Research and innovation statistics at regional level

Data extracted in March 2016. Most recent data: Further Eurostat information, Main tables and Database. Planned article update: September 2017.

Maps can be explored interactively using Eurostat’s Statistical Atlas (see user manual).

Map 1: R & D intensity — gross domestic expenditure on R & D (GERD) relative to gross domestic product (GDP), by NUTS 2 regions, 2013 (1)
(%)
Source: Eurostat (rd_e_gerdreg)
Figure 1: Share of R & D researchers in the number of persons employed, by NUTS 2 regions, 2013 (1)
(%)
Source: Eurostat (rd_p_persreg)
Map 2: Share of human resources in science and technology (HRST) within the total population, by NUTS 2 regions, 2014 (1)
(%)
Source: Eurostat (hrst_st_rcat) and (hrst_st_ncat)
Figure 2: Share within the economically active population of human resources in science and technology core (HRSTC), by NUTS 2 regions, 2014 (1)
(%)
Source: Eurostat (hrst_st_rcat) and (hrst_st_ncat)
Figure 3: Gender gap for the share within the economically active population of human resources in science and technology core (HRSTC), by NUTS 1 regions, 2014 (1)
(percentage points difference, share for men - share for women)
Source: Eurostat (hrst_st_rsex) and (hrst_st_ncat)
Map 3: Share within total employment of employment in high-tech sectors, by NUTS 2 regions, 2014 (1)
(%)
Source: Eurostat (htec_emp_reg2) and (htec_emp_nat2)
Map 4: Patent applications to the EPO relative to the population size, by NUTS 3 regions, 2011 (1)
(number per million inhabitants)
Source: Eurostat (pat_ep_rtot) and (pat_ep_ntot)
Table 1: Top 10 regions for EU trademarks and Community designs, by NUTS 3 regions, 2014
Source: Eurostat (ipr_ta_reg), (ipr_tr_reg), (ipr_da_reg), (ipr_dfa_reg) and (demo_r_pjanaggr3)

This article is part of a set of statistical articles based on the Eurostat regional yearbook publication. It presents statistical information analysing regional developments for a range of research and innovation-related indicators within the European Union (EU), including the following issues: research and development (R & D) expenditure, the number of R & D researchers, human resources in science and technology (HRST), employment in high technology sectors and intellectual property rights.

Main statistical findings

Gross domestic expenditure on R & D (GERD) includes expenditure on R & D by business enterprises, higher education institutions, as well as government and private non-profit organisations. It was estimated to be EUR 283.9 billion across the EU-28 in 2014; this equated to an average of EUR 560 of R & D expenditure per inhabitant.

Europe 2020: research and development intensity

Both the Europe 2020 strategy and its predecessor the Lisbon agenda (launched in 2000) set similar targets in relation to R & D expenditure, namely that expenditure on R & D should be equivalent to at least 3.00 % of the EU’s gross domestic product (GDP). This overall target is divided into a range of national targets, reflecting the position of each EU Member State and commitments agreed between the European Commission and national administrations through a series of reform programmes. These national targets for R & D expenditure vary considerably between EU Member States and ranged from 0.50 % of GDP in Cyprus to 3.76 % of GDP in Austria and 4.00 % of GDP in the traditionally R & D-intensive Member States of Finland and Sweden; there is no national target for the United Kingdom.

From a level of 1.79 % of GDP in 2000 (which is the start of the series for the EU-28) there was little or no change in the EU’s R & D intensity during the period 2000–07. In 2008, there was a modest increase, as R & D expenditure relative to GDP rose to 1.85 % and this was followed by a further increase to 1.94 % in 2009 (resulting from the level of R & D expenditure falling at a slower pace than GDP as the full impact of the financial and economic crisis was felt). There was a rebound in economic growth and R & D expenditure in the following years, with further modest gains in the EU-28’s R & D intensity, which reached 2.03 % in 2013, a level that was repeated in 2014.

High R & D intensity in many Nordic and German regions

The nature of R & D is such that there are clusters of activity, in other words, specific geographical areas where R & D activity appears to be concentrated. These regions are often developed around academic institutions or specific high-technology industrial activities and knowledge-based services, which foster a favourable environment, thereby attracting new start-ups and highly qualified personnel such that the competitive advantage of these regions is further intensified.

