Priority Sector Report: Creative and Cultural Industries

Priority Sector Report: Creative and Cultural Industries Dominic Power, Uppsala University Tobias Nielsén, Volante QNB Research March 2010 – deliverable D9-1 Executive summary  In 2006 European creative and cultural industries firms employed a total of 6.5 million persons.  Regions with high concentrations of creative and cultural industries have Europe’s highest prosperity levels.  Large urban areas and capital city regions dominate the creative and cultural industries, but some city regions do better than others. The super clusters London and Paris stand out, followed by Milan and Amsterdam.  The creative and cultural industries are significant generators of intellectual property, in particular copyrights, and the largest creative and cultural industries regions are also among the largest employment centres for copyright-based industries.  Among the regions of Europe which rank among the top 25 either by population or creative and cultural industries employment the following have a disproportionally large creative and cultural sector: Athens, Berlin, Budapest, Denmark, Frankfurt, Helsinki, Ireland, Inner London, Outer London, Maastricht, Madrid, Munich, Nijmegen, Oxford, Rome, Stockholm, and Stuttgart.  As a share of the regional labour market, creative and cultural industries account for the largest shares in Inner London (5.95%), Stockholm (5.87%), Prague (5.81%), and Bratislava (5.01%).  Most of the regions in the top 25 highest cultural and creative growth regions are small and medium sized regions. However, the following regions with labour markets over 1 million people were in the top 25 for annual employment growth: Seville (7.78%), Southampton (7.22%), Valencia (6.25%), Bilbao (6.51%), Galicia (5.45%), Lithuania (5.79%).  The highest annual employment growth rates in the period 2001-2006 are found in Austria (6.2%), Lithuania (5.79%), Estonia (4.02%), Slovakia (3.88%), Latvia (3.87%), and Slovenia (3.76%).  Creative and cultural industries manufacturing and production activities are the most regionally concentrated, and consumer oriented activities such as retail the least regionally concentrated.  Further statistical work is needed to measure the true size of the creative and cultural industries. The data used in this report covers employees but not sole traders (i.e. firms with no employees but one active owner) or freelancers. 2 Introduction The European cultural and creative industries (CCI) represent a significant set of industries. Social, cultural and technological changes have helped fuel our thirst and demand for cultural products, new forms of entertainment, distraction, and inspiration. Driven by these changes entirely new industries have emerged (e.g. computer games, web design), older cultural industries have gone from being the preserve of the elite to mass market global industries (e.g. books, high fashion, designer goods), and traditional consumer industries have tried to redesign and repackage what they have always done to suit consumers’ insatiable desire for culture and creativity. Europe’s creative and cultural industries are global leaders and competitive exporters in a wide range of fields. They are the heart of creating Europe’s culture and identity, and central to promoting Europe’s identity around the world. Moreover they are an aggregate group of industries that in 2006 employed a total of 6,576,558 persons or 2.71% of the European labour market. This report presents regionalised data and trends for these 6.5 million employees in 30 European countries. The report rests upon a methodology that has aimed at caution, minimalism and accuracy 1 above all . It is important to note at the outset then that, the number of people working in Europe’s creative and cultural industries is likely much higher. The data used in this report covers employees but does not include sole traders: i.e. it excludes firms with no employees but one active owner. The cultural and creative industries are fields where many micro-businesses and freelancers are active and it is important to note they may account for a significant number of people actively engaged in the European creative and cultural economy. Taking Sweden as an example, the number of establishments with no employees in Sweden is presently 73,150 out of a total of 88,372 creative and cultural industries establishments: i.e. Sweden 82.7% of establishments are not covered by employment statistics compared to 73.2% in the overall Swedish economy. 1 Creative and cultural industries and prosperity The creation of employment opportunities is crucial to economic and social well-being. There is a strong relationship between the presence of creative and cultural industries and regional prosperity. 2 Figure 1 shows that those regions with above average concentrations of Europe’s creative and cultural industries employees are generally those where economic prosperity is highest. 1 An extensive methodological appendix to this report goes into detail in how we have defined creative and cultural industries and the various measures and data we have used in this report. 