Innovation Union Competitiveness report 2011 Methodological annex

© European Union, 2011. Reproduction is authorised provided the source is acknowledged.

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Methodological Annex

1. Symbols and abbreviations

Country codes BE Belgium SE Sweden BG Bulgaria UK United Kingdom CZ Czech Republic EU European Union DK Denmark IS Iceland DE Germany LI Liechtenstein IE Ireland NO Norway EL Greece CH Switzerland ES Spain HR Croatia FR France MK The former Yugoslav Republic of Macedonia IT Italy TR Turkey CY Cyprus IL Israel LV Latvia ERA European Research Area LT Lithuania US United States LU Luxembourg JP Japan HU Hungary CN China MT Malta KR South Korea NL Netherlands IN India AT Austria TW Chinese Taipei PL Poland SG Singapore PT Portugal RU Russian Federation RO Romania AU Australia SI Slovenia CA Canada SK Slovakia ZA South Africa FI Finland BR Brazil RoW Rest of the World

Other abbreviations

: ‘not available’

- ‘not applicable’ or ‘real zero’ or ‘zero by default’

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2. General definitions

The NUTS classification Definition: The Nomenclature of Statistical Territorial Units (NUTS) is a single coherent for dividing up the European Union’s territory in order to produce regional statistics for the Community. NUTS subdivides each Member State into a whole number of regions at NUTS I level. Each of these is then subdivided into regions at NUTS level 2 and these in turn into regions at NUTS level 3. Source: Eurostat Gross Domestic Product (GDP) Definition: Gross domestic product (GDP) data have been compiled in accordance with the European System of Accounts (ESA 1995). Since 2005, GDP has been revised upwards for the majority of EU Member States following the allocation of FISIM (Financial Intermediation Services Indirectly Measured) to user sectors. This has resulted in a downward revision of R&D intensity for individual Member States and for the EU. Source: Eurostat Value Added Definition: Value added is current gross value added measured at producer prices or at basic prices, depending on the valuation used in the national accounts. It represents the contribution of each industry to GDP. Sources: Eurostat, OECD Purchasing Power Standards (PPS) Definition: Financial aggregates are sometimes expressed in Purchasing Power Standards (PPS), rather than in euro based on exchange rates. PPS are based on comparisons of the prices of representative and comparable goods or services in different countries in different currencies on a specific date. The calculations on R&D investments in real terms are based on constant 2000 PPS. Source: Eurostat Venture Capital Definition: Venture Capital investment is defined as private equity being raised for investment in companies. Management buyouts, management buy-ins, and venture purchase of quoted shares are excluded. Venture Capital includes early stage (seed + start-up) and expansion and replacement capital. Source: Eurostat Small and medium-size enterprises Definition: For the purposes of this publication, small and medium-size enterprises (SMEs) are defined as enterprises having fewer than 250 employees. Sources: Eurostat, OECD

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3. Research and Innovation

Community Trademark Definition: A Community Trademark is any trademark which is pending registration or has been registered in the EU as a whole (rather than on a national level within the EU).

Source: OHIM / Eurostat

Country groupings – methodology In order to create homogeneous groups of similar research and innovation systems in the European Research Area, a principal components analysis (PCA) on nineteen variables characterising research and innovation systems was carried out. The values of the variables as were obtained for 2008 or the latest available year from Eurostat and the OECD and included data for all 27 EU Member States as well as for Norway, Switzerland, Croatia, Turkey and Israel. Table 1 presents the main values of the different factors accruing from the PCA. The first principal component explains 49.7% of the variance and represents. The second principal component explains 12.4% of the variance and together, the two principal components manage to explain above 62% of the total variance.

Table 1: Results of the Principal Component Analysis Table 2 presents the correlation matrix between the main components and the individual variables that can help interpreting the nature of these factors. To a great extent, Component 1 corresponds to the economic and technological development of the country. As shown by the correlation matrix, this factor is closely related with per capita GDP, investments in R&D, HRST, research excellence, patents and levels of skills and employment. The second component represents the sectoral specialisation, as it is shown by the coordinates of industrial employment and employment in medium-high and high tech manufactures.

0.84220.05331.01292575Factor 5

0.78890.06481.23153877Factor 4

0.7240.10331.96210394Factor 3

0.62080.12382.35266703Factor 2

0.49690.49699.44203858Factor 1

CumulativeProportionEigenvalue

0.84220.05331.01292575Factor 5

0.78890.06481.23153877Factor 4

0.7240.10331.96210394Factor 3

0.62080.12382.35266703Factor 2

0.49690.49699.44203858Factor 1

CumulativeProportionEigenvalue

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Table 2: Correlation matrix between the principal components and the individual variables Factor1 Factor2 Factor3 Factor4 Factor5

