2002 European Innovation Scoreboard: Technical Paper No 2 Candidate Countries

Transcription

1 European Trend Chart on Innovation 2002 European Innovation Scoreboard: Technical Paper No 2 Candidate Countries November 26, 2002 European Commission Enterprise Directorate-General A publication from the Innovation/SMEs Programme

2 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 co-ordination approach laid down by the Lisbon Council in March 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. The Trend Chart products The Trend Chart on Innovation has been running since January 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 ( 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 is 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 by Hugo Hollanders of MERIT ( The information contained in this report has not been validated in detail by either the Member States or the European Commission. Contact: Peter Löwe: peter.loewe@cec.eu.int 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.

3 European Innovation Scoreboard The European Innovation Scoreboard (EIS) was developed at the request of the Lisbon European Council in 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 contains 17 main indicators, selected to summarize the main drivers and outputs of innovations. These indicators are divided into four groups: Human resources for innovation (5 indicators); the creation of new knowledge (3 indicators of which one is divided into EPO and USPTO patents); the transmission and application of knowledge (3 indicators); and Innovation finance, outputs and markets (6 indicators). The EIS complements the Enterprise Policy Scoreboard 2 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 indicators. All indicators have been updated based on data availability as of September 15, Four indicators could not be updated due to delays in the execution of the third Community Innovation Survey 3. 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 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. 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 ( 1 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) SEC(2002) These are indicators 3.1, 3.2, 3.3 and 4.3.

4 Table of Contents 1. Introduction EIS Results for the Candidate countries Leading Candidate countries Current trends Relative strengths and weaknesses Variation per indicator...7 Annex Table A: European Innovation Scoreboard Data Definitions and Sources...10 Annex Table E: European Innovation Scoreboard Candidate Countries Annex Table F: European Innovation Scoreboard Most recent years used (Candidate Countries)...12 Annex Table G: European Innovation Scoreboard Trends (Candidate Countries) Annex Table I: European Innovation Scoreboard Trend base years (Candidate Countries)...14 Country pages...15 Bulgaria...16 Cyprus...17 Czech Republic...18 Estonia...19 Hungary...20 Lithuania...21 Latvia...22 Malta...23 Poland...24 Romania...25 Slovenia...26 Slovakia...27 Turkey...28 Technical details...29 A.1 Calculating averages...29 A.2 Calculating trend data

5 1. Introduction 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 countries in December 2002; while they will continue with Bulgaria and Romania. Negotiations have not yet started with Turkey (TR). This report gives the full results for the Candidate countries for Trend Chart s third annual European Innovation Scoreboard (EIS). The EIS for the Candidate countries contains 15 main indicators and 3 alternative indicators divided into four categories: Human resources for innovation, comprising 5 main indicators: 1.1 New S&E graduates ( of years age class) 1.2 Population with tertiary education (% of years age classes) 1.3 Participation in life-long learning (% of years olds) 1.4 Employment in medium-high and high-tech manufacturing (% of total workforce) 1.5 Employment in high-tech services (% of total workforce) The creation of new knowledge, comprising 3 main indicators: 2.1 expenditures (GERD - BERD) (% GDP) 2.2 Business expenditure on R&D (BERD) (% GDP) USPTO high-tech patent applications per million population and one alternative indicator: 2.3.1A All EPO patent applications (per million population) (replacing EPO hightech patent applications), The transmission and application of knowledge, comprising 3 main indicators: 3.1 SMEs innovating in-house (% of manufacturing SMEs) 3.2 Manufacturing SMEs involved in innovation co-operation 3.3 Innovation expenditures (% of all turnover in manufacturing) Innovation finance, outputs and markets, comprising 4 main indicators: 4.1 High-tech venture capital investment ( of GDP) 4.2 New capital raised on stock markets (% of GDP) 4.3 New to market products (% of sales by manufacturing firms) 4.5 enditures (% of GDP) and two alternative indicators: 4.4A (% of population) (replacing 4.4 Home internet access per household) 4.6A Stock of inward FDI (% of GDP) (replacing 4.6 Percent of manufacturing valueadded from high technology) The three alternative indicators replace those used in the EU Member states EIS 4 for two different reasons. Two indicators are possibly more appropriate for economies in transition than the indicators for the EU Member states. These include all EPO patent applications EPO (2.3.1A) versus high technology EPO 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 only (4.4). 4 Where available, data for indicators 2.3.1, 4.4 and 4.6 will be presented but will not be analysed. 2