2 Measured by location quotients. Location quotients measure the level of regional specialisation. Values over 1 indicate aboveaverage levels of concentration. 3 Figure 1: Creative and cultural industries concentration and regional prosperity. If we take into account no other factors, regional creative and cultural specialisation explains 60% of the variance in GDP per capita. Europe’s wealthiest regions are home to disproportionate levels of creative and cultural industries concentration. It is likely that creative and cultural firms and employees are drawn to the markets represented by prosperous regions but also that the creative and cultural industries are themselves important components of and contributors to the economies of Europe’s wealthiest regions. 2 Principal labour markets The largest concentrations of creative and cultural industries employees in Europe are major urban areas. This confirms academic research findings and literature that suggests that creative and cultural activities that become industrialised are concentrated in and attracted to large urban areas. Creativity and cultural innovation, of course, happen in many different types of region across Europe but it seems that large scale industrialisation of these activities occurs in large urban areas. 4 Table 1. Europe’s Top 25 regions for creative and cultural industries employment clusters. Region CCI Rank Employment LQ Île de France (Paris), FR 1 301,895 1.53 Inner London, UK 2 235,327 2.19 Lombardia (Milan), IT 3 195,848 1.28 West-Nederland (Amsterdam), NL 4 195,646 1.56 Madrid, ES 5 172,800 1.58 Cataluña (Barcelona), ES 6 153,202 1.30 Danmark, DK 7 124,352 1.28 Lazio (Rome), IT 8 118,047 1.51 Oberbayern (München), DE 9 97,050 1.59 Stockholm, SE 10 86,239 2.16 Kozep-Magyarorszag (Budapest), HU 11 82,429 1.73 Outer London, UK 12 80,845 1.28 Berks, Bucks and Oxon (Oxford), UK 13 80,628 1.82 Attiki (Athens), GR 14 78,920 1.26 Oost-Nederland (Nijmegen), NL 15 74,064 1.39 Andalucía (Sevilla), ES 16 71,843 0.74 Ireland, IE 17 70,602 1.18 Zuid-Nederland (Maastricht), NL 18 70,543 1.28 Darmstadt (Frankfurt am Main), DE 19 68,238 1.23 Piemonte (Turin), IT 20 66,291 1.04 Köln, DE 21 65,341 1.28 Etelä-Suomi (Helsinki), FI 22 64,500 1.43 Veneto (Venice), IT 23 63,024 0.89 Stuttgart, DE 24 61,626 1.17 Berlin, DE 25 60,736 1.53 Note: LQ is an indicator of CCI employment relative to the total employment of the region, where LQ>1 indicates an overrepresentation of CCI employment. Most of the largest employment clusters have higher than average levels of CCI concentration. This can be seen from location quotients listed in the Table 1 above. However, two of the top 25 clusters have lower than average shares of CCI employment: Seville and Venice. 5 Table 2. Regions which rank in the top 25 either by regional population size or creative and cultural industries employment. Region Largest City Population Rank CCI Rank Île de France (FR) Paris 1 1 Lombardia (IT) Milan 2 3 Andalucía (ES) Sevilla 3 16 West-Nederland (NL) Amsterdam 4 4 Cataluña (ES) Barcelona 5 6 Vlaams Gewest (BE) Antwerpen 6 31 Rhône-Alpes (FR) Lyon 7 37 Campania (IT) Naples 8 39 Madrid (ES) Madrid 9 5 Danmark (DK) - 10 7 Düsseldorf (DE) Düsseldorf 11 26 Lazio (IT) Rome 12 8 Mazowieckie (PL) Warszawa 13 42 Sicilia (IT) Palermo 14 58 Provence-Alpes-Côte d'Azur (FR) Marseille 15 50 Slaskie (PL) Katowice 16 160 Veneto (IT) Venice 17 23 Outer London (UK) Outer London 18 12 Valencia (ES) Valencia 19 27 Köln (DE) Köln 20 21 Piemonte (IT) Turin 21 20 Oberbayern (DE) München 22 9 Emilia-Romagna (IT) Bologna 23 28 Ireland (IE) - 24 17 Puglia (IT) Bari 25 72 Stuttgart (DE) Stuttgart 27 24 Attiki (GR) Athens 28 14 Darmstadt (DE) Frankfurt am Main 30 19 Zuid-Nederland (NL) Maastricht 35 18 Oost-Nederland (NL) Nijmegen 36 15 Berlin (DE) Berlin 39 25 Inner London (UK) Inner London 46 2 Kozep-Magyarorszag (HU) Budapest 49 11 Etelä-Suomi (FI) Helsinki 60 22 Berks, Bucks and Oxon (UK) Oxford 82 13 Stockholm (SE) Stockholm 98 10 Note: CCI rank is the rank in CCI employment Whilst there is a relationship between CCI and large urban areas this is not always so. Though many of Europe’s most populous regions are home to highly ranked CCI clusters, some of the largest regions are lagging in CCI employment. 6 Among the regions of Europe which rank among the top 25 either by population or CCI employment the following cities host an over-representation of the creative and cultural sector: Athens, Berlin, Budapest, Denmark, Frankfurt, Helsinki, Ireland, Inner London, Outer London, Maastricht, Madrid, Munich, Nijmegen, Oxford, Rome, Stockholm, and Stuttgart. Of the regions with 25 largest populations the following have a far lower than expected representation of creative and cultural industries: Antwerp, Bari, Bologna, Düsseldorf, Katowice, Lyon, Marseille, Naples, Palermo, Seville, Valencia, Venice, Warszawa. As with many industrial sectors, firms and labour are unequally distributed and this indicates the existence of regional industrial and innovation systems and clusters underpinned by favourable regional conditions. Employment and competitiveness in the creative and cultural industries is not directly related to labour market size or population and cannot be considered a simple by-product of human habitation. Creative and culture activities are knowledge driven industries that are drawn to specialised labour markets and to clusters. Clusters and large labour markets support organisational and project-base scale and scope. 