GERD as % of GDP 0.88045 0.34761 0.1694 0.09631 -0.06329BERD as % of GDP 0.86653 0.37803 0.0769 0.10575 -0.03081GOVERD as % of GDP 0.07583 0.26135 0.55564 -0.44498 0.49791HERD as % of GDP 0.77148 0.08173 0.20893 0.25351 -0.41071HRST as % of total population 0.84051 -0.32415 0.24602 -0.09118 0.16476EPO patent applications per million population 0.85114 0.24681 -0.1413 0.04174 -0.02927EPO high-tech patents per million population 0.82359 0.28775 -0.08296 0.01004 -0.02086Population aged 25-64 having completed tertiary education 0.76955 -0.39397 0.23008 -0.10595 0.04449Participation in life-long learning 0.8845 -0.00273 0.21098 0.24563 -0.03637Employment in primary sectors -0.63319 0.01507 0.40398 -0.07697 -0.32419Employment in industrial sectors -0.5726 0.60788 0.22957 0.32484 0.2158Employment in business and financial sectors 0.59243 0.03313 -0.52275 -0.38809 0.16055Employment in high-tech and medium-high-tech manufacturing -0.07533 0.88354 0.0989 0.10371 0.24159Employment in knowledge-intensive services (KIS) 0.90799 -0.08451 -0.00034 0.15404 0.08702Population density -0.05817 -0.08058 -0.69541 0.49535 0.29596Employment rate 0.70931 -0.29551 0.44466 0.10663 0.07883GDP per capita 0.75882 -0.09803 -0.28462 -0.27672 0.20282GDP natural logarithm 0.17245 0.584 -0.29413 -0.48494 -0.41219Research excellence (highly-cited scientific publications) 0.89965 0.08266 -0.2061 0.04531 -0.10682 Based on the findings of the PCA, a hierarchical cluster analysis is carried out in order to gather the regions in homogeneous groups. Figure 1 presents the dendogramme presenting the different groups as well as the bar separating the different country groups.

Figure 1: Cluster Analysis- Dendogramme EU Industrial R&D Investment Scoreboard Definition: The EU Industrial R&D Investment Scoreboard presents information on the top 1000 EU companies and the 1000 non-EU companies. The Scoreboard includes data on R&D investment along with other economic and financial data. It is the source for the ICT

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Scoreboard which provides data on the ICT companies with the largest R&D budgets globally.

Framework Programme Definition: The Framework Programmes for Research and Technological Development are the EU's main instruments for supporting collaborative research, development and innovation in science, engineering and technology. Participation is on an internationally collaborative basis and must involve European partners. The first Framework Programme was launched in 1984. The seventh Framework Programme (FP7) covers the period 2007-2013. Source: DG Research and Innovation The international dimension of the Seventh framework programme for research and technological development1

Each of the four specific programmes “Cooperation”, “Capacities”, “Ideas”, “People” supports international cooperation through various instruments and mechanisms. As far as “Cooperation” is concerned, international cooperation activities take two forms:

• The “general opening”, which can be either “passive” - all thematic areas are open to all third countries - or “targeted”, namely particularly encouraged for certain countries/ country groups or emphasised for certain themes.

• The “Specific International Collaboration Actions” (SICA) aims to reinforce research capacity in European Neighbourhood Countries and to address the particular needs of developing and emerging economies by means of dedicated cooperative activities. Specific participation criteria apply to SICA: Participation of a minimum of two Member States or Associated Countries plus two targeted International Cooperation Partner Countries. The SICA is therefore to be seen as a mechanism for a specifically bilateral or bioregional cooperation.

• In order to complement and to facilitate international participation in the different programmes, one of the seven activities under “Capacities” is fully dedicated to international cooperation and covers support measures for third countries and regions. The objectives of these activities are:

° To create platforms for a structured S&T policy dialogue (INCO-NET) between authorities and stakeholders of the EU and the regions/countries concerned;

° to disseminate information, provide assistance, favour partnership building (BILAT), with a view to facilitate access and promote participation in the 7th FP;

° to coordinate international cooperation activities of the Member States (ERA-NET) in order to enhance their international engagement and achieve critical mass in given areas and specific countries/regions.

The “People” specific programme also has a substantial international dimension: It aims to increase the quality of European research by attracting research talent to Europe, providing opportunities for European researchers to abroad and fostering mutually beneficial research 1 SEC (2007) 47 "A New Approach to International S&T Cooperation in the EU's 7th Framework Programme (2007-2013)", 12 January 2007.