6 EIS Results for the Candidate countries The 2002 EIS results for the Candidate countries are given in Annex Table E, with trend results in Annex Table G. Brief definitions of each indicator are given in Annex Table A 5. Annex Table F 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, and Annex Table I includes the trend base years. For comparison, both Annex Tables E and G include the EU average. Full data details per country are provided in the Annex Country pages. A 2001 report for the European Commission replicated the 2001 EIS for six Candidate countries 6 (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 markets 7. 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 eight countries: Bulgaria, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Malta and Turkey. On average, the 2002 EIS has data for 66% of the indicators, ranging from a low of 38% for Cyprus to a high of 81% for Lithuania and Turkey. In order to maintain comparability, EUROSTAT data were used even when (more recent) national estimates were available. Only for the R&D indicators, more recent national estimates were used where available. Years of current performance were chosen to reflect those used in the Member states EIS. For S&E graduates for Bulgaria, Estonia and Latvia 2000 data were thus used even when 2001 national estimates were available. National estimates have only marginally been checked for reliability. In those cases were indicator values appeared to be too high, GSO members or their representatives were asked for more details. 2.1 Leading Candidate countries Table 1 identifies the innovation leaders among the Candidate countries and gives the EU and Candidate countries means. The table only includes the alternative indicators for all EPO patents, population with internet access, and inward FDI. None of the Candidate countries are above the EU mean for five of the 13 available indicators: high-tech services employment, business R&D, all EPO patents, high-tech USPTO patents, and internet access. The Candidate countries perform favourably compared to the EU for the share of the working-age 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), enditures (with the Czech Republic, Estonia, Hungary and Latvia close to or above the EU mean), and the stock of inward FDI (with the Czech Republic, Estonia, Hungary and Malta above the EU mean). 5 Full definitions are available in Technical Paper No 4: Indicators and Definitions and in Technical Paper No 6: Methodological Report. 6 European Commission DG Enterprise, Innovation policy issues in six candidate countries: The challenges, EUR 17036, Most Candidate countries do 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 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 Romania has planned the launching of the questionnaire for the 1st quarter of 2003, Bulgaria is planning a test survey for

7 For 3 indicators, Candidate countries are above the best performing EU member state: Lithuania for both working-age population with tertiary education and high-tech venture capital 8, and Malta for sales of new to market products 9 (not shown in Table 1). Table 1. Innovation leaders among the Candidate countries No Indicator 1 EU mean 2 CC mean 3 CC leaders 1.1 S&E graduates / years (SI) 9.4 (LT) 6.8 (EE) 1.2 Population with tertiary education (LT) 29.4 (EE) 26.8 (CY) 1.3 Participation in life-long learning (LV) 9.7 (MT) 5.3 (EE) 1.4 Employment in med/high-tech manufacturing (CZ) 8.8 (HU) 8.7 (SI) 1.5 Employment in high-tech services (EE) 3.2 (HU) 3.2 (CZ) 2.1 / GDP (SI) 0.54 (CZ) 0.53 (EE/LT/TR) 2.2 / GDP (SI) 0.81 (CZ) 0.45 (SK) 2.3.1A All EPO patents / population (SI) 16.1 (HU) 12.1 (CZ) High-tech USPTO patents / population (MT) 0.6 (CZ) 0.5 (LT) 4.1 High-tech venture capital / GDP (LT) 0.62 (LV) 0.15 (SI) 4.4A / 100 population (EE) 30.0 (SI) 25.4 (MT) 4.5 enditure / GDP (EE) 9.5 (CZ) 8.9 (HU) 4.6A / GDP (MT) 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. Insufficient data are available for calculating weighted means. Innovative capabilities in the Candidate countries are dominated by less than half of the countries, with 88% of the leading slots in Table 1 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 performing Candidate countries At 45%, the Lithuanian percentage of working-age population with some form of tertiary education seems to be too high, compared to 36.5% in the US and 32.5% in Finland, but differences in educational systems and definitions may be one possible explanation. 9 The figure for indicator 4.3 for Malta is very high because of one multinational: ST Microelectronics. 10 Turkey does perform relatively well for indicator 4.2 (capital raised on parallel markets plus by new firms on main markets), but due to limited data, this indicator is only available for three countries and is therefore not included in the analysis in this report. 4