3 Regional specialisation and focus Regional creative and cultural industries specialisation is not limited to the largest urban areas but capital city regions and certain of the largest cities exhibit strong CCI Focuses. The table and map below show the share of a region’s labour force employed by creative and cultural industries. 7 Figure 2. CCI Focus: Creative and cultural industries share of regional labour force 2006 Of the 15 regions with the highest CCI Focus most are capital city regions. In all but two countries capital city regions have the highest national CCI Focus: Germany where Hamburg is the city with the highest CCI Focus and Munich is the largest employment centre; and Switzerland where Basel the city with the highest CCI Focus and Zurich is the largest employment centre. Of the Top 15 CCI Focus regions, three are in Central and Eastern Europe: Prague, Bratislava, and Budapest. The creative and cultural industries have almost the same share of the entire regional labour market in Prague as is the case in Inner London. 8 Table 3. Top 15 regions by CCI Focus. CCI Focus Employment CCI Rank Inner London, UK 5.95% 235,327 2 Stockholm, SE 5.87% 86,239 10 Praha, CZ 5.81% 53,461 35 Bratislavsky kraj (Bratislava), SK 5.01% 21,776 87 Berks, Bucks and Oxon (Oxford), UK 4.94% 80,628 13 Hamburg, DE 4.75% 54,867 32 Kozep-Magyarorszag (Budapest), HU 4.69% 82,429 11 Oslo og Akershus, NO 4.61% 39,778 44 Oberbayern (München), DE 4.32% 97,050 9 Karlsruhe, DE 4.30% 55,794 30 Madrid, ES 4.30% 172,800 5 West-Nederland (Amsterdam), NL 4.23% 195,646 4 Berlin, DE 4.15% 60,736 25 Île de France (Paris), FR 4.15% 301,895 1 Lazio (Rome), IT 4.11% 118,047 8 Note: Focus indicates how large share of the region’s total employment the CCI sector constitutes. Creative and cultural industries command unusually high share of regional employment in Bratislava. This demonstrates that relatively small European regions can also score highly on specialisation and focus measures, even if the opposite is more common. 4 Growth 3 The creative and cultural industries are a sector of the European economy that exhibit strong growth . However, as the map below shows that growth is not evenly spread over Europe. As can be seen higher levels of growth was broadly concentrated in areas of central Europe, areas of France, Spain, UK and the Baltic States. In Germany and Scandinavia there is a mixed picture with certain regions showing higher growth rates whilst others suffered CCI employment decline in the period. 3 Time series data was not available for the following countries: Bulgaria, Cyprus, Greece, Italy, Netherlands, Poland, Portugal, Romania. 9 Figure 3. Creative and cultural industries average annual growth 2001-2006. Note: Growth is measured using compound annual growth rates (CAGR). In 24 of the top 25 CCI growth regions the creative and cultural industries grew at a faster rate than the rest of the labour market. 10 Table 4. Regions with the highest average annual growth in CCI employment 2001-2006. CCI Growth Rest of the economy CCI LQ CCI Rank CCI Employment Niederösterreich (St. Pölten), AT 16.63% 7.60% Salzburg, AT 10.00% 6.32% 1.07 84 22,593 1.08 161 10,434 Oberösterreich (Linz), AT 8.99% 6.97% 0.73 126 14,506 Asturias (Oviedo), ES 8.42% 3.05% 0.85 146 11,399 Zapadne Slovensko (Nitra), SK 8.35% 1.96% 0.68 106 17,728 Cumbria (Carlisle), UK 8.31% 2.47% 0.84 220 5,087 La Rioja (Logroño), ES 7.99% 5.64% 0.70 237 3,217 Andalucía (Sevilla), ES 7.78% 5.27% 0.74 16 71,843 Hants and Isle of Wight (Southampton), UK 7.22% 1.18% 1.27 45 38,851 Castilla-La Mancha (Toledo), ES 6.87% 4.79% 0.67 109 16,528 Jihovychod (Brno), CZ 6.65% 0.39% 0.86 89 21,606 País Vasco (Bilbao), ES 6.51% 2.52% 1.12 51 36,539 Murcia, ES 6.35% 5.25% 0.61 152 10,906 Valencia, ES 6.25% 4.48% 0.86 27 59,901 Kärnten (Klagenfurt), AT 6.13% 4.55% 0.73 222 4,950 Lietuva, LT 5.79% 3.63% 0.88 68 26,102 Galicia (A Coruña), ES 5.45% 2.71% 0.78 60 29,294 Picardie (Amiens), FR 5.41% 1.31% 0.55 181 8,934 Nyugat-Dunantul (Györ), HU 5.33% -0.51% 0.65 180 9,002 Extremadura (Mérida), ES 5.32% 3.11% 0.66 188 8,022 Canarias (Tenerife), ES 4.97% 4.16% 0.79 88 21,765 Steiermark (Graz), AT 4.87% 5.63% 0.76 144 11,479 Corse (Ajaccio), FR 4.72% 4.08% 0.45 247 1,092 Heref, Worcs and Warws (Hereford), UK 4.67% 0.84% 1.12 91 21,115 E Riding and N Lincs, UK 4.55% 1.61% 0.75 177 9,104 Note: LQ is an indicator of CCI employment relative to the total employment of the region, where LQ>1 indicates an over-representation of CCI employment. Growth is measured using compound annual growth rates (CAGR). It is striking that 15 of the top 25 growth regions between 2001 and 2006 were in either Austria or Spain. Austria accounts for 5 of the top CCI Growth regions and Spain 10 top CCI Growth regions. Indeed growth and contraction are highly regionalised in Europe. This can be seen for instance in the United Kingdom where certain regions had high annual growth rates - Cumbria (Carlisle) 8.31%; Hampshire and Isle of Wight (Southampton) 7.22%; Hereford, Worcester and Warwickshire (Hereford) 4.67%; East Riding and North Lincolnshire 4.55 - whilst the 6 regions with the largest labour markets suffered decline – Inner London -1.29%, Outer London -3.42%; Berkshire, Buckinghamshire and Oxfordshire (Oxford) -1.6%; East and West Surrey (Brighton) -3.17%; Greater Manchester -1.4%; West Midlands (Birmingham) -1.64%. 