 70000GDP per capita, 2005 PPP US$
private_rd_pct_GDP_05 Fitted values
Source: Constructed by the author
Conditional on Lithuania’s per capita public spending on R&D, the country performs on the Summary Innovation Index slightly below of what would be expected. Lithuania spends PPP US$ 8,591 per capita per year on public R&D, which ranks it 17th out of the EU27 countries. Looking at the relationship between the level of spending and the Summary Innovation Index (SII), we find that the output (SII) level is fairly consistent with it – although Lithuania is located somewhat below the respective regression line, the difference is not significant (Figure 13).
21
Figure 13: Summary Innovation Index (SII) versus annual public spending on R&D per capita (in PPP USD) – Lithuania versus the EU27 member states
ATBE
BG
CH
CY
CZ
DEDK
EE
EL
ES
FI
FR
HU
IE
IT
LT
LU
LV
MT
NL
PL PT
RO
SI
SK
UK
.2.3
.4.5
.6.7
.8S
umm
ary
Inno
vatio
n In
dex
(SII)
, 200
7
0 50 100 150 200 250 300Public R&D spending per capita, 2005 PPP US$
sii_2007 Fitted values
Source: Constructed by the author
The analysis indicates that given its level of public spending on R&D Lithuania underperforms on the knowledge production indicators. Given the level of public R&D spending, Lithuania is lagging behind in the area of new patents (EPO, USPTO, triads), even after controlling for the population size and the openness of the business environment. However, once we also control for the level of private R&D spending (to take into account that knowledge production is determined by both types of spending), we find that Lithuania underperforms only in the area of the USPTO and triad patents. We find no evidence for Lithuania to underperform, given its level of public and private spending, on the output indicators related to absorption (application) of new knowledge.
The 2007-2013 EU Structural Funds (SF) earmarked for R&D will substantially increase the budget envelope available for public and private R&D. Assuming (for simplicity of making an argument) that the EU SF will be evenly distributed across years, we find that while the 2008 public and private spending on R&D increases from the EUR 214 million without EU SF, to EUR 327 million with EU SF, or by 54% (Figure 14).25 This estimate is based on the reported EUR 794 million in the EU SF direct support of the R&D and Innovation.
25 The forecast also assumes that the spending envelope for R&D is also expected to increase by 2013 due to an average annual real growth rate of 5% in R&D spending due to the growing economy (at the same rate).
22
Figure 14: Lithuania’s expected total (private and public) spending on R&D over 2007-2013, and the impact of the EU Structural Funds
207.6218.0
278.3
321.1 331.4
391.7
196.5
309.9
100
150
200
250
300
350
400
450
07' 08' 09' 10' 11' 12' 13'
EU
R, m
illio
n
Total R & D spending, no EU Structural Funds (no financial crisis) Total R&D spending, with EU Structural Funds (no financial crisis)Total R & D spending, no EU Structural Funds (financial crisis) Total R&D spending, with EU Structural Funds (financial crisis)
Source: Constructed by the author
The reliance on the EU Structural Funds for R&D would be even more important in the current environment of the financial crisis, which would significantly constrain the public and private resources available for the sector. We estimate that under the current economic forecast the total R&D spending envelope over 2008-13 would downsize by a cumulative of about EUR 335 million (compared to its total expected value under no crisis scenario), which is more than the yearly value of the R&D spending envelope without EU Structural Funds (Figure 14).26
What would be the expected impact of the EU Structural Funds for R&D on the Lithuania’s Summary Innovation Index (SII)? The simulations suggest that without EU funds for R&D the SII would be expected to increase by 5.4% between 2008 and 2013.27 However, with the infusion of the EU Structural Funds for R&D the SII is forecasted to increase by 7.5% over the “no EU funds” scenario level. That may not look like a large increase, but one needs to consider two facts here. First, these calculations do not take into consideration that the institutional environment for R&D may improve due to various factors and reforms, and that the private sector contribution to the R&D spending is likely to increase beyond the contribution of the EU Structural Funds. Second, even this magnitude of the increase will put Lithuania on the new trajectory in its R&D effort.28
5. Key challenges faced by the RDI system in Lithuania26 It is important to keep in mind that those estimates are highly indicative, since they are based on macroeconomic projections that are being revised frequently. 27 This is derived under the assumption of the constant share of the total R&D spending in the GDP, and the average real growth in GDP of 5% per year.28 This can actually be seen from the Figure 10 as a vertical movement of Lithuania all the way up to the regression line or above.