8 2.2 Current trends Trend results for the Candidate countries are summarized in Table 2. 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 countries 11. The full results are given in Annex Table G. 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 these 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 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 2 gives both the two leading countries and the two countries with the largest negative trends. For the indicators in group 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. No Indicator 1 Table 2. Trends in innovation performance (% change) in the Candidate countries EU Mean 2 CC Mean 3 CC leaders CC decreases 1.1 S&E graduates / years (LT) 38.2 (EE) (HU) 1.2 Population with tertiary education (BG) 14.2 (RO) -1.1 (SI) -0.1 (EE) 1.3 Participation in life-long learning (RO) 7.9 (LV) -7.5 (LT) -7.0 (EE) 1.4 Employment in med/high-tech manufacturing (LV) 20.0 (EE) (RO) (LT) 1.5 Employment in high-tech services (SI) 24.3 (CY) (LT) -8.6 (RO) 2.1 / GDP (TR) 26.0 (CZ) (RO) (SK) 2.2 / GDP (TR) 83.7 (LV) (RO) (BG) 4.4A / 100 population (MT) (BG) 4.5 enditure / GDP (PL) 38.9 (SK) 4.6A / GDP (SK) (BG) -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. 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, internet access and inward FDI, while Latvia is leading for participation in life-long learning, employment in medium/high-tech manufacturing and business R&D. Although Romania is the worst affected by decreases in both R&D and the 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, several of these leading trends for individual countries are derived from very low initial values, so that 11 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. 5

9 even after rapid growth the trend leaders are often below the indicator average for the Candidate countries. 2.3 Relative strengths and weaknesses Table 3 summarizes the relative strengths and weaknesses of each Candidate country. Only those indicators are considered for which current levels are available for at least 10 countries 12. The results are limited to a maximum of four current indicators or trends that are at least 20% (above or below) the CC mean. Some countries are weak in several related indicators, such as the three education or two R&D indicators. These are treated as a single indicator. Table 3. Relative strengths and weaknesses of Candidate countries Country Major relative strengths Major relative weaknesses Bulgaria Cyprus Trend for internet access (4.4A) and inward FDI (4.6A) Current tertiary education (1.2) and internet access (4.4A) Czech Republic Current medium/hi-tech manufacturing employment (1.4), business R&D (2.2) and EPO patents (2.3.1A) Estonia Hungary Lithuania Latvia Malta Poland Current tertiary education (1.2), internet access (4.4A) and inward FDI (4.6A) Current medium/hi-tech manufacturing employment (1.4) and EPO patents (2.3.1A); trend for internet access (4.4A) Current education (1.1 and 1.2); trend for S&E graduates (1.1) and internet access (4.4A) Current life-long learning (1.3); trend for medium/hi-tech manufacturing employment (1.4) and business R&D (2.2) Current life-long learning (1.3), internet access (4.4A) and inward FDI (4.6A); trend for internet access (4.4A) Current medium/hi-tech manufacturing employment (1.4) Current business R&D (2.2), EPO patents (2.3.1A) and internet access (4.4A); trend for business R&D (2.2) Current medium/hi-tech manufacturing employment (1.4) and business R&D (2.2); trend for inward FDI (4.6A) Current education (1.1 and 1.2) Trend for business R&D (2.2) Current education (1.1 and 1.3); trend for S&E graduates (1.1) and inward FDI (4.6A) Current business R&D (2.2), EPO patents (2.3.1A) and internet access (4.4A) Current medium/hi-tech manufacturing employment (1.4), EPO patents (2.3.1A) and internet access (4.4A); trend for internet access (4.4A) Current tertiary education (1.2) and ICT expenditures (4.5) Current tertiary education (1.2), EPO patents (2.3.1A) and internet access (4.4A); trend for internet access (4.4A) Romania Trend for life-long learning (1.3) Current life-long learning (1.3), public R&D (2.1) and EPO patents (2.3.1A) Slovenia Current S&E graduates (1.1), business R&D (2.2), EPO patents (2.3.1A) and internet access (4.4A) Slovakia Turkey Current medium/hi-tech manufacturing employment (1.4) and business R&D (2.2); trend for inward FDI (4.6A) Current public R&D (2.1); trend for R&D (2.1 and 2.2) Current life-long learning (1.3) and inward FDI (4.6A); trend for inward FDI (4.6A) Current tertiary education (1.2) and public R&D (2.1); trend for internet access (4.4A) Current medium/hi-tech manufacturing employment (1.4), internet access (4.4A) and inward FDI (4.6A) All countries have some strengths, although these are limited to trends for the less innovative countries of Bulgaria and Romania. The strengths of the more innovative Candidate countries (Czech 12 USPTO high-tech patents are not included as the absolute patent counts are very low and trends are volatile over time. 6