11 Many of the fastest growing regions are relatively small and are growing from a lower than average baseline. Indeed 20 of the top 25 growth regions have CCI shares of regional employment below or well below the average European region. Higher than average growth in certain of these regions may reflect lower base lines as well as the quickening pace of catch-up. Most of the regions in the top 25 highest cultural and creative growth regions are small and medium sized regions. However, the following regions with labour markets over 1 million people were in the top 25 for annual employment growth: Seville (7.78%), Southampton (7.22%), Valencia (6.25%), Bilbao (6.51%), Galicia (5.45%), Lithuania (5.79%). For those European regions we have growth data for, almost as many regions suffered declines in CCI employment as there were regions that experienced growth: 92 regions grew versus 89 declined (66 regions with no growth data). From the data at our disposal it is difficult to draw any conclusions about why there is such a mixed growth picture. One possible explanation, for which there is some evidence, is that CCI growth/decline is linked to cycles in the rest of the regional labour market and that CCI will grow where there is growth and decline where there is general decline. This would indicate that creative and cultural industries are embedded and interdependent with the surrounding economy; rather than independent of the region as entirely export oriented industries may be. An alternative explanation is that the data only concentrates on employment trends and it may be that declines in employment are due to, or compensated for, by increases in sole-trading and other entrepreneurial activity that would not appear in our statistics. Certainly many sectors within the creative and cultural industries have come under pressure from digital transitions which have created new opportunities and threats as well as leading to productivity gains and changing organisational forms that may have led to employment decreases. Regionalised patterns of growth and change seem to be a strong feature of the creative and cultural industries. 5 National perspectives on growth and size In most cases, employment in the creative and cultural industries seems largely to reflect growth rates in the entire economy. For many countries creative and cultural industries employment growth was an amplified version of general growth: if employment was going up it went up faster in creative and cultural industries and vice versa. As can be seen from Table 5, the general pattern is that overall employment increases in the country are equalled or bettered by creative and cultural industries, whilst negative overall growth is coupled by higher levels of decline in the creative and cultural industries. For example in Austria and Lithuania overall employment growth was strong in the period 2001-2006 and creative and cultural industries 12 employment reflected and bettered this positive upturn. In Norway and Germany the opposite was the case: as employment in the overall economy turned negative, employment in the creative and cultural industries fell even faster. Spain, Ireland, and France are notable exceptions to this tendency: in these countries positive annual growth rates for the entire economy were significantly above CCI growth rates. Table 5. Average annual employment growth 2001-2006 in creative and cultural industries and in all sectors of the economy. Country CCI Growth All Growth Austria 6.20% 5.42% Lithuania 5.79% 3.63% Estonia 4.02% 2.71% Slovakia 3.88% 0.63% Latvia 3.87% 3.89% Slovenia 3.76% 0.78% Spain 2.78% 3.86% Hungary 1.45% 0.08% Czech Republic 0.80% 0.30% Luxembourg 0.72% 1.55% Ireland 0.55% 3.75% France -0.14% 1.40% Iceland -0.22% 0.10% Finland -0.47% -0.10% United Kingdom -0.55% 0.32% Belgium -0.82% 0.07% Sweden -0.97% -0.32% Switzerland -1.47% -0.13% Denmark -1.99% -1.07% Germany -2.08% -1.39% Norway -2.41% -0.28% Note: Growth is calculated here as a Compound Annual Growth Rate (CAGR) over the period. Small countries tend to have a higher CCI Focus than large countries. As Table 6 shows, of the 12 countries with the highest CCI Focus only two have a population of over 10 million: the Netherlands and the UK. The lower share of total employment that CCI account for in larger countries may be due to the ability to exploit greater economies of scale in creative and cultural product provision. It may also be that smaller countries own language, cultural heritage and specificity mean that substitutes are harder to import, or demand more labour to tailor to local conditions and demands. All countries big or small need a foundation of cultural and media institutions and it can be assumed that all need an indigenous basic provision: something that cannot be imported from outside. 