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collaboration with researchers from outside Europe. A new instrument, the International Research Staff Exchange Scheme – IRSES – work was developed in FP7 strengthening institutional partnerships between European research organisation and “counterparts” from countries with which the Community has S&T agreements or which are covered by the European Neighbourhood Policy. The “Ideas” Specific Programme aims to support excellence by funding investigator initiated frontier research across all fields of science carried out by individual researchers or research teams. The principal investigator can be of any nationality, but the work must be carried out in Europe. Marie Curie Actions (FP6) The Human Resources and Mobility (HRM) activity within FP6 had a budget of € 1,580 million, being the largest mobility scheme at EU level. The scheme, known as the Marie Curie Actions, aimed at providing advanced training tailored to researchers' individual needs in order to become professionally independent and to gain complementary or different scientific skills. Individual researchers interested in taking part in a Marie Curie Action had two options, to prepare a project together with a host institution of his/her choice and submit it to the Commission (Marie Curie Individual Fellowships – IEF), or to apply directly to an institution that has been selected by the Commission for a Host-Driven Action. Eligible candidates were researchers from EU or Associated States, with at least four years of postgraduate research experience or a PhD, willing to spend a mobility period working in a host institution located in another EU or Associated State, different from his/her own and different from that where they have been recently.

Gender equity Sex and gender are often confused, but they are distinct terms with distinct meanings. Sex is a biological quality. Gender is a socio-cultural process. The two terms interact in important and complex ways, although gender is the most used and understood term nowadays. Therefore, we have opted to use the term gender, although it is essential to grasp the distinction between the two terms. Gender Equality This term refers to the situation where individuals of both sexes are free to develop their personal abilities and make choices without the limitations imposed by strict gender roles. The different behaviours, aspirations and needs of women and men are considered, valued and favoured equally. "Glass ceiling" Obstacles that hold women back from accessing the highest positions in the hierarchy. Glass Ceiling Index (GCI) The glass ceiling index (GCI) illustrates the difficulties women have in getting access to the highest levels of the hierarchy and measures their relative probability, as compared with men, of reaching a top position. The GCI compares the proportion of women in grade A positions (equivalent to Full Professors in most countries) to the proportion of women in academia (grade A, B, and C), indicating the opportunity, or lack of, for women to move up the hierarchical ladder in their profession.

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Boards The coverage of boards differs across countries, one can state that in general, boards data cover scientific commissions, R&D commissions, boards, councils, committees and foundations, academy assemblies and councils, and also different field-specific boards, councils and authorities.

Higher Education

ISCED (International Standard Classification of Education)

ISCED 5: Tertiary education (first stage) not leading directly to an advanced research qualification.

ISCED 5A: Tertiary education programmes with academic orientation.

ISCED 5B: Tertiary education programmes with occupation orientation.

ISCED 6: Tertiary education (second stage) leading to an advanced research qualification (PhD or doctorate).

High-Tech and Medium-High-Tech product exports

Definition: The value of medium and high-tech exports. These exports include exports of the following SITC Rev.3 products: 266, 267, 512, 513, 525, 533, 54, 553, 554, 562, 57, 58, 591, 593, 597, 598, 629, 653, 671, 672, 679, 71, 72, 731, 733, 737, 74, 751, 752, 759, 76, 77, 78, 79, 812, 87, 88, 891.

Source: UN (Comtrade)

High-Tech trade

Definition: High-tech trade covers exports and imports of products whose manufacture involved a high intensity of R&D. They are defined in accordance with the OECD’s high-tech product list (see OECD (1997). Revision of the High-Technology Sector and Product Classification (1997), STI Working Papers 2/1997, OECD, Paris. The indicators used in this report use the so-called 'product approach', i.e. they measure the world market share of exports of high-tech products.

Sources: Eurostat (Comext), UN (Comtrade)

Human Resources for Science and Technology (HRST), R&D personnel and researchers The Canberra Manual proposes a definition of HRST as persons who either have higher education or persons who are employed in positions that normally require such education. HRST are people who fulfil one or other of the following conditions: a) Successfully completed education at the third level in an S&T field of study (HRSTE - Education); b) Not formally qualified as above, but employed in a S&T occupation where the above qualifications are normally required (HRSTO - Occupation). HRST Core (HRSTC) are people with both tertiary-level education and an S&T occupation. Scientists and engineers are defined as ISCO categories 21 (Physical, mathematical and engineering science professionals) and 22 (Life science and health professionals).

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The Frascati Manual proposes the following definitions of R&D personnel and researchers: - R&D personnel: “All persons employed directly on R&D should be counted, as well as those providing direct services such as R&D managers, administrators, and clerical staff.” (p.92); - Researchers: “Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems and also in the management of the projects concerned.” (p.93). R&D may be the primary function of some persons or it may be a secondary function. It may also be a significant part-time activity. Therefore, the measurement of personnel employed in R&D involves two exercises: - measuring their number in headcounts (HC): the total number of persons who are mainly or partially employed in R&D is counted; - measuring their R&D activities in full-time equivalence (FTE): the number of persons engaged in R&D is expressed in full-time equivalents on R&D activities (= person-years). Public and Private sector researchers Definition: For the purposes of this publication, Public sector researchers refer to researchers in the government and higher education sectors. Private sector researchers refer to researchers in the business enterprise and private non-profit sectors. Source: Eurostat, OECD Impact of the 3% R&D Intensity target on the number of researchers needed in the European research system in 2020