SPOTLIGHT ON THE REGIONS

Prov. Brabant Wallon, Belgium

Louvain-la-Neuve Halles.JPG

In 2013, R & D intensity in the EU-28 averaged 2.03 %, considerably lower than its Europe 2020 target of 3.00 %. Among NUTS level 2 regions there was a wide diversity in R & D intensities, which tends to reflect clusters of research activity. For example, the NUTS level 2 region with the highest R & D intensity (11.36 %) was the Prov. Brabant Wallon (Belgium), which could be contrasted with two neighbouring Belgian regions — the Prov. Namur and the Prov. Luxembourg — where R & D intensities were below 1.00 %.

©: Jonathan Nélis

Map 1 presents the regional distribution of R & D expenditure relative to GDP for NUTS level 2 regions for 2013. It shows the most concentrated areas of research activity. Just over 1 in 10 (11.4 %) of the 264 NUTS level 2 regions in the EU for which data are available reported R & D intensity that had reached the Europe 2020 target of at least 3.00 % (as shown by the darkest shade of orange in Map 1); together these regions accounted for more than one third (34.9 %) of the EU-28’s total R & D expenditure in 2013. Note that the Europe 2020 targets have not been set at a regional level and that each EU Member State may choose how to reach their national target (either by general measures across the territory or by encouraging specific regional concentrations/clusters of research activity).

The Province Brabant Wallon had the highest R & D intensity in the EU

There were three NUTS level 2 regions in the EU where the level of R & D intensity was particularly pronounced. Two of these were in Germany, Stuttgart and Braunschweig, where R & D expenditure relative to GDP rose to 6.00 % and 7.33 % respectively in 2013. However, R & D intensity peaked in the Belgian region of the Province Brabant Wallon, at 11.36 %; as such, its research intensity was almost six times as high as the EU-28 average.

Research activity was otherwise often focussed on capital city regions, for example, the Nordic capitals of Hovedstaden, Helsinki-Uusimaa and Stockholm, or the German and Austrian capitals of Berlin and Wien. There were also a number of other regions with R & D intensity of at least 3.00 %, many of which have a tradition of research excellence, including, for example: the Provincie Vlaams-Brabant in Belgium; Tübingen and Oberbayern in Germany; the Midi-Pyrénées in France; or East Anglia in the United Kingdom.

Most southern and eastern regions had relatively low levels of R & D intensity

Outside of these clusters, R & D expenditure relative to GDP was generally modest in the remaining western and northern regions of the EU and low in most southern and eastern regions of the EU. Indeed, the Spanish region of País Vasco (2.12 %) and the Italian region of Piemonte (2.03 %) were the only southern EU regions to report R & D intensity above 2.00 % in 2013, while the only eastern regions of the EU to record intensities above 2.00 % were: the Czech regions of Jihovýchod (2.84 %), Praha (2.59 %) and Střední Čechy (2.15 %), as well as Slovenia (2.60 %, no regional data available).

Researchers

Researchers are directly employed within R & D activities and are defined as ‘professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems and in the management of the projects concerned’.

There were an estimated 2.71 million researchers active across the EU-28 in 2013. Their number has grown at a steady pace in recent years, rising from 1.80 million in 2003. An alternative unit of measure for labour input adjusts the number of researchers to take account of different working hours and working patterns. Based on this measure, there were 1.73 million full-time equivalent (FTE) researchers in the EU-28 in 2013, a figure which rose to 1.76 million in 2014.

The distribution of researchers across the EU was particularly clustered in capital city regions …

The distribution of researchers was relatively concentrated in a few clusters, principally in those regions where R & D intensity was high. The main difference is that researchers tended to be somewhat higher in regions characterised as having higher education establishments and research institutes (often capital city regions). Furthermore, there was a relatively high share of researchers among persons employed in a number of southern regions, principally located across Spain (for example, País Vasco) and Greece (for example, Kriti).

Like R & D intensity, the share of researchers among persons employed was skewed (see Figure 1), as just under one third (31.1 %) of the regions for which data are available for 2013 reported a share of researchers that was above the EU-28 value of 0.8 %, while the median share across all NUTS level 2 regions was 0.6 %.