13 Table 6. National labour markets and CCI Focus. Country CCI Focus CCI Rank CCI Employment Iceland 4.01% 28 8,633 Netherlands 3.94% 6 377,903 Sweden 3.76% 7 205,831 Denmark 3.48% 15 124,352 Switzerland 3.40% 8 167,479 Finland 3.25% 18 96,511 Ireland 3.20% 20 70,602 Estonia 3.14% 26 23,965 United Kingdom 3.12% 1 1,131,697 Norway 2.96% 19 81,874 Malta 2.94% 29 5,765 Slovenia 2.87% 24 29,151 Austria 2.83% 12 131,015 Germany 2.79% 2 956,668 Spain 2.74% 4 655,042 Hungary 2.73% 11 134,921 Italy 2.66% 3 767,521 Czech Republic 2.64% 10 156,272 Latvia 2.60% 23 31,720 Cyprus 2.52% 27 10,794 France 2.52% 5 634,251 Lithuania 2.38% 25 26,102 Slovakia 2.30% 22 61,777 Greece 2.28% 13 128,421 Belgium 2.26% 16 101,646 Portugal 2.13% 17 96,741 Luxembourg 2.08% 30 5,273 Poland 1.69% 9 162,408 Bulgaria 1.63% 21 65,587 Romania 1.18% 14 126,637 Europe 2.71% 6,576,558 Note: Focus indicates how large share of the nation’s total employment the CCI sector constitutes. Table 6 clearly demonstrates the need to take a regional and cluster approach to these industries. For example whilst Romania has the lowest share of its total employment in creative and cultural th th industries, as a nation it ranks 14 in Europe and the capital region of Bucharest ranks 34 of all European regions whilst being home to 42.6% of the nation’s creative and cultural industries employees. 6 Innovation The Lisbon Treaty as well as a significant academic literature posits a relation between regional innovation and the presence of creative and cultural industries. Since creative and cultural industries operate in fast moving and often fashion oriented markets continual innovation and creativity is core to 14 competitive advantage. Regional clusters must innovate in order to survive or grow and innovation is likely to be reflected in employment growth. Equally one might expect to see knowledge and innovation spill-over from creative and cultural industries to other areas of the economy. There is a relationship between CCI employment and traditional innovation indicators such as patent applications but as can be seen in the Figure below it is not a definite or direct relationship. Thus the thesis that creative and cultural industries and workers are interlinked to other types of ‘creative’ and innovative industries is not definitely provable. Figure 4. Creative and cultural industries concentration and patent applications. Note: LQ is an indicator of CCI employment relative to the total employment of the region, where LQ>1 indicates an over-representation of CCI employment. Similarly it is not possible to draw direct relationships between standard regional innovation performance measures and creative industries growth. With the exceptions of Gothenburg, Malmoe Prague and Vienna, those regions with the 20 highest Regional Innovation Scoreboard value (RIS) 4 4 Regional Innovation Scoreboard 2006 conducted by Maastricht Economic and social Research and training centre on Innovation and Technology (MERIT): 2006 European Regional Innovation Scoreboard, MERIT, 2006. 15 all suffered negative creative and cultural industries growth. RIS is therefore not an adequate predicator of growth in this area. Table 7. Top 20 regions on the Regional Innovation Scoreboard (RIS) and average annual growth in creative and cultural industries. RIS 2006 Annual CCI Growth (CAGR) Stockholm, SE 0.895 -2.07% Västsverige (Gothenburg), SE 0.828 1.07% Oberbayern (München), DE 0.791 -1.84% Etelä-Suomi (Helsinki), FI 0.782 -0.38% Karlsruhe, DE 0.775 -0.55% Region Stuttgart, DE 0.768 -1.52% Braunschweig, DE 0.759 -0.98% Sydsverige (Malmö), SE 0.758 0.39% Île de France (Paris), FR 0.746 -0.85% Östra Mellansverige (Uppsala), SE 0.742 -1.93% Berlin, DE 0.737 -1.74% Tübingen, DE 0.718 -0.85% Praha, CZ 0.698 1.37% Darmstadt (Frankfurt am Main), DE 0.693 -3.11% Dresden, DE 0.687 -0.49% Köln, DE 0.686 -2.31% Danmark, DK 0.681 -1.99% Pohjois-Suomi (Oulu), FI 0.679 -0.33% Mittelfranken (Nürnberg), DE 0.676 -3.12% Wien, AT 0.675 2.36% The mixed results above likely point to the difficulty of using standard innovation performance indicators – such as RIS and patent data – to measure innovation levels and conditions in creative and cultural industries. Many of the types of knowledge, goods, services and business models produced by the creative and cultural industries simply cannot be protected by patents. Other types of intellectual property appropriation and exploitation regimes are much more central to the creative and cultural industries. In particular copyright is a more prevalent form of intellectual property appropriation in creative and cultural industries than patent. Regional innovation measures tend to stress a region’s science and high technology emphasis and it is not clear that all of the creative and cultural industries are reliant upon such types of ‘innovation’ system to maintain their own creativity and innovation. Innovation performance indicators better attuned to the innovation dynamics (and likely spill over areas) of the creative and cultural industries are needed in order to make more definite conclusions about their impact on and role in regional innovation. 