Some initial background figures:

In 2008, the EU had approximately 1.5 million researchers (FTE): about 690,000 in the Private Sector; 610,000 in the Higher Education System; and 190,000 in the Public Sector. In 2000, the number of researchers was about 1.1 million: 525,000 in the Private Sector; 410,000 in Higher Education; and 170,000 in the Public Sector. These figures reveal important characteristics of the community of researchers in the EU that have to be taken into account when estimating the need for new researchers. Firstly, only half of the researchers in the EU work in the private sector, where research is more closely linked to innovation. This situation contrasts markedly with that in other countries. In the United States, almost four out of five researchers – and in Japan, two out of three researchers – work in the private sector. Secondly, the figures show that, over a period of 8 years, the number of researchers in the EU increased by almost 30% at an average annual growth rate of 3.8%. The size of the research population and R&D expenditure both increased at the same rate, while R&D intensity stagnated due to an equivalent increase in GDP. Thirdly, the increase in the number of researchers was not homogeneous across sectors. It increased by an annual average of 5% in the Higher Education System; by 3.5% in the Private Sector; and by 1.2% in the Public Sector. As a consequence, the combination of an increase in R&D intensity to 3% by 2020 and expected levels of economic growth during the period 2010-2020 will require a very sharp net increase in the number of researchers in the EU.

An approach to estimate the number of researchers needed

Estimating the net increase in the number of researchers needed in the EU is complex because many of the variables affecting this estimate co-evolve over time i.e. the value of one variable affects and interacts with the value of another and the accuracy of any estimate based on past data is therefore tentative and has to be treated with caution. Despite these difficulties, estimates can be made. As noted in the previous section, the number of researchers is related

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to the absolute level of research investment in the economy, and research investment can be decomposed into two factors: (1) an increase in GDP; and (2) an increase in research intensity. In order to calculate the impact of the increase of research investment on the number of researchers needed in the economy, a three step approach can be followed: Step 1: Calculation of the research investment in the EU in 2020 Research investment will increase due to an expansion of the overall economy and an increase in research intensity. If GDP increases at an average annual rate of 2% over the next decade, the GDP of the EU in 2020 will increase to €14,660,430 million (PPS). GDP EU (2009) = €11,790,842 million (PPS) GDP EU (2020) = GDP EU (2009) x (1+2%)11 = €14,660,430 million (PPS) As the EU target is to increase research intensity to 3%, total research investment will therefore rise in this scenario to approximately €440 billion (PPS). GERD (2020) = GDP EU (2020) x 3% = €439,813 million (PPS) Step 2: Calculation of the ratio of research investment per researcher in Europe in 2008 Levels of funding for individual researchers vary greatly depending on the characteristics of the field of research and the type of research being conducted. However, an average amount of research investment per researcher can be calculated. For the EU, this value was €151,000 (PPS) per researcher in 2008. Ratio of research investment per researcher = GERD (2008) / Number of researchers Ratio of research investment per researcher = €227,191 million (PPS) / 1.5 million researchers = €151,000 (PPS) per researcher Step 3: Calculation of the number of researchers needed in the EU in 2020, not taking into account any major change in the economic and scientific structure of the EU Once estimates of total research investment in 2020 and the ratio of research investment per researcher have been calculated, the number of researchers needed in 2020 can be calculated by dividing these estimates. This calculation yields a result of 2.95 million researchers, which represents a net increase of around 1.5 million researchers. Number of researchers (2020) = GERD (2020) / Ratio of research investment per researcher) Number of researchers (2020) = €439,813 million (PPS) / €151,000 (PPS) per researcher = 2.95 million researchers Correction of the estimate based on expected changes in economic and scientific structure

The figure of 2.95 million researchers assumes that the ratio of research investment per researcher remains constant in the EU. The evidence suggests, however, that this ratio increases as an economy becomes more research intensive. There are two main reasons for this: 1) Research intensive activities often involve higher paid researchers and better (and more costly) infrastructures, leading to higher levels of research investment per researcher. 2) Research intensive economies tend to have a high proportion of private sector research, which has a higher ratio of research investment per researcher. As a result, the initial estimate needs to be corrected to control for these factors.