10 Republic, Estonia, Hungary, Lithuania, Malta and Slovenia) are dominated by current conditions, except for Lithuania, which has a strong trend for both S&E graduates and internet access. For some countries, an indicator can be both a current and trend strength: S&E graduates for Lithuania, internet access for Malta 13, and business R&D for Turkey. Both high-tech services employment and ICT expenditures are no strength for any country. Relative weaknesses are evenly spread over indicator categories one, two and four. Weaknesses for human resources and knowledge creation are mostly current weaknesses, except for a weak trend for S&E graduates for Hungary and for business R&D for Bulgaria and Estonia. For innovation finance, output and markets weaknesses are both of a current and trend nature: internet access is a current weakness for Bulgaria and Lithuania, a trend weakness for Slovakia, and both for Latvia and Poland. The stock of inward FDI is a current weakness for Turkey, a trend weakness for Cyprus and Hungary, and both for Slovenia. 2.4 Variation per indicator Table 4 gives a measure of the amount of variation for each indicator 14. The highest variation between Candidate countries is in the financial indicator and both patent indicators. The lowest variation is in S&E graduates, high-tech services employment, public R&D, and enditures. Compared to the results for the EU member states, the variation differs for 5 of 10 comparable indicators, in particular for human resources where the variation for the Candidate countries is much smaller than that for the member states. For both groups we also see that the variation for public R&D is half of that for business R&D. No Table 4. Variation of indicators between Candidate countries Indicator Variation Candidate countries 1 Variation Member States New S&E graduates Low 39.7 Medium Pop with 3rd education Medium 59.2 Low Life-long learning Medium 77.6 High Employment in med/hi-tech manufacturing Medium 51.7 Low Employment in hi-tech services Low 23.9 Low / GDP Low 39.4 Low / GDP Medium 77.8 Medium A EPO patents / pop High USPTO hi-tech patents / pop High High Hi-tech venture capital / GDP High Medium A / 100 pop Medium 61.1 Low enditures / GDP Low 39.3 Low A / GDP Low : Coefficient of variation or CV (standard deviation/mean*100) 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. For the Candidate countries, all low CVs are below 40, the medium CVs lie between 50 and 80, and the high CVs are above Malta s strong performance in internet access contradicts sharply with its weakness in current ICT expenditures. 14 A convergence/divergence analysis similar to that for the member states (cf. Technical Paper No 1: Member States and Associate Countries) is not possible due to limited data availability. 7