16 7 Intellectual property The creative and cultural industries are significant generators of intellectual property in particular copyrights. Using the World Intellectual Property Organization (WIPO) definition for Copyright-Based 5 Industries , it can be seen that the largest creative and cultural industries regions are generally also the largest employment centres for copyright-based industries. Table 8. Top 10 regions by employees in CCI and Copyright-based Industries. CCI WIPO 1 Île de France (Paris) 301,895 1 Île de France (Paris) 2 Inner London 235,327 2 Inner London 371,400 212,479 3 Lombardia (Milan) 195,848 3 Madrid 209,784 4 West-Nederland (Amsterdam) 195,646 4 West-Nederland (Amsterdam) 193,344 5 Madrid 172,800 5 Lombardia (Milan) 182,503 6 Cataluña (Barcelona) 153,202 6 Cataluña (Barcelona) 151,286 7 Danmark 124,352 7 Lazio (Rome) 123,822 8 Lazio (Rome) 118,047 8 Danmark 122,189 9 Oberbayern (München) 97,050 9 Oberbayern (München) 101,417 10 Stockholm 86,239 10 Zuid-Nederland (Maastricht) 86,830 Regions with a high creative and cultural industries focus – the share of a region’s labour force employed by creative and cultural industries – also have a high focus on copyright-based industries. Table 9. Top 10 regions by CCI Focus and Copyright-based Industries Focus. Region CCI Focus Employment WIPO Focus Employment Inner London, UK 5.95% 235,327 5.64% 212,479 Stockholm, SE 5.87% 86,239 5.48% 76,601 Praha, CZ 5.81% 53,461 6.48% 57,113 Bratislavsky kraj (Bratislava), SK 5.01% 21,776 5.10% 21,287 Berks, Bucks and Oxon (Oxford), UK 4.94% 80,628 4.36% 68,148 Hamburg, DE 4.75% 54,867 4.60% 51,170 Kozep-Magyarorszag (Budapest), HU 4.69% 82,429 4.34% 73,615 Oslo og Akershus, NO 4.61% 39,778 4.62% 38,250 Oberbayern (München), DE 4.32% 97,050 4.68% 101,417 Karlsruhe, DE 4.30% 55,794 3.71% 46,270 Note: Focus indicates how large share of the region’s total employment the CCI sector constitutes. 5 See Methodological Appendix for details and comparison of the WIPO definition to the Cluster Observatory definition. 17 8 Breaking down the creative and cultural industries There has been considerable debate over the idea that the industries we suggest comprise the creative and cultural industries can in fact be aggregated. We agree that despite many similarities and interdependencies the activities gathered under the umbrella of creative and cultural industries need also to be understood as separate industries in their own rights. The knowledge requirements, working methods, business and organisational models and consumer interfaces that define competitiveness in computer games are, for instance, very different to those that shape competitiveness in performance arts. It is necessary to understand the creative and cultural industries not as a unified category but as an aggregate category. It is necessary to understand that the industries that make up the European creative and cultural industries competitiveness share much but also exhibit unique and different cluster dynamics. The creative and cultural industries are a term that includes a variety of different related industries. Our definition includes not just ‘cultural’ industries but also ‘creative’ industries such as certain types of software work (e.g. publishing of software, software consultancy and supply, new media and computer games). These are industries that are defined by their creative working and by the intellectual property they create. Together they employ 1,471,915 Europeans in 30 countries: 22.3% of creative and cultural industries employees work with software publishing, consultancy or supply. Table 10. Top 15 employment centres for software. Region Software Employment Île de France (Paris), FR 63,617 West-Nederland (Amsterdam), NL 47,843 Inner London, UK 44,081 Berks, Bucks and Oxon (Oxford), UK 41,955 Lombardia (Milan), IT 41,857 Madrid, ES 37,145 Lazio (Rome), IT 33,486 Stockholm, SE 33,239 Danmark, DK 31,525 Oberbayern (München), DE 31,074 Cataluña (Barcelona), ES 28,741 Karlsruhe, DE 28,332 Darmstadt (Frankfurt am Main), DE 26,785 Surrey, E and W Sussex (Brighton), UK 24,173 Outer London, UK 23,833 The following maps show employment concentrations for four activity areas within the creative and cultural industries: Artistic creation and literary interpretation; Advertising; Radio and television activities; Museum activities and preservation of historical sites and buildings. 