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In 1996, research investment per researcher in the EU was €127,364. By 2008, however, this ratio had risen to around €151,000. These data appear to corroborate the assumption of higher research investment per researcher as R&D intensity increases. If this trend is extrapolated, research investment per researcher in the EU should approach €200,000 in 2020. This value is similar to the level of research investment per researcher in countries such as the United States, Germany, Austria or Sweden (all of which have a ratio around or above €200,000 per researcher). On the other hand, the ratio is somewhat higher than it is in other research intensive economies such as Finland, South Korea, Japan or Denmark (all of which have ratios between €140,000 and €160,000). However, the marked specialisation in ICT of Finland, South Korea and, to a lesser extent Japan, suggests that the ratio of research investment per researcher in the EU is likely to evolve towards the ratio in the first group of countries. When the correction for an increased level of research investment per researcher is applied, the resulting number of researchers needed in Europe in 2020 drops from the original estimate of 2.95 million researchers to 2.45 million researchers, i.e. a net increase of around 1 million researchers over the situation in 2008. It should also be remembered that this is an underestimate, since lack of data prevents any correction for the number of additional researchers that will be needed to replace those retiring before 2020. Innovative enterprises Definition: Enterprises that introduce new or significantly improved products (goods or services) to the market or enterprises that implement new or significantly improved processes. Innovations are based on the results of new technological developments, new combinations of existing technology or the utilisation of other knowledge acquired by the enterprise.

Knowledge-Intensive Activities (KIAs) Definition: Knowledge-Intensive Activities (KIAs) are defined as economic sectors in which more than 33% of the employed labour force has completed academic-oriented tertiary education (i.e. at ISCED 5 and 6 levels). They cover all sectors in the economy, including manufacturing and services sectors, and can be defined at two and three-digit levels of the statistical classification of economic activities.

Source: Eurostat

Knowledge-Intensive Services (KIS) Definition: Knowledge-intensive services (KIS) includes the following sectors (NACE Rev.1.1 codes are given in brackets): water transport (61), air transport (62), post and telecommunications (64), financial intermediation, except insurance and pension funding (65), insurance and pension funding, except compulsory social security (66), activities auxiliary to financial intermediation (67), real estate activities (70), renting of machinery and equipment without operator and of personal and household goods (71), computer and related activities (72), research and development (73), other business activities (74), education (80), health and social work (85), recreational, cultural and sporting activities (92). Source: OECD

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Knowledge-Intensive Services exports Definition: Exports of knowledge-intensive services are measured by the sum of credits in EBOPS (Extended Balance of Payments Services Classification) 207, 208, 211, 212, 218, 228, 229, 245, 253, 260, 263, 272, 274, 278, 279, 280, 284. Source: UN / Eurostat Licence and patent revenues from abroad Definition: The export part of international transactions in royalties and license fees. Source: Eurostat Mobility of researchers The concept of mobile researchers There are several difficulties involved in conceptualising researcher's mobility. A first difficulty stems from the very definition of a researcher. As defined by the Frascati Manual in OECD 2002, the standard classification used internationally in surveys, the International Standard Classification of Occupations, does not recognise “researcher” as a profession, only “research and development manager”. Secondly, there are no data on the mobility patterns of individual researchers over time. The data are collected based on the nationality or place of birth of researchers in the population of a particular country. Furthermore, methodology of data collection has changed over time, so it is not possible to present time series and trends on mobility of researchers. For the sub-population of doctorate holders, it may be feasible in the coming years to present time series on mobility based on the results of the “Careers of Doctorate Holders” project.2 For the sub-population of doctoral graduates, time series on mobility may also be available in the coming years, depending on the implementation of the new methodology introduced in 2005 in education statistics.3 Methodology for mobility 'Mobile'/'international' is defined on the basis of the country of citizenship. The data collected on mobile/international students changed in the Unesco-OECD-Eurostat data collection in 2005. Two new concepts were introduced to better capture student mobility across countries: country of permanent residence and country of prior education. This change has been motivated by the fact that the data collected before the 2005 UOE data collection are not appropriate for measuring all mobile/international students. Observations based on the citizenship criterion are affected by the differences in legislation governing the acquisition of nationality. Thus, certain foreign students may have lived in their host countries for many years and completed some or all of their prior education in the same country and, therefore, they may have never been ‘mobile’. Citizenship alone is not a variable sufficient to measure incoming and outgoing students. However, the changes have not been fully implemented yet and are still in the pilot phase, not available for full exploitation. 2 This project is funded by OECD, the UNESCO Institute for Statistics and EUROSTAT and initiated in 2004: the Careers of Doctorate Holders (CDH) project. It aims at developing a regular and internationally comparable production system of indicators on the careers and mobility of doctorate holders, building on surveys currently existing in some countries and on other data sources. The first results are available, but only for a limited number of countries. (see Auriol L. (2007), “Labour market characteristics and international mobility of doctorate holders: results for seven countries”, OECD STI Working Paper 2007/2). 3 A pilot phase is initiated by OECD and EUROSTAT, running for the 2008 exercise as well.