In all multi-regional EU Member States the share of researchers among persons employed in the capital city region was above the national share. In fact, in 14 of the 21 multi-regional Member States for which data are available, the share in the capital city region was higher than in any other region, the exceptions being Belgium, Germany, Greece, Spain, Italy, the Netherlands and the United Kingdom (data for London is only available at NUTS level 1). In some Member States (for example, Denmark and Finland), the capital city region was the only region with a share of researchers in the number of persons employed that was above the national share.

Looking at all EU regions, only seven reported that researchers made-up at least 2.0 % of their total number of persons employed in 2013, the highest share being 2.8 % in the Danish capital city region of Hovedstaden. By contrast, 112 regions reported shares that were below 0.5 %.

Human resources in science and technology

An alternative measure for highly qualified personnel is provided by statistics relating to human resources in science and technology (HRST), defined as those persons who have completed a tertiary level of education and/or are employed in a science and technology occupation. A more restricted definition is applied for those persons who meet both of these criteria, referred to as core human resources in science and technology (HRSTC).

Human resources in science and technology: just over 30 % of the EU’s working-age population

Human resources in science and technology contributed 120 million persons to the EU-28 workforce in 2014, of which 47 million were categorised as core HRST. In 2008, HRST accounted for slightly more than one quarter (27.3 %) of the EU-28’s population aged 15–74 (hereafter referred to as the working-age population); this share rose in successive years to reach 31.8 % by 2014.

Among the EU Member States, HRST accounted for 16.6 % of the working-age population in Romania, the only Member State in 2014 to record a share that was less than one fifth. At the other end of the range, upwards of 40 % of the working-age population in Finland, Sweden and Luxembourg were classified as HRST.

SPOTLIGHT ON THE REGIONS

Stockholm, Sweden

Main building of the Royal Swedish Academy of Sciences.jpg

Stockholm, the Swedish capital city region, recorded the highest regional share of human resources in science and technology within its total population (52.8 %). It was one of only four regions to report a majority of its population employed in science and technology; the other three included the neighbouring Nordic capital region of Helsinki-Uusimaa (Finland) and two regions from the south of the United Kingdom (London (NUTS level 1) and Berkshire, Buckinghamshire and Oxfordshire).

©: Hackspett

Map 2 shows the regional distribution of HRST for NUTS level 2 regions, with the darkest shade of orange highlighting those regions where the share of HRST in the working-age population was at least 40 %. Approximately 12 % of the 266 regions for which data are available in 2014 met this criterion, with HRST accounting for at least two fifths of their working-age population. Many of the regions with high shares of HRST were also characterised as having a high degree of R & D intensity (see above). Indeed, the main clusters of HRST were located in the United Kingdom (11 regions), the Nordic Member States, the Benelux Member States and Germany. The proportion of the working-age population classified as HRST also rose to over 40 % in two regions from Spain, and the capital city regions of the Czech Republic, France, Austria and Slovakia.

At least half of the working-age population in Stockholm, Helsinki-Uusimaa, London and Berkshire, Buckinghamshire and Oxfordshire was classified as HRST

There were three capital city regions where at least half of the working-age population was classified as HRST in 2014 —Stockholm (52.8 %), Helsinki-Uusimaa (51.7 %) and London (51.1 %, NUTS level 1) — and one other region, Berkshire, Buckinghamshire and Oxfordshire to the west of London.

There were also relatively high shares of HRST in the working-age population in several other regions close to capital cities — for example: the Province Brabant Wallon and the Provincie Vlaams-Brabant around the Belgian capital; Utrecht near to Amsterdam in the Netherlands; and several other regions around London (Bedfordshire and Hertfordshire; Surrey, East and West Sussex). High shares of HRST in regions away from capital city regions were observed in Oberbayern and Hamburg in Germany, País Vasco in Spain, Sydsverige and Västsverige in Sweden, and several British regions in south-western and northern England and in Scotland.

For 28 NUTS level 2 regions HRST accounted for less than one in five of their working-age population in 2014 (as shown by the lightest shade of orange in Map 2). These regions were all located in southern and eastern parts of the EU, with eight from Greece, seven from Romania, six from southern Italy, four from Portugal, and a single region each from Bulgaria, Spain and Hungary.