18 The maps indicate that for these parts of the creative and cultural industries clustering is a prominent feature. In particular Inner London and its surrounding regions and the Paris region are the largest centres in each of the four industries. Amsterdam, Madrid and Milan are also important centres. However despite the existence of prominent clusters in each of the industries many other centres exist. Figure 5. Artistic creation and literary interpretation 19 Figure 6. Advertising Figure 7. Radio and television activities 20 Figure 8. Museum activities and preservation of historical sites and buildings The Table below lists the top 15 clusters (defined by employment and share of total European employment in that category) in the four fields illustrated above: Artistic creation and literary interpretation; Advertising; Radio and television activities; Museum activities and preservation of historical sites and buildings. These figures clearly show the role of Paris, London, Milan, Amsterdam and Madrid as Europe’s most important employment centres for creative and cultural industries. Of these the super clusters London and Paris stand out. 21 Table 11: Top 15 regions by number of employees and share of European employment in four sectors of the creative and cultural industries. Employment European share Radio and television activities Employment European share Advertising 1 Inner London 31,231 8.08% Île de France (Paris) 52,202 7.56% 2 Île de France (Paris) 24,472 6.33% Lombardia (Milan) 30,020 4.35% 3 Madrid 19,105 4.95% Inner London 24,348 3.53% 4 Cataluña (Barcelona) 10,756 2.78% West-Nederland (Amsterdam) 19,876 2.88% 5 Köln 10,317 2.67% Madrid 18,738 2.71% 6 Bucuresti – Ilfov 10,122 2.62% Danmark 17,343 2.51% 7 Oberbayern (München) 10,037 2.60% Cataluña (Barcelona) 12,410 1.80% 8 West-Nederland (Amsterdam) 7,647 1.98% Düsseldorf 11,653 1.69% 9 Lazio (Rome) 7,516 1.95% Stockholm 11,230 1.63% 1.95% Darmstadt Main) 10,053 1.46% 7,515 (Frankfurt am 10 Outer London 11 Andalucía (Sevilla) 7,385 1.91% Hamburg 9,664 1.40% 12 Attiki (Athens) 7,100 1.84% Attiki (Athens) 9,266 1.34% 13 Danmark 6,648 1.72% Lazio (Rome) 9,246 1.34% 14 Rheinhessen-Pfalz (Mainz) 6,644 1.72% Lisboa 9,217 1.33% 15 E Scotland (Edinburgh) 6,351 1.64% Zuid-Nederland (Maastricht) 8,970 1.30% Museum activities and preservation of historical sites and buildings Artistic and literary creation and interpretation 1 Île de France (Paris) 20,113 6.80% Île de France (Paris) 10,675 6.24% 2 Inner London 18,434 6.23% 3 West-Nederland (Amsterdam) Inner London 6,993 4.09% 5,774 1.95% Danmark 5,162 3.02% 4 Outer London 5,357 1.81% West-Nederland (Amsterdam) 4,525 2.64% 5 6 Danmark 5,156 1.74% E Scotland (Edinburgh), 3,370 1.97% Stockholm 4,983 1.68% Vlaams Gewest (Antwerpen), 2,850 1.66% 7 Etelä-Suomi (Helsinki) 8 Lombardia (Milan) 4,549 1.54% Lazio (Rome) 2,720 1.59% 4,448 1.50% Stockholm 2,648 1.55% 9 Rhône-Alpes (Lyon) 4,165 1.41% Ireland 2,631 1.54% 10 11 Slovenija 4,119 1.39% Latvija 2,497 1.46% Lazio (Rome) 4,000 1.35% Madrid 2,240 1.31% 12 Provence-Alpes-Côte d'Azur (Marseille) 3,767 1.27% Kozep-Magyarorszag (Budapest) 2,120 1.24% 13 Surrey, E and W Sussex (Brighton) 3,714 1.26% Cataluña (Barcelona) 2,102 1.23% 14 Cataluña (Barcelona) 3,539 1.20% Malopolskie (Kraków) 2,040 1.19% 15 Kozep-Magyarorszag (Budapest) 3,533 1.19% Oost-Nederland (Nijmegen) 2,010 1.17% Not all parts of the creative and cultural industries, however, are so dominated by a couple of large cities. As the Table and Map below clearly show in Print Media there is a much more even spread of activities over Europe. This may be explained by the fact that print media employs large numbers of employees in production and distribution and it may not be necessary or desirable to locate these employees in the largest urban areas. The print media employs 2,285,744 people or 34.8% of all the 22 creative and cultural industries and is thus central to the contribution of this sector to Europe competitiveness. Table 12. Top 15 regions by number of employees and share of European employment in Print Media. Rank Employment European share 1 Île de France (Paris) 81,696 3.57% 2 Lombardia (Milan) 68,582 3.00% 3 Inner London 64,323 2.81% 4 Cataluña (Barcelona) 62,015 2.71% 5 West-Nederland (Amsterdam) 55,884 2.44% 6 Madrid 53,244 2.33% 7 Attiki (Athens) 38,271 1.67% 8 Danmark 36,121 1.58% 9 Oberbayern (München) 30,313 1.33% 10 Andalucía (Sevilla) 28,753 1.26% 11 Mazowieckie (Warszawa) 28,720 1.26% 12 Lazio (Rome) 28,420 1.24% 13 Oost-Nederland (Nijmegen) 26,580 1.16% 14 Kozep-Magyarorszag (Budapest) 24,523 1.07% 15 Bucuresti – Ilfov 24,222 1.06% Note: Print media is an aggregate of the following NACE codes: 22.11, 22.12, 22.13, 22.21, 22.22, 22.23, 22.24, 22.25, 52.47. Figure 9. Print media employment. 23 8 Clustering and value chains Whilst there are different cluster and location tendencies for different sectors of the creative and cultural industries it is interesting to note that different stages in the CCI value chain also exhibit different cluster tendencies. Manufacturing activities are the most regionally concentrated, and consumer oriented activities the least regionally concentrated. Concentration measures clearly show that the most concentrated creative and cultural industries are those involved in specialised manufacture: recorded media and musical instruments. There is considerable evidence from other industries that specialised manufacturing benefits from, and is drawn to, industry clusters; it seems this is also the case in creative and cultural industries. A similar pattern can be found for production related activities such as publishing of software and music, news agencies, and film production. The least concentrated activities are those in the value chain that are nearest the consumer: such as bookshops, cinemas, and exhibition spaces. Such activities do exhibit some cluster tendencies at a European level but locational concentration is likely more apparent within regions: e.g. at the level of shopping or theatre districts. Employees in firms focused on advertising and in artistic and literary creation and interpretation are also less likely to be concentrated in dominant centres. This is likely due to the need to locally tailor advertising campaigns or artistic and literary products to local conditions: something that is most efficiently done in proximity to end users. Nonetheless as was shown earlier a degree of clustering on a European level can be found in both of these activities and several large urban areas are home to disproportionate concentrations of these activities. 