23
The Lithuanian RDI system has many good elements to build on, and the EU Structural Funds provide a great opportunity to launch it on a new orbit.29 However, it also faces formidable challenges ahead. Those include:
(i) The overall direction for the RDI system development is needs to be better defined. There is currently a Government’s plan to consolidate the existing network of the 35 RDI institutes (RDII) into the 6 scientific centers, in which RDIIs are better integrated with the universities. The idea is also to organize these scientific centers along the geographic principle and make them mimic the concept of “Silicon valley”. There is not clear though how that would work in practice. It is important to keep in mind that while the Silicon Valley in the USA was effectively built on the “bottom-up” approach, with a large concentration of engineers and IT people coupled with venture capitalists driving new technological breakthroughs, what is envisioned in Lithuania currently looks like a “top-down” design, which carries a risk of a failure to elucidate base elements or be detailed enough to be realistically implemented. Some policy makers also express concerns that the envisioned number of the scientific centers and technology platforms is too large, and may lead to spreading the resources too thinly.
(ii) The existing RDIIs continue to rely on the old principles of predominantly state-financing rewarding input and past output. Subsidies from the government still make up about 70% of the resource base, with the rest coming from the customer base and international scientific projects.30 Moreover, 80% of the state funding covers input-based “basic” research, and the remainder 20% is output-based financing based on the past (last 3 years) output (number of publications, scientific conferences, etc.). The competitive-based financing, which is believed to be the main driver of innovation, is very limited.
(iii) The small size of the country and limited number of the high-tech enterprises creates a demand constraint for the output of the RDIIs. It is estimated that only about 2% of the Lithuanian companies can be qualified as “high-tech” – companies that could potentially use the services of the RDIIs. The absorption of the EU structural funds (SF) is based on the principle that the development of the new products will be 50% financed by the firm/enterprise, while the remaining 50% will be covered by SF, and the RDIIs will be the developing the new technology. While the small number of the high-tech companies is a problem in itself, further constraints arise from the fact that Lithuanian RDIIs cannot team up with the international businesses for the purpose of absorption of the SF. This is because the guiding principle of the SF is that they can only be used by the local firms.
29 Lithuania’s progress in Science, Technology and Innovation (STI) from a point of view of institutional environment is analyzed in a much greater detail in a separate qualitative report. 30 This structure of financing is for the Semiconductor Physics Institute (SPI), which is one of the leading/most progressive RDIIs in Lithuania. It is likely that the dependence on state financing is even higher for other RDIIs.
24
(iv) There is a weak link between technological inventions and the development and sales of invention-related market products. On a positive side, Lithuanian RDIIs seem to have freedom of signing contracts with business entities, including the foreign ones. However, the local market for invention-related products is limited. At the same time, competition at the global level (e.g., Chinese products) is very fierce. As a result, many Lithuanian companies already found themselves unable to compete (e.g., the factory producing the TV screens was shut down), and a few remaining will face significant difficulties.
(v) Efficient allocation of the EU structural funds for RDI will be a key challenge. The total 2007-2013 EU SF budget envelope provided through the MoES and MoE in direct support of the R&D and Innovation is equal to EUR 794 million. On one hand, those funds provide a huge opportunity for Lithuania to put its R&D sector on a much higher level. On the other hand, the allocation and efficient utilization of those funds will be a challenge.
V. Conclusions
The analysis described in this report has revealed several key findings, around which some policy recommendations can be formulated:
Lithuania is currently behind most EU member states in terms of Summary Innovation Index. While the level of the Summary Innovation Index (SII) observed in Lithuania is consistent with its level of development (per capita GDP) and population size, with a right effort the country can perform much better than “average”. Moreover, the analysis reveals that Lithuania shows the tendency to catch up with other EU member states. Nevertheless, more can be done to put Lithuania among “positive outliers” – countries that perform better than would be expected given their levels of development (e.g., the neighboring Estonia).
The analysis indicates that Lithuania has strong foundations to be a knowledge-based economy. Lithuania is positioned quite well in comparison to the EU average on the quantitative indicators related to the knowledge base. Moreover, Lithuania is doing well relative to the EU average on the SMEs’ participation in the innovation activities. The data on the quality of the general secondary education that comes from PISA and TIMSS indicate that Lithuania is doing quite well in this regard. The levels of math and science scores are on par with EU averages, but noticeably lower than of the leading countries in the EU. The analysis of the degree of Lithuania’s integration into the framework of the Bologna process indicates that the country has made substantial progress, but some gaps remain. Moreover, in the absence of the data, it is not clear how Lithuania compares to other countries on the quality of tertiary education.