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Different facets of mobility A first facet of mobility is geographical. Researchers could move within national borders, cross-border or transnationally. Mobility could even be virtual, based on ICT-based tools. The analysis in this report focuses on transnational (geographical) mobility of researchers in Europe. The transnational geographical mobility may or may not form part of a scientific career (including aspects such as the rewards an institution or a national research system attach to mobility for career prospects). Related differentiations are: - the length of the mobility period (6 months, one year, a whole careers) - the positions occupied by the mobile researcher, and - the possible accumulation of mobility periods at different stages in a scientific career. However, the concept ‘Mobility of researchers’ refers as well to other facets: - Mobility of researchers between public and private sectors, and the reverse - Mobility of researchers between one discipline and another - Demographic and career aspects on mobility of researchers (including retirement) Patent Cooperation Treaty (PCT) Patents Definitions: The Patent Cooperation Treaty (PCT) is an international treaty, administered by the World Intellectual Property Organization (WIPO), signed by 133 Paris Convention countries. The PCT makes it possible to seek patent protection for an invention simultaneously in each of a large number of countries by filing a single “international” patent application instead of filing several separate national or regional applications. Indicators based on PCT applications are relatively free from the "home advantage" bias (proportionate to their inventive activity, domestic applicants tend to file more patents in their home country than non-resident applicants). The granting of patents remains under the control of the national or regional patent offices. The PCT patents considered are ‘PCT patents, at international phase, designating the European Patent Office’. The country of origin is defined as the country of the inventor.

The timeliness (at the international phase of the PCT procedure) is much better than for Triadic patents. However, the relatively low cost of a patent application on an international basis makes the PCT procedure not very selective. Many PCT applications will cover inventions whose value is known a posteriori to be low, while few of them will cover inventions of very high value. A high share of patent applications invented in a given country might turn out to be of limited impact on its economy if they all turn out to be of little or no use. Societal challenges patents comprise climate change mitigation patents and health technology patents. Climate change mitigation patents comprise patents for renewable energy, electric and hybrid vehicles and energy efficiency in buildings and lighting. Health technology patents comprise patents for medical technologies and pharmaceuticals. Source: OECD

R&D expenditure Gross Domestic Expenditure on R&D Definition: Gross domestic expenditure on R&D (GERD) is defined according to the OECD Frascati Manual definition. GERD can be broken down by four sectors of performance:

(i) Business Enterprise Expenditure on R&D (BERD);

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(ii) Government Intramural Expenditure on R&D (GOVERD); (iii) Higher Education Expenditure on R&D (HERD); (iv) Private non-Profit expenditure on R&D (PNPRD). GERD can also be broken down by four sources of funding: (i) Business Enterprise; (ii) Government; (iii) Other national sources; (iv) Abroad.

Sources: Eurostat, OECD Public expenditure on R&D Definition: For the purposes of this publication, Public expenditure on R&D is defined as Government Intramural Expenditure on R&D (GOVERD) plus Higher Education Expenditure on R&D (HERD). Sources: Eurostat, OECD R&D Intensity Definition: Gross Domestic Expenditure on R&D (GERD) as % of Gross Domestic Product (GDP) Sources: Eurostat, OECD BERD Intensity Definition: Business Enterprise Expenditure on R&D (BERD) as % of Gross Domestic Product (GDP) Sources: Eurostat, OECD Public sector R&D Intensity Definition: Public expenditure on R&D (GOVERD plus HERD) as % of GDP. Sources: Eurostat, OECD Government budget for R&D Definition: The government budget for R&D is defined as government budget appropriations or outlays for R&D (GBAORD), according to the OECD Frascati Manual definition. The data are based on information obtained from central government statistics and are broken down by socio-economic objectives in accordance with the nomenclature for the analysis and comparison of scientific programmes and budgets (NABS). Source: Eurostat Research Infrastructures The term “Research Infrastructures” (RIs) may be employed in a number of contexts with different scopes. In its broadest sense, research infrastructures refer to all facilities, laboratories and resources used by research personnel for research activities. This broad definition of RIs would match the “capital” category of the Frascati manual, which includes “land and buildings”, “equipment and research instruments” and “computer software”. However, the term “RI” usually refers to large-scale facilities or resources, which may be single-sited, distributed or virtual, but which provide unique access and services to research communities in both academic and industry domains. These facilities typically have

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investment, operating or maintenance costs that are relatively high in relation to research costs in their particular field. Pan-European Research Infrastructures

1. Research Infrastructures must provide resources, facilities and services that are essential to the scientific or technological research community.

2. Research Infrastructures should typically have investment, operating or maintenance costs that are relatively high in relation to research costs in their particular field.

3. Research Infrastructures should be open to external researchers, i.e. provide access to conduct research, irrespective of the location of the RI (e.g. through Transnational Access contracts or any other bilateral and/or multilateral agreements).

4. Research Infrastructures should have a clear European dimension and added value, i.e. they should:

5. Research Infrastructures must provide resources, facilities and services that are essential to the scientific or technological research community.

6. Research Infrastructures should typically have investment, operating or maintenance costs that are relatively high in relation to research costs in their particular field.

7. Research Infrastructures should be open to external researchers, i.e. provide access to conduct research, irrespective of the location of the RI (e.g. through Transnational Access contracts or any other bilateral and/or multilateral agreements).