11 2: These results are for indicator 4.4 and are included for illustrative reasons only as they are, although of a similar nature, not directly comparable to those for indicator 4.4A. 8

12 ANNEX Main Data Tables Table A: European Innovation Scoreboard Data Definitions and Sources Table E: European Innovation Scoreboard Candidate Countries Table F: European Innovation Scoreboard Most recent years used (Candidate Countries) Table G: European Innovation Scoreboard Trends (Candidate Countries) Table I: European Innovation Scoreboard Trend base years (Candidate Countries) Country pages Technical details 9

13 Annex Table A: European Innovation Scoreboard Data Definitions and Sources No 1 Short definition of indicator Source 1. Human resources 1.1 New S&E graduates ( of years age class) EUROSTAT, Education statistics (Structural Indicator 2.4) Population with tertiary education (% of years age class) EUROSTAT, Labour Force Survey Participation in life-long learning (% of years age class) EUROSTAT, Labour Force Survey (Structural Indicator 1.5) Employment in medium-high and high-tech manufacturing (% of total workforce) EUROSTAT, Labour Force Survey Employment in high-tech services (% of total workforce) EUROSTAT, Labour Force Survey 2 2. Knowledge creation 2.1 expenditures (GERD BERD) (% of GDP) EUROSTAT, R&D statistics (Structural Indicator 2.1); OECD Business expenditures on R&D (BERD) (% of GDP) EUROSTAT, R&D statistics (Structural Indicator 2.1); OECD EPO high-tech patent applications (per million population) EUROSTAT A EPO patent applications (per million population) EUROSTAT USPTO high-tech patent applications (per million population) USPTO (US Patent and Trademark Office) 2 3. Transmission and application of knowledge 3.1 SMEs innovating in-house (% of manufacturing SMEs) EUROSTAT, Community Innovation Survey SMEs involved in innovation co-operation (% of manufacturing SMEs) EUROSTAT, Community Innovation Survey Innovation expenditures (% of all turnover in manufacturing) EUROSTAT, Community Innovation Survey 2 4. Innovation finance, output and markets 4.1 High technology venture capital investment (% of GDP) European Private Equity & Venture Capital Association (EVCA): Mid-Year Survey of Pan-European Private Equity & Venture Capital Activity Capital raised on parallel markets plus by new firms on main markets (% of GDP) World Federation of Exchanges (FIBV) 4.3 Sales of new to market products (% of all turnover in manufacturing) EUROSTAT, Community Innovation Survey Home internet access (% of all households) EUROSTAT (Structural Indicator 2.3a) 2 4.4A Home internet access (per 100 population) EUROSTAT 4.5 enditures (% of GDP) EUROSTAT (Structural Indicator 2.7); WITSA/IDC: Digital Planet Share of manufacturing value-added in high-tech sectors EUROSTAT, Structural Business Statistics 2 4.6A stock (% of GDP) UNCTAD: World Investment Report 1: Indicator numbers followed by A are alternative indicators used for Candidate countries only. 2: For some of the Associate and Candidate countries national estimates are used (as collected by the questionnaires distributed to the GSO Senior Officials in Innovation Policy). Annex Tables B and E give these national estimates in italics. 10

14 Annex Table E: European Innovation Scoreboard Candidate Countries 1 No 2 Indicator EU BG CY CZ EE HU LT LV MT PL RO SI SK TR 1.1 New Pop with 3 rd education Life-long learning Empl med/hi-tech manufacturing Empl hi-tech services / GDP / GDP EPO hi-tech patents / pop A EPO patents / pop USPTO hi-tech patents / pop 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 A Home internet access / pop enditures / GDP Manuf hi-tech value-added share A / GDP : Data in italics are national estimates taken from the questionnaires. 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. 11