The share of core HRST in the active working-age population was approximately twice as high as the EU-28 average in Luxembourg

Figure 2 shows the distribution of core HRST as a share of the economically active population aged 15–74 in 2014, ranked by national averages. Core HRST accounted for 16.3 % of the EU-28’s economically active population in 2008 and saw its share rise each year through to 2014, when it stood at 19.6 %.

Across all of the NUTS level 2 regions of the EU, the highest share of core HRST in the economically active population aged 15–74 in 2014 was 40.8 % in Luxembourg (a single region at this level of analysis).

Capital city regions often recorded the highest shares of core HRST, while a majority of the other regions saw their shares of core HRST fall below the national average; this skewed distribution is clearly apparent in Figure 2. Among those EU Member States with more than two NUTS level 2 regions, the capital city regions of the Nordic Member States, Austria, Hungary, Bulgaria, Portugal and Slovakia were noteworthy insofar as they were the only regions in each of these Member States to record a share of core HRST that was above the national average. Belgium, France and the Netherlands displayed an atypical pattern among the multi-regional EU Member States, insofar as their capital city regions did not register the highest share of core HRST, but all had values above their national averages. Turning to the non-member countries shown in Figure 2, Switzerland was a greater exception, as not only was the share of core HRST in the capital city region (Espace Mitteland) not the highest among the Swiss regions, it was also below the national average.

The share of core HRST in the active working-age population was higher among women than among men, except in Germany

In the EU-28 as a whole, the share of core HRST in the economically active population was 5.0 percentage points higher for women than for men in 2014, as the share for women was 22.3 % and that for men 17.3 %. Among the EU Member States, Germany was the only one where the share of core HRST in the economically active population was higher for men than for women. By contrast, the female share was more than 10.0 percentage points higher than the male share in all three Baltic Member States, Bulgaria, Poland, Sweden and Slovenia, as it also was in Norway and Iceland. These national averages are reflected in the regional data presented in Figure 3 which shows the NUTS level 1 regions where the gender gap for the share of core HRST in the economically active population was greatest. In fact, there were only 10 regions (in the EU, Iceland, Norway, Switzerland, the former Yugoslav Republic of Macedonia and Turkey) where the share was higher for men than for women, and the top eight of these were in Germany, the other two being in Austria and Switzerland (for which only national data are available). Every other region recorded a higher share for women, with a particularly large gender gap in several Polish regions, one region each in Bulgaria and Sweden, and especially the three Baltic Member States (each one region at this level of detail).

Employment in high-technology sectors

There were approximately 8.5 million persons employed across the EU-28 within high-tech sectors in 2014; between 2009 and 2014 the total number of persons working in high-tech sectors increased by 389 thousand. In relative terms, those working in high-tech sectors accounted for 3.7 % of the total number of persons employed in the EU-28 in 2009. There was a modest increase in their share which climbed to 3.9 % in 2012 and remained at the same level in 2013 and 2014.

Defining high-tech sectors

High-tech sectors include high-tech manufacturing industries and knowledge-intensive services, which are defined according to technological intensity and based on the activity classification NACE. Note that the statistics on employment in high-tech sectors cover all persons (including support staff) who work in these enterprises, and as such will overstate the number of highly-qualified staff.

The distinction between manufacturing and services is made due to the existence of two different methodologies. While R & D intensities are used to distinguish between high, medium-high, medium-low and low-technology manufacturing industries, for services the proportion of the workforce that has completed a tertiary education is used to distinguish between knowledge-intensive services and less knowledge-intensive services.

High-technology manufacturing covers the manufacture of: basic pharmaceutical products and pharmaceutical preparations; computer, electronic and optical products; and air and spacecraft and related machinery.

High-tech knowledge-intensive services include: motion picture, video and television programme production, sound recording and music publishing activities; programming and broadcasting; telecommunications; computer programming, consultancy and related activities; information service activities; and research and development services.

More information on the aggregation of data for high-tech industries and knowledge-intensive services is provided on Eurostat’s website.

Across the EU-28, those employed in high-tech sectors — both high-tech manufacturing and high-tech knowledge-intensive services — accounted for approximately 3.9 % of persons aged 15–74 in employment. In 2014, the highest share of employment in high-tech sectors among the EU Member States was recorded in Ireland, at 7.3 %, followed by Malta at 6.2 % and Finland at 5.9 %.