8. Research Infrastructures should have a clear European dimension and added value, i.e. they should:

o be considered rare for the specific discipline(s) and be of pan-European interest, relevance and top-level in their respective field and so be considered as "European key infrastructures";

o allow the performance and development of science at the cutting edge (i.e. by providing the best tools, continuously upgrading them, improvements to services and interface with users);

o be working in international networks/collaborations;

o be recognised at international level (even if a national RI) as organisations facilitating excellence in research (including comparisons to Japan and the US);

o be attractive to and capable of receiving external users, by providing adequate scientific, technical and logistic support.

Examples of Research Infrastructures

Telescopes, synchrotrons and accelerators, satellite and aircraft observation facilities, networks of computing facilities, coastal observatories, research vessels, collections, special habitats, libraries, databases, biological archives, clean rooms, integrated arrays of small research installations, high-capacity/high speed communication networks, data infrastructures.

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Scientific Publications Definition: Publications are research articles, reviews, notes and letters published in referenced journals which are included in the Scopus database of Elsevier. A full counting method was used at the country level. However, for the EU aggregate, double counts of multiple occurrences of EU Member States in the same record were excluded. Source: Scopus (Elsevier); treatments and calculations: Science Metrix

Average of Relative Citations (ARC)

The ARC is an indicator of the scientific impact of papers produced by a given entity (e.g., the world, a country, a NUTS2 region, an institution) relative to the world average (i.e., the expected number of citations). The number of citations received by each publication is counted for the year in which it was published and for the three subsequent years. For papers published in 2000, for example, citations received in 2000, 2001, 2002 and 2003 are counted.

To account for different citation patterns across fields and subfields of science (e.g., there are more citations in biomedical research than in mathematics), each publication's citation count is divided by the average citation count of all publications of the corresponding document type (i.e., a review would be compared to other reviews, whereas an article would be compared to other articles) that were published the same year in the same subfield to obtain a Relative Citation count (RC). The ARC of a given entity is the average of the RCs of the papers belonging to it. An ARC value above 1 means that a given entity is cited more frequently than the world average, while a value below 1 means the reverse. The ARC is computed for the 2000-2006 period only since publications in 2007, 2008 and 2009 have incomplete citation windows.

Methodology of co-publication analysis The methodology used for the co-publication analysis involved three types of analysis: a) Single country publications cover co-publications that involve domestic partners only; this is the sum of all papers written by one or more authors from a given country (and non-nationals resident in that country). Although the literature usually distinguishes between domestic single publications (including one or more authors belonging to the same institution) and domestic co-publications (i.e. authors within the same country but from different main organisations), for the aim of the current analysis the sum of the two categories have been used under the heading of “single country publications”. b) EU transnational co-publications refer to international co-publications which involve at least one author from an EU country. This category includes both co-publications by authors from at least two different EU Member States (as defined by research papers containing at least two authors' addresses in different countries) and co-publications between one or several authors from the EU together with at least one author from a country outside the EU. c) Extra-EU co-publications is a sub-category of the broader EU transnational co-publications. It refers exclusively to international co-publications involving at least one EU author and at least one non-EU author, as defined by the authors' addresses in different countries. An important methodological issue is the way in which a co-publication is quantified. The full counting method has been used in this report, meaning that a single international co-published

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paper is assigned to more than one country of scientific origin. If, for example, the authors' addresses signal three different countries in the EU, the publication is counted three times – once for each country mentioned. Therefore, in a matrix of co-publications between countries, the number of publications mentioned is not a completely accurate indicator of the number of publications being co-authored, but rather how often a country or region is involved in co-publications. Public-Private co-publications Definition: Number of public-private co-authored research publications. The private sector excludes the private medical and health sector. Source: CWTS / Thomson Reuters Scientific Specialisation Definition: The relative scientific specialisation index (RCA) is calculated for 28 disciplines on the basis of publications from 2000-2002 and 2004-2006. The fields ‘multidisciplinary’ and ‘social Sciences’' have been excluded. The formula used is the hyperbolic tangent function for the ratio of the share of a domain or discipline in a country compared to the share of the domain in the total for the world: RCAki = 100 x tanh ln {(Aki/∑iAki)/(∑kAki/∑kiAki)}, with Aki indicating the number of publications of country k in the field i, whereby the field is defined by 28 scientific disciplines used in the classifications.

LN centres the data on zero and the hyperbolic tangent multiplied by 100 limits the RCA values to a range of +100 to -100. Scores below -20 are considered a significant under-specialisation in a given scientific field, scores between -20 and +20 are around field average and mean no significant (under-)specialisation, and scores above +20 mean a significant specialisation in a given field. The RCA indicator allows the assessment of the relative position of a field i in a country beyond any size effects. Neither the size of the field nor the size of the country has an impact on the outcome of this indicator. Therefore, it is possible to directly compare countries and fields. Source: ISI, Science Citation Index; treatments and calculations: Fraunhofer ISI

Structural Funds Definition: Structural Funds are funds intended to facilitate structural adjustment of specific sectors, regions, or combinations of both, in the European Union. Structural Funds for RTDI include data from sectors involving research and development, technological innovation, entrepreneurship, innovative ICT and human capital. Source: DG REGIO.