15 Annex Table F: European Innovation Scoreboard Most recent years used (Candidate Countries) No 1 Indicator BG CY CZ EE HU LT LV MT PL RO SI SK TR 1.1 New Pop with 3 rd education Life-long learning Empl med/hi-tech manufacturing Empl hi-tech services / GDP / GDP EPO hi-tech patents / pop A EPO patents / pop USPTO hi-tech patents / pop SMEs innov in-house SMEs innov co-op Innovation exp Hi-tech venture capital / GDP New capital 2 00/01 99/00 00/ New-to-market prod Home internet access / household A Home internet access / pop enditures / GDP Manuf hi-tech value-added share A / GDP : Indicators 2.3.1A, 4.4A and 4.6A are alternative indicators. 2: Unweighted average of last two years. 12

16 Annex Table G: European Innovation Scoreboard Trends (Candidate Countries) 1 No 2 Indicator EU BG CY CZ EE HU LT LV MT PL RO SI SK TR 1.1 New Pop with 3 rd education Life-long learning Empl med/hi-tech manufacturing Empl hi-tech services / GDP / GDP EPO hi-tech patents / pop A EPO patents / pop USPTO hi-tech patents / pop SMEs innov in-house 3.2 SMEs innov co-op 3.3 Innovation exp 4.1 Hi-tech venture capital / GDP New capital 4.3 New-to-market prod 4.4 Home internet access / household A Home internet access / pop enditures / GDP Manuf hi-tech value-added share A / GDP : 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. 13

17 Annex Table I: European Innovation Scoreboard Trend base years (Candidate Countries) No 1 Indicator BG CY CZ EE HU LT LV MT PL RO SI SK TR 1.1 New Pop with 3 rd education Life-long learning Empl med/hi-tech manufacturing Empl hi-tech services / GDP / GDP EPO hi-tech patents / pop A EPO patents / pop USPTO hi-tech patents / pop SMEs innov in-house 3.2 SMEs innov co-op 3.3 Innovation exp 4.1 Hi-tech venture capital / GDP New capital 4.3 New-to-market prod 4.4 Home internet access / household A Home internet access / pop enditures / GDP Manuf hi-tech value-added share A / GDP : Indicators 2.3.1A, 4.4A and 4.6A are alternative indicators. 14

18 Country pages The following pages give for each Candidate country: the European Innovation Scoreboard 2002 data; the base year data used for calculating the trends; the data source from which the data were taken. The data values used for the EIS 2002 are given in bold, the base year data in italic. Each country page also contains two graphs, one showing the current performance relative to the EU and the other showing the trend performance relative to EU. Indicators more than 20 percent above the EU mean are highlighted in green, indicators more than 20 percent below the EU mean in red. Indicators close to the EU mean are highlighted in yellow. The following data sources are used: EUROSTAT: indicators 1.2, 1.3, 1.4, 1.5, 2.1, 2.2, 2.3.1A, 3.1, 3.2, 4.4, 4.4A and 4.5; OECD: indicators 2.1 and 2.2; USPTO: indicator 2.3.2; FIBV: indicator 4.2; WITSA/IDC: indicator 4.5; UNCTAD: indicator 4.6A. National estimates taken from the questionnaires were used to complement the above data sources. In order to maintain comparability, EUROSTAT data were used even when (more recent) national estimates were available. Only for the R&D indicators, more recent national estimates were used where available. Years of current performance were chosen to reflect those used in the Member states EIS. For S&E graduates for Bulgaria, Estonia and Latvia 2000 data were thus used even when 2001 national estimates were available. National estimates have only marginally been checked for reliability. In those cases were indicator values appeared to be too high, GSO members or their representatives were asked for more details. Eight countries returned their questionnaire: Bulgaria, Czech Republic, Estonia, Lithuania, Latvia, Malta and Turkey. 15