The share of employment in high-tech sectors was at least 4.5 % in 59 of the 252 NUTS level 2 regions for which data are available (as indicated by the darkest shade of orange in Map 3), while 20 regions reported a share of employment in high-tech sectors that was less than 1.5 % (as indicated by the lightest shade).

People working in high-tech sectors accounted for at least 7.5 % of total employment in 11 regions in 11 different Member States

In 2014, the highest share of people working in high-tech sectors was 11.0 %, as recorded in Berkshire, Buckinghamshire and Oxfordshire, a region with a high density of enterprises in information and communications technology and life sciences located in the infrastructure-rich area to the west of London. Nearly all of the 10 other NUTS level 2 regions with shares in excess of 7.5 % were capital city regions, from Ireland and Austria in the west, Denmark, Finland and Sweden in the north, the Czech Republic, Hungary and Slovakia in the east, and Spain in the south. The one exception was Prov. Brabant Wallon to the south of the Belgian capital. Apart from Belgium and the United Kingdom, the only other EU Member States where the capital city region did not record the highest share of people working in high-tech sectors were Germany and the Netherlands, and this was also the case in Switzerland.

Germany and the United Kingdom recorded a relatively high number of regions where the employment share of high-tech sectors was above 4.5 % (the darkest shade in Map 3), with 12 such regions in Germany and 10 in the United Kingdom. In Belgium, four regions in and around the capital city region recorded shares of employment in high-tech sectors that were above 4.5 %, as did a cluster of three regions in and around the Czech capital city region.

Intellectual property rights

The term intellectual property rights is used to cover the granting of different kinds of protection through the issuing of patents, copyrights and trademarks. The protection of intellectual property allows the holder to exercise a monopoly on the use of the item in question for a set period, as imitation and duplication are restricted. By doing so, enterprises may be encouraged to invest more in research and creative activity.

The number of patent applications from the EU-28 to the European Patent Office (EPO) rose at a relatively fast pace through to 1999, when an average of more than 100 applications per million inhabitants was passed for the first time. Thereafter, modest increases followed up until 2006 when a relative peak of 117 applications per million inhabitants was registered. From this relative high, the number of EPO patent applications per million inhabitants in the EU-28 fell slowly to 112 applications per million inhabitants in 2010, and stabilised at 113 applications per million inhabitants between 2011 and 2013 during which time the total number of applications was just over 57 thousand.

Defining patents

Patent counts can provide a measure of invention and innovation. A patent is an intellectual property right that gives its owner the exclusive right to use his/her invention in a particular technical field for a limited number of years.

A patent application should be based on a new solution to a technical problem which satisfies three criteria: novelty; inventiveness; and industrial applicability. A patent may be granted to an enterprise, a public body, or an individual. Patents remain valid for a given country or area for a limited period of time.

Regional statistics for patent applications to the EPO build on information from the addresses of inventors, which is not always the place (region) of invention as inventors do not necessarily live in the same region as the one in which they work; the impact of this discrepancy is likely to be higher when smaller geographical units are being analysed.

Care should be taken interpreting this data as not all inventions are patented and patent propensities vary across activities and enterprises. Furthermore, patented inventions vary in technical and economic value.

The average number of patent applications per million inhabitants in the EU-28 stood at 113.2 in 2011, the latest year for which complete regional information is available. As with the other research and innovation indicators, patent applications tend to be clustered geographically in a limited number of regions; this is especially true for high-tech patents. Indeed, Map 4 shows that technological activity in the form of patent applications was very much concentrated in the centre of the EU and in particular in southern Germany and in Switzerland.

This relatively high degree of concentration of patent activity is demonstrated by the fact that across the 1 126 NUTS level 3 regions for which recent data are available, around three fifths reported their ratio of patent applications per million inhabitants below the EU-28 ratio, while the median value for all NUTS level 3 regions was 83 patent applications per million inhabitants.

The darkest shade of orange in Map 4 indicates those regions where this ratio reached at least 250 patent applications per million inhabitants. Among these 210 regions, the overwhelming majority (165 of them) were located in Germany. The remainder were mainly from western and northern EU Member States, including: nine French regions, eight Austrian regions, six Swedish regions, five British regions, and four regions each from Belgium, Denmark, the Netherlands and Finland. The one region from a southern Member State was Pordenone within the Friuli-Venezia Giulia region (north-east Italy).