Lithuania spends a respectful share of its GDP on the public investments in RDI, but more effort is needed to create the conditions that would enhance the private spending on RDI. The country is currently well behind the EU
25
average on the private sector R&D expenditures as a share of GDP – 0.2% in Lithuania versus 1.2% in the EU. However, this position may well be improved wit the appropriate use of the EU Structural Funds, combined with a clear strategy of how to move forward with the overall RDI strategy. The international studies on the quality of education indicate that Lithuania is also positioned quite well in the international context on the quality of education indicators, as measured by the math and science scores.
The area where Lithuania is clearly behind the EU average is the creation of new knowledge, as evident from the intellectual property indicators. This does not necessarily mean that Lithuania should abandon in its entirety its ambitions for the creation of new knowledge. What it does suggest is that while identifying and exploring some niche markets for the creation of knowledge could be a good idea for the country, Lithuania with its small size and limited resources would hardly be able to compete with other innovation giants across the wide spectrum of high-tech products. Hence, the more pronounced focus on the knowledge absorption can be well justified.
While Lithuania is currently trailing behind the EU average on the output indicators related to the application of new knowledge, the existing gap seems to be possible to bridge. Moreover, on those indicators Lithuania already performs at the level consistent with its spending on R&D and other input indicators. Given the country’s solid foundations for a knowledge-based economy coupled with favorable business climate and the EU support in the form of the Structural Funds for R&D, the practical and viable approach for Lithuania could be a greater focus on the adoption and diffusion of the latest knowledge available elsewhere in the world, rather than the concentrated effort on the creation of new knowledge.
In the current environment of the financial crisis, Lithuania’s reliance on the EU Structural Funds for R&D will be very important, since the public and private resources available for the sector will be significantly constrained, at least in the short term. The 2007-2013 EU Structural Funds (SF) earmarked for RDI will substantially increase the budget envelope available for public and private RDI, and the simulations we perform indicate that these funds could give a good push for Lithuania to reach a new trajectory in its RDI effort. However, we estimate that under the current economic forecast the total RDI spending envelope over 2008-13 would downsize by a cumulative of about EUR 335 million (compared to its total expected value under no crisis scenario).
26
ANNEX
Table A1: The European Innovation Scoreboard (EIS) 2007 IndicatorsN Category/Indicator Source1 Innovation Drivers (Input Dimension)1.1 S&E graduates per 1,000 population aged 20-29 Eurostat1.2 Population with tertiary education per 100 population aged 25-
64Eurostat, OECD
1.3 Broadband penetration rate (number of broadband lines per 100 population)
Eurostat, OECD
1.4 Participation in life-long learning per 100 population aged 25-64 Eurostat1.5 Youth education attainment level (% of population aged 20-24
having completed at least upper secondary education)Eurostat
2 Knowledge Creation (Input Dimension)2.1 Public R&D expenditures (% of GDP) Eurostat, OECD2.2 Business R&D expenditures (% of GDP) Eurostat, OECD2.3 Share of medium-high-tech and high-tech R&D (% of
manufacturing R&D expenditures)Eurostat, OECD
2.4 Share of enterprises receiving public funding for innovation Eurostat (CIS4)3 Innovation and Entrepreneurship (Input Dimension)3.1 SMEs innovating in-house (% of all SMEs) Eurostat (CIS4)3.2 Innovative SMEs co-operating with others (% of all SMEs) Eurostat (CIS4)3.3 Innovation expenditures (% of total turnover) Eurostat (CIS4)3.4 Early-stage venture capital (% of GDP) Eurostat3.5 ICT expenditures (% of GDP) Eurostat, World
Bank3.6 SMEs using organizational innovation (% of all SMEs) Eurostat (CIS4)4 Applications (Output Dimension)4.1 Employment in high-tech services (% of total workforce) Eurostat4.2 Exports of high-technology products (share of total exports) Eurostat4.3 Sales of new-to-market products (% of total turnover) Eurostat (CIS4)4.4 Sales of new-to-firm products (% of total turnover) Eurostat (CIS4)4.5 Employment in medium-high and high-tech manufacturing (%
of total workforce)Eurostat, OECD
5 Intellectual Property (Output Dimension)5.1 EPO patens (per million population) Eurostat, OECD5.2 USPTO patents (per million population) Eurostat, OECD5.3 Triad patents (per million population) Eurostat, OECD5.4 New community trademarks (per million population) Eurostat, OECD5.5 New community designs (per million population) Eurostat, OECD
Note: CIS4 refers to the 4th Community Innovation Survey.