19 Bulgaria Work pop w 3rd educ % Lifelong learning manuf serv Work pop w 3rd educ Lifelong learning manuf 0% EPO patents USPTO hi-tech patents 1 2 serv SMEs innov in-house SMEs innov co-op Innovation exp -43% 13% Hi-tech venture capital New capital 71% New-to-market prod 24 3% 47 82% Level relative to EU -60% -30% 0% 30% 60% 90% Trend relative to EU Indicator Source Trend 1.1 New NSI Pop with 3 rd education Eurostat NSI Life-long learning Empl med/hi-tech manufacturing Eurostat NSI Empl hi-tech services Eurostat NSI / GDP Eurostat NSI / GDP Eurostat NSI EPO hi-tech patents / pop A EPO patents / pop Eurostat USPTO hi-tech patents / pop USPTO 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 A / pop Eurostat enditures / GDP WITSA/IDC Manuf hi-tech value-added share NSI A / GDP UNCTAD NSI = National Statistical Institute Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 16

20 Cyprus Work pop w 3rd educ 126 Lifelong learning manuf serv Work pop w 3rd educ Lifelong learning manuf -2% -2% EPO patents USPTO hi-tech patents 4 serv 6% SMEs innov in-house SMEs innov co-op Innovation exp Hi-tech venture capital New capital -56% New-to-market prod % Level relative to EU -125% -100% -75% -50% -25% 0% 25% Trend relative to EU Indicator Source Trend 1.1 New Pop with 3 rd education Eurostat Life-long learning Eurostat Empl med/hi-tech manufacturing Eurostat Empl hi-tech services Eurostat / GDP Eurostat / GDP Eurostat EPO hi-tech patents / pop A EPO patents / pop Eurostat USPTO hi-tech patents / pop 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 A / pop Eurostat enditures / GDP Manuf hi-tech value-added share A / GDP UNCTAD Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 17

21 Czech Republic Work pop w 3rd educ Lifelong learning manuf serv Work pop w 3rd educ Lifelong learning manuf -11% 7% EPO patents USPTO hi-tech patents 5 8 serv -18% SMEs innov in-house 28% SMEs innov co-op Innovation exp 7% Hi-tech venture capital New capital 9-1% New-to-market prod 43 19% % Level relative to EU -30% -20% -10% 0% 10% 20% 30% 40% Trend relative to EU Indicator Source Trend 1.1 New MR Pop with 3 rd education Eurostat Life-long learning Empl med/hi-tech manufacturing Eurostat CzSO Empl hi-tech services Eurostat CzSO / GDP OECD CzSO / GDP OECD CzSO EPO hi-tech patents / pop A EPO patents / pop Eurostat USPTO hi-tech patents / pop USPTO SMEs innov in-house SMEs innov co-op Innovation exp Hi-tech venture capital / GDP DGE New capital New-to-market prod Home internet access / household A / pop Eurostat enditures / GDP WITSA/IDC Manuf hi-tech value-added share A / GDP UNCTAD CzSO = Czech Statistical Office MR = Mickiewicz and Radosevic: "Innovation capabilities of the six EU candidate countries: comparative data based analysis", September 2001 DGE = DG Enterprise: Innovation Policy in Six Candidate Countries, September 2001 Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 18

22 Estonia Work pop w 3rd educ % Lifelong learning manuf serv Work pop w 3rd educ Lifelong learning manuf -28% -18% 22% EPO patents USPTO hi-tech patents 5 serv 4% SMEs innov in-house 75-1% SMEs innov co-op 116 Innovation exp 64 21% Hi-tech venture capital New capital -7% New-to-market prod 93-1% % Level relative to EU -40% -30% -20% -10% 0% 10% 20% 30% Trend relative to EU Indicator Source Trend 1.1 New ESA + EME Pop with 3 rd education Eurostat ESA Life-long learning Eurostat ESA Empl med/hi-tech manufacturing Eurostat ESA Empl hi-tech services Eurostat ESA / GDP Eurostat ESA / GDP Eurostat ESA EPO hi-tech patents / pop A EPO patents / pop Eurostat USPTO hi-tech patents / pop SMEs innov in-house ESA SMEs innov co-op ESA Innovation exp ESA Hi-tech venture capital / GDP New capital New-to-market prod ESA Home internet access / household Eurostat A / pop Eurostat enditures / GDP Eurostat WITSA/IDC Manuf hi-tech value-added share A / GDP UNCTAD ESA = Statistical Office of Estonia EME = Estonian Ministry of Education Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 19