The highest number of patent applications per million inhabitants in 2011 was 2 467 in Erlangen, Kreisfreie Stadt, while the neighbouring region of Erlangen-Höchstadt had the third highest ratio (1 471); Erlangen is home to a number of research institutes and a university, with much of its research activity based on optics, engineering, technology and computer science. These two regions were split by Zuidoost-Noord-Brabant in the Netherlands with 1 924 patent application per million inhabitants. Two other German regions also reported more than 1 000 patent applications per million inhabitants: Heidenheim and Ludwigsburg, both near Stuttgart in southern Germany. Among the non-member regions shown in Map 4, the highest ratio was recorded for the Swiss region of Basel-Stadt (873 patent application per million inhabitants).

By contrast, 174 of the NUTS level 3 regions in the EU for which data are available reported that they had less than 10.0 patent application per million inhabitants in 2011 (as shown by the lightest shade of orange in Map 4; note that some of the information relates to earlier reference periods). Most of these regions were located in the Baltic Member States, in eastern parts of the EU, in Greece, in the southern half of Italy or across the Iberian Peninsula, although there were a handful of regions in Germany, France and the United Kingdom too.

The French capital city region of Paris had the highest number of EU trademark and Community design applications

Trademarks can be an essential part of the identity of goods and services, as they help to deliver brand recognition and play a role in marketing and communication. A design is the outward appearance of a product or part of it, resulting from the lines, contours, colours, shape, texture, materials and/or its ornamentation.

Table 1 provides information on the application for and granting of EU trademarks and Community designs. The top 10 regions in 2014 are shown for each of these, with the highest number of applications and registrations for EU trademarks and Community designs made in the French capital city region of the Paris. For each part of Table 1, the top 10 regions accounted for a 13–21 % share of the EU-28 total, with each ranking dominated by some of the most populous regions in the EU, either capital city regions or other regions with large cities. The top 10 list for Community design registrations stands out as it includes Varna (Bulgaria) — the only region from the eastern EU Member States to feature in any of the rankings presented in Table 1.

Data sources and availability

Methodology

The methodology for R & D statistics is laid down in the ‘Frascati manual: proposed standard practice for surveys on research and experimental development’ (OECD, 2002), which is also used by many non-member countries.

The methodology for statistics on human resources in science and technology (HRST) is laid down in the Canberra manual (OECD, 1995), which lists all HRST concepts.

Legal basis

Commission Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology provides the legal requirements and determines the datasets, analysis (breakdowns), frequency and transmission delays to be respected by the EU Member States for these statistics.

Sources

Many of the statistics that are used to analyse research and innovation are derived from other statistical domains within Eurostat and a range of international databases provided by other organisations, including:

Patent applications filed at the EPO are classified by the inventor’s residence and in accordance with the international patents classification of applications (IPC). Patent data are regionalised using procedures linking postcodes and/or place names to NUTS level 1, NUTS level 2 and NUTS level 3 regions. Patent statistics published by Eurostat are almost exclusively based on the EPO worldwide statistical patent database, Patstat.

Data on Community trademarks and designs refer to trademark and design protections throughout the EU. Trademarks have to be represented graphically and must be capable of distinguishing products or services from those belonging to competitors, as defined in Directive 2008/95/EC. A Community design is ‘the appearance of the whole or a part of a product resulting from the features of, in particular, the lines, contours, colours, shape, texture and/or materials of the product itself and/or its ornamentation’, as defined by Council Regulation (EC) No 6/2002 on Community designs.

NUTS

The data presented in this article are based exclusively on the 2013 version of NUTS. For the vast majority of regions there is no difference between the 2010 and 2013 versions of NUTS. Nearly all of the regional data in this article have been converted from NUTS 2010, the exceptions being the data on Community trademark and designs presented in Table 1. The conversion of the other data has generally had the following consequences at NUTS level 1: data for the French départements d’outre-mer and for the Greek regions of Voreia Ellada and Kentriki Ellada are not available. The conversion of the data has had the following consequences at NUTS level 2: data for the French départements d’outre-mer are not available, only national data are available for Slovenia, and data for London are shown at NUTS level 1. The conversion of the data has had the following consequences at NUTS level 3: data for a number of regions are not available and for several regions in Germany, Greece, Poland, Portugal and the United Kingdom data are shown at NUTS level 2.