27
Table A2: Bologna Scorecard, 2007LLL Joint
1 2 3 4 5 6 7 8 9 10 11 12
N country Impl
Acc
NQ
F
ES
G
Ext
Stu
d
Int
DS
LRC
EC
TS
LLL
JD
1 Albania 3 1 2 4 4 2 3 4 2 5 1 42 Andorra 3 1 2 4 4 2 1 4 1 3 4 53 Armenia 5 5 2 3 4 3 1 3 4 2 2 44 Austria 3 5 2 5 5 4 5 5 5 5 4 55 Azerbaijan 5 1 1 4 3 3 1 3 5 2 3 56 Belgium Flemish 4 5 4 5 5 5 5 4 1 5 5 57 Belgium French 5 5 2 4 4 5 3 5 1 5 5 58 Bosnia Herzegovina 3 5 3 2 2 3 2 3 2 2 3 59 Bulgaria 5 5 4 4 4 4 3 5 5 4 5 510 Croatia 3 5 3 4 4 5 4 3 5 5 3 511 Cyprus 5 5 2 4 3 3 4 3 5 3 4 512 Czech Republic 5 5 3 4 4 3 4 5 5 3 2 513 Denmark 5 5 5 5 5 5 4 5 5 5 4 514 Estonia 4 5 2 4 4 5 3 5 5 4 4 415 Finland 5 5 3 5 5 5 3 5 5 5 5 516 France 4 5 2 4 4 3 4 3 5 5 5 517 Georgia 4 5 2 4 2 3 2 5 5 4 3 418 Germany 3 5 5 5 5 5 5 3 1 3 5 519 Greece 4 5 2 4 4 4 4 5 1 5 2 520 Holy See 5 5 2 4 4 3 4 3 3 2 2 521 Hungary 2 5 4 5 5 5 5 5 5 5 4 522 Iceland 5 5 5 4 4 4 3 5 5 5 5 423 Ireland 5 4 5 5 5 5 5 5 5 5 5 524 Italy 5 5 3 4 4 4 4 5 1 4 4 525 Latvia 5 4 3 4 5 5 5 5 5 4 3 426 Liechtenstein 5 5 2 4 4 3 3 5 5 5 5 427 Lithuania 5 4 2 4 5 5 3 5 5 4 4 428 Luxembourg 4 5 2 4 5 4 5 3 5 5 5 529 Malta 5 5 4 3 4 4 3 3 4 5 2 530 Moldova 3 2 2 4 4 3 3 5 5 3 2 431 Montenegro 4 3 2 3 3 2 1 3 2 4 2 432 Netherlands 5 5 3 5 5 5 5 4 1 5 3 433 Norway 5 5 3 5 5 5 5 5 5 5 5 534 Poland 4 5 2 5 5 5 4 5 5 5 2 435 Portugal 3 5 5 4 4 4 5 5 5 3 5 536 Romania 4 5 4 4 4 4 3 5 5 5 4 537 Russia 2 4 3 4 4 4 3 2 4 5 4 538 Serbia 4 3 3 5 4 4 3 5 4 5 3 539 Slovakia 5 5 2 5 5 4 5 4 5 5 1 440 Slovenia 2 5 2 4 3 4 3 5 5 5 5 541 Spain 3 5 2 4 5 3 4 3 1 4 4 442 Sweden 2 5 4 5 5 5 4 5 5 5 5 443 Switzerland 4 4 2 5 4 4 4 5 5 5 3 544 The FYROM 3 5 2 4 3 2 3 3 5 2 2 445 Turkey 5 5 3 5 4 4 3 4 4 5 3 546 UK - EWNI 5 5 5 5 5 4 4 3 5 2 5 547 UK - Scotland 5 5 5 5 5 5 4 4 5 5 5 548 Ukraine 5 5 2 3 4 5 2 1 5 4 5 5
Quality AssuranceDegree System Recognition
2
1
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
1
#REF!
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Indicator 1 comparison 2005-2007
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
1
Year
Percentage of countries in each colour category
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Note: 5 is the highest score (best practice), and 1 is the lowest score (worst practice). Criteria for Bologna scorecard are available at: http://www.unze.ba/download/bologna/Bologna%20Scorecard%20criteria%20140305.pdf.Source: www.uni-lj.si/files/ULJ/userfiles/ulj/bolonjski_proces/2007%2004%20Stocktaking.xls.
28