23 Hungary Work pop w 3rd educ % Lifelong learning manuf serv Work pop w 3rd educ Lifelong learning manuf -23% -12% 9% EPO patents USPTO hi-tech patents 2 11 serv -1% SMEs innov in-house SMEs innov co-op Innovation exp 12% 21% Hi-tech venture capital New capital 14 44% New-to-market prod 47 17% % Level relative to EU -100% -50% 0% 50% Trend relative to EU Indicator Source Trend 1.1 New HCSO Pop with 3 rd education Eurostat HCSO Life-long learning Eurostat HCSO Empl med/hi-tech manufacturing Eurostat HCSO Empl hi-tech services Eurostat HCSO / GDP OECD HCSO / GDP OECD HCSO EPO hi-tech patents / pop HCSO A EPO patents / pop Eurostat USPTO hi-tech patents / pop USPTO SMEs innov in-house SMEs innov co-op Innovation exp Hi-tech venture capital / GDP HVCA New capital New-to-market prod Home internet access / household HCSO A / pop Eurostat enditures / GDP Eurostat 8.00 WITSA/IDC Manuf hi-tech value-added share HCSO A / GDP UNCTAD HCSO = Hungarian Central Statistical Office HVCA = Hungarian Venture Capital Association Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 20

24 Lithuania Work pop w 3rd educ % Lifelong learning manuf serv Work pop w 3rd educ Lifelong learning manuf -29% -10% -13% EPO patents USPTO hi-tech patents 1 4 serv -30% SMEs innov in-house % SMEs innov co-op 107 Innovation exp -36% Hi-tech venture capital New capital % New-to-market prod % Level relative to EU -50% -25% 0% 25% 50% Trend relative to EU Indicator Source Trend 1.1 New StD Pop with 3 rd education Eurostat StD Life-long learning Eurostat StD Empl med/hi-tech manufacturing Eurostat StD Empl hi-tech services Eurostat StD / GDP Eurostat StD / GDP Eurostat StD EPO hi-tech patents / pop A EPO patents / pop Eurostat USPTO hi-tech patents / pop USPTO SMEs innov in-house Eurostat SMEs innov co-op Eurostat Innovation exp Hi-tech venture capital / GDP StD New capital New-to-market prod Home internet access / household Eurostat A / pop Eurostat enditures / GDP Eurostat 5.90 StD Manuf hi-tech value-added share StD A / GDP UNCTAD StD = Lithuanian Department of Statistics Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 21

25 Latvia 54 Work pop w 3rd educ 86 Lifelong learning 192 manuf 23 serv EPO patents 2 USPTO hi-tech patents SMEs innov in-house SMEs innov co-op Innovation exp Hi-tech venture capital 258 New capital New-to-market prod Level relative to EU Work pop w 3rd educ Lifelong learning manuf serv -66% -73% -14% -14% -14% -10% -13% 78% -100% -50% 0% 50% 100% Trend relative to EU 108% Indicator Source Trend 1.1 New CSB Pop with 3 rd education Eurostat CSB Life-long learning CSB Empl med/hi-tech manufacturing Eurostat CSB Empl hi-tech services Eurostat CSB / GDP Eurostat CSB / GDP Eurostat CSB EPO hi-tech patents / pop A EPO patents / pop Eurostat USPTO hi-tech patents / pop SMEs innov in-house SMEs innov co-op Innovation exp Hi-tech venture capital / GDP CSB New capital New-to-market prod Home internet access / household CSB A / pop Eurostat enditures / GDP Eurostat Manuf hi-tech value-added share A / GDP UNCTAD CSB = Central Statistical Bureau of Latvia Values in bold give the current levels used in the 2002 EIS. Values in italic give the base years used in calculating the trends. 22