Context

Innovation in its broadest sense covers new growth opportunities that come from providing new products and services derived from technological breakthroughs, new processes and business models, non-technological innovation and innovation in the services sector, combined with creativity, flair and talent.

Europe has a long tradition of excellence in the fields of R & D and innovation. An innovative society may help businesses to maintain a competitive advantage, develop products with higher added value, stimulate economic activity and thereby safeguard or create jobs. At the same time, research and innovation may contribute to finding solutions to some of society’s main challenges, such as the ageing population, energy security, climate change, disaster risk management, or social inclusion. Indeed, the influence of new research and innovation extends well beyond the economic sphere, as it can lead to solutions that directly impact on the daily lives of the population, for example, ensuring safer food, developing new medicines to fight illness and disease, or alleviating environmental pressures.

Regional research, knowledge and innovative capacity depends on a range of factors — business culture, workforce skills, education and training institutions, innovation support services, technology transfer mechanisms, regional infrastructure, the mobility of researchers, sources of finance and creative potential. Education, training and lifelong learning are considered vital to developing a region’s capacity to innovate, with universities across the EU increasingly implicated in the commercialisation of research, collaboration with regional businesses.

Europe 2020

The Europe 2020 strategy is the EU’s growth strategy to become a ‘smart, sustainable and inclusive economy’. It is composed of five headline targets, one of which covers research expenditure, namely, that R & D expenditure should be equivalent to 3.00 % or more of the EU’s GDP by 2020.

Innovation union — a flagship Europe 2020 initiative

In 2010, the European Commission adopted a communication launching a flagship initiative titled ‘Innovation union’ (COM(2010) 546 final); this sets out a strategic approach to a range of challenges like climate change, energy and food security, health and an ageing population. It is hoped that the promotion of innovation in these areas will lead to innovative ideas being transformed into new economic activities and products, which in turn will generate jobs, green growth and social progress.

The innovation union seeks to use public sector intervention to stimulate the private sector, removing bottlenecks which may prevent ideas from reaching market, such as access to finance, a lack of venture capital, fragmented research systems, the under-use of public procurement for innovation, and speeding-up harmonised standards and technical specifications.

To achieve these goals more than 30 separate actions have been identified, including a range of European innovation partnerships (EIPs), designed to act as a framework to address major societal challenges.

For more information: Innovation union — a Europe 2020 initiative.

The innovation union is supplemented by a Communication from the European Commission on ‘Regional policy contributing to smart growth in Europe 2020’ (COM(2010) 553 final) which explores ways in which regional policy can be used to unlock the growth potential of the EU. The communication calls for the development of smart specialisation strategies across the EU’s regions in order to identify those activities that offer the best chance of strengthening a region’s competitiveness, while encouraging interaction between businesses, research centres and universities on the one hand and local, regional and national administrations on the other.

Under the EU’s flagship innovation union, the European Commission undertakes to create an innovation-friendly environment, with a comprehensive intellectual property rights strategy, as detailed in its 2011 Communication titled ‘A single market for intellectual property rights: boosting creativity and innovation to provide economic growth, high quality jobs and first class products and services in Europe’ (COM(2011) 287 final) which seeks to establish a single market for intellectual property.

The innovation union scoreboard tracks a broad range of innovation indicators, including educational standards, R & D expenditure, patent production and business innovation. The results are used in the annual growth survey, helping EU Member States to determine their strengths and the areas they need to focus more on.

In 2014, the European Commission adopted a Communication on ‘Research and innovation as sources of renewed growth’ (COM(2014) 339 final) which proposes that EU Member States should seek to actively support growth enhancing policies, notably through research and innovation, so as to benefit from the largest internal market in the world, many of the world’s leading innovative companies, and the highly-educated European workforce. Proposals were made to explore how the impact of research and innovation could be maximised, through:

  • improving the quality of strategy development and the policymaking process;
  • improving the quality of programmes, focusing of resources and funding mechanisms;
  • optimising the quality of public institutions performing research and innovation.