Technology Categories Definition: The four manufacturing industry technology categories are defined as follows (NACE Rev 1.1 codes are given in brackets):

(1) High-tech: office machinery and computers (30), radio, television and communication equipment and apparatus (32), medical, precision and optical instruments, watches and clocks (33), aircraft and spacecraft (35.3), pharmaceuticals, medicinal chemicals and botanical products (24.4).

(2) Medium-high-tech: machinery and equipment (29), electrical machinery and apparatus (31), motor vehicles, trailers and semi-trailers (34), other transport equipment (35) excluding

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building and repairing of ships and boats (35.1) and excluding aircraft and spacecraft (35.3), chemicals and chemical products (24) excluding pharmaceuticals, medicinal chemicals and botanical products (24.4).

(3) Medium-low-tech: coke, refined petroleum products and nuclear fuel (23), rubber and plastic products (25), non-metallic mineral products (26), basic metals (27), fabricated metal products (28), building and repairing of ships and boats (35.1).

(4) Low-tech: food products and beverages (15), tobacco products (16), textiles (17), wearing apparel; dressing and dyeing of fur (18), tanning and dressing of leather, manufacture of luggage, handbags, saddlery and harness (19), wood and products of wood and cork, except furniture (20), pulp, paper and paper products (21), publishing, printing and reproduction of recorded media (22), furniture and other manufacturing (36), recycling (37).

Technological Specialisation Definition: The relative technological specialisation index (or RCA) is calculated for 19 technology domains on the basis of PCT patent applications (at the international phase, designating the EPO). The data were classified by earliest priority date and country of residence of the inventor. The formula used is the hyperbolic tangent function for the ratio of the share of a domain in a country compared to the share of the domain in the total for the world: RCAki = 100 x tanh ln {(Aki/∑iAki)/(∑kAki/∑kiAki)}, with Aki indicating the number of PCT patent applications (at international phase, designating the EPO) of country k in the field i.LN centres the data on zero and the hyperbolic tangent multiplied by 100 limits the RCA values to a range of +100 to -100. Scores below -20 are considered a significant under-specialisation in a given scientific domain, scores between -20 and +20 are around domain average and mean no significant (under-)specialisation, and scores above +20 mean a significant specialisation in a given domain. The RCA indicator allows the assessment of the relative position of a field i in a country beyond any size effects. Neither the size of the domain nor the size of the country has an impact on the outcome of this indicator. Therefore, it is possible to directly compare countries and domain. Source: JRC-IPTS, based on EPO and WIPO data Trans-nationally coordinated research – national public funding National public funding to trans-nationally coordinated research is defined as the total budget funded by the government (state, federal, provincial), as measured by GBAORD (Government Budget Appropriations or Outlays for R&D), which is directed to the following three categories of R&D performers and programmes:

1. trans-national public R&D performers located in Europe; 2. Europe-wide trans-national public R&D programmes; 3. bilateral or multilateral public R&D programmes established between Member State

governments (and with candidate countries and EFTA countries). 1. Trans-national public R&D performers include:

• the European Organisation for Nuclear Research (CERN); • the European Molecular Biology Laboratory (EMBL); • the European Southern Observatory (ESO); • the European Synchrotron Radiation Facility (ESRF); • the Institut Laue-Langevin (ILL);

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• the European Commission’s Joint Research Centre (JRC). 2. Europe-wide trans-national public R&D programmes include: EUREKA, COST, ESA, ERA-NETs, ERA-NET+, EFDA, EUROCORES, Article 185 initiatives (Europe-developing countries clinical trials platform, Eurostars and Ambient assisted living for the elderly), Joint technology initiatives (public funding part: ENIAC, ARTEMIS). National contributions to FP funding which come from the overall national contributions to the total EU budget are not included. 3. Bilateral or multilateral public R&D programmes include for instance programmes under the D-A-CH agreement or Nordforsk. The main source used by most of the countries for the compilation of these data is Government Budget Appropriations or Outlays for Research and Development (GBAORD), in many cases supplemented with additional information from the national funding agencies/ministries. In some countries R&D budget text analysis is combined with data collected through R & D surveys.

GBAORD covers not only government-financed R&D performed in government establishments but also government-financed R&D in the other three national sectors (business enterprise, private non-profit, higher education) as well as abroad (including international organisations). Data collection on ‘national public funding to trans-nationally coordinated research’ was conducted for the first time in 2010 by National Statistical Institutes under the guidance of Eurostat and DG Research and Innovation. As it is the first data collection of this kind, the figures have to be considered with the greatest caution and will be subject to revision in the coming years. 18 European countries provided all the data on this indicator, including 15 EU Member States.