Framework programmes

Since their launch in 1984, the EU’s framework programmes for research have played a leading role in multidisciplinary research activities. Regulation (EU) No 1291/2013 of the European Parliament and of the Council established Horizon 2020 — the Framework Programme for research and innovation (2014–20). By coupling research and innovation, it aims to ensure Europe produces world-class science, removes barriers to innovation, bridges the gap between research and the market so technological breakthroughs are transformed into viable products, and makes it easier for the public and private sectors to work together. Horizon 2020 has a budget of almost EUR 80 billion, in addition to the private expenditure that it is expected this funding will attract.

While EU funding seeks to target all regions, the innovation divide across Europe’s regions reflects a pattern whereby the majority of EU regions are low absorbers of framework programme funding and structural funds that are designed to raise their modest levels of research and innovation. Indeed, there appears to be a paradox, whereby those regions characterised by established innovative activity attract the most qualified personnel and new business ventures, thereby maintaining their position as innovative leaders, while those that trail behind fail to catch-up, despite efforts to target funding and policy prescriptions specifically to these regions.

European research area (ERA)

In order to pool talent and achieve a necessary scale, policymakers seek to encourage transnational cooperation within the European research area (ERA). The EU’s research efforts have often been described as being fragmented along national and institutional lines. The ERA was launched at the Lisbon European Council in March 2000 and aims to ensure open and transparent trade in scientific and technical skills, ideas and know-how; it sets out to create a unified research area that is open to the world that promotes the free movement of researchers, knowledge and technology.

In July 2012, the European Commission adopted a Communication titled ‘A reinforced European research area partnership for excellence and growth’ (COM(2012) 392 final), focusing on five key priority areas for reforming the ERA: more effective national research systems; optimal transnational cooperation and competition; an open labour market for researchers; gender equality and gender mainstreaming in research; and optimal circulation and transfer of scientific knowledge.

See also

Further Eurostat information

Data visualisation

Publications

Main tables

Regional science and technology statistics (t_reg_sct)
Human resources in science and technology (HRST) by NUTS 2 regions (tgs00038)
Employment in high-tech sectors by NUTS 2 regions (tgs00039)
Patent applications to the European Patent Office (EPO) by priority year by NUTS 2 regions (tgs00040)
High-tech patent applications to the European Patent Office (EPO) by priority year by NUTS 2 regions (tgs00041)
Total intramural R&D expenditure (GERD) by NUTS 2 regions (tgs00042)
Researchers, all sectors by NUTS 2 regions (tgs00043)
Research and development (t_research)
Statistics on research and development (t_rd)
Total intramural R&D expenditure (GERD) by NUTS 2 regions (tgs00042)
Researchers, all sectors by NUTS 2 regions (tgs00043)
High-tech industry and knowledge-intensive services (t_htec)
Employment in high-tech sectors by NUTS 2 regions (tgs00039)
Human Resources in Science & Technology (t_hrst)
Human resources in science and technology (HRST) by NUTS 2 regions (tgs00038)
Intellectual property rights (t_ipr)
Patent (t_pat)
Patent applications to the European patent office (EPO) by priority year by NUTS 2 regions (tgs00040)
High-tech patent applications to the European patent office (EPO) by priority year by NUTS 2 regions (tgs00041)

Database

Regional science and technology statistics (reg_sct)
R&D expenditure and personnel (reg_rd)
Employment in high technology sectors (reg_htec)
Human resources in science and technology (HRST) (reg_hrst)
Research and development (research)
Statistics on research and development (rd)
R&D expenditure at national and regional level (rd_e)
R&D personnel at national and regional level (rd_p)
High-tech industry and knowledge-intensive services (htec)
Employment in high-tech industry and knowledge-intensive services (HTEC) (htec_emp)
Science and technology in high-tech industry and knowledge-intensive services (HTEC) (htec_sti)
Human Resources in Science & Technology (hrst)
Stocks of HRST at national and regional levels (hrst_st)
Intellectual property rights (ipr)
Patent (pat)
Community trade marks (CTM) (ipr_t)
Community design (CD) (ipr_d)

Dedicated section

Methodology / Metadata

Source data for tables, figures and maps (MS Excel)

Other information

  • Commission Regulation (EC) No 753/2004 of 22 April 2004 implementing Decision 1608/2003/EC as regards statistics on science and technology
  • Report (COM(2011) 184 final) from the Commission to the European Parliament and the Council on the implementation of Decision No 1608/2003/EC of the European Parliament and of the Council on science and technology statistics

External links