24 6 Table 13. The most concentrated and clustered creative and cultural industries sub-sectors . NACE Category Gini Krugman Theil Reproduction of computer media 0.88 (1) 1.46 (1) 2.05 (1) Reproduction of sound recording 0.85 (2) 1.40 (2) 1.71 (2) Reproduction of video recording 0.80 (3) 1.25 (3) 1.39 (3) Manufacture of prepared unrecorded media 0.76 (4) 1.24 (4) 1.17 (5) Manufacture of musical instruments 0.73 (5) 1.11 (7) 1.30 (4) Publishing of software 0.73 (6) 1.15 (5) 1.00 (7) Publishing of sound recordings 0.72 (7) 1.14 (6) 1.01 (6) Motion picture and video distribution 0.66 (8) 1.05 (8) 0.83 (8) News agency activities 0.65 (9) 1.02 (9) 0.81 (9) Motion picture and video production 0.61 (10) 0.92 (10) 0.74 (10) Other publishing 0.60 (11) 0.86 (12) 0.73 (11) Printing of newspapers 0.59 (12) 0.89 (11) 0.62 (12) Radio and television activities 0.55 (13) 0.84 (13) 0.56 (13) Publishing of books 0.53 (14) 0.80 (14) 0.48 (17) Bookbinding 0.52 (15) 0.76 (16) 0.49 (14) Publishing of journals and periodicals 0.51 (16) 0.76 (15) 0.48 (15) Ancillary activities related to printing 0.51 (17) 0.72 (18) 0.48 (16) Pre-press activities 0.48 (18) 0.69 (19) 0.43 (18) Library and archives activities 0.48 (19) 0.74 (17) 0.40 (19) Other entertainment activities n.e.c. 0.47 (20) 0.68 (20) 0.39 (20) Operation of arts facilities 0.45 (21) 0.65 (21) 0.34 (21) Other software consultancy and supply 0.44 (22) 0.63 (22) 0.32 (22) Publishing of newspapers 0.40 (23) 0.57 (24) 0.27 (23) Museums activities, etc. 0.39 (24) 0.58 (23) 0.25 (25) Artistic and literary creation and interpretation 0.39 (25) 0.55 (25) 0.25 (24) Advertising 0.37 (26) 0.53 (26) 0.23 (26) Printing n.e.c. 0.30 (27) 0.42 (27) 0.15 (28) Photographic activities 0.29 (28) 0.41 (29) 0.17 (27) Motion picture projection 0.29 (29) 0.41 (28) 0.15 (29) Retail sale of books, newspapers and stationery 0.25 (30) 0.36 (30) 0.12 (30) 6 Based on data for 2006 for 16 countries where 4-digit NACE data was available at a regional level. The countries are: BE, BG, CH, DK, DE, FI, FR, IE, IS, LT LV, NL, NO, RO, SE and UK. ‘Gini’, ‘Krugman’ and ‘Thiel’ are statistical measures of regional inequality or coefficients of variation. 25 About the European Cluster Observatory The European Cluster Observatory, launched in June 2007, is the most comprehensive database on clusters, cluster organisations, and cluster reports in Europe. It is managed by the Center for Strategy and Competitiveness (CSC) at the Stockholm School of Economics and funded by the European Commission's Directorate General for Enterprise and Industry. The European Cluster Observatory website provides a wide variety of data on clusters in Europe, and is focused on the following issues:  Cluster Mapping providing information on 38 cluster categories in 259 NUTS II regions  Information, maps and lists of regional or local private-public partnerships focused on cluster improvements  Providing reports on national and regional cluster policies and programmes  Providing detailed knowledge thorough publishing Observatory reports, cluster case studies and other cluster-related documents In 2009, the Observatory entered the second phase of development bringing new features and introducing a collaboration platform for cluster organisations and SMEs. Please visit the European Cluster Observatory at www.clusterobservatory.eu. 26 Priority Sector Report: Creative and Cultural Industries – Methodological Appendix Dominic Power, Uppsala University Tobias Nielsén, Volante QNB Research March 2010 – deliverable D9-1 Conceptual definition This report is about both the „creative industries‟ and the „cultural industries‟ over which there has been considerable debate. This report will not try to summarize or repeat these debates. There is an extensive literature that gives more detailed accounts of the various terms and debates related to creative and cultural industries: (Caves 2000; Scott 2000; Hesmondhalgh 2002; Power 2002; Power and Scott 2004; Pratt 2005; Fleming 2007; Galloway and Dunlop 2007; Kolmodin, Pelli, Bager-Sjögren et al. 2008; Nielsen 2008; Jeffcutt and Pratt 2009; Mato 2009; Miller 2009; Power 2009). However, whilst each term has a separate heritage and legacy they share much. In industrial policy and analysis both these terms share a common concern with industries that have often been marginalized from economic and industrial analysis and policy. In particular both terms share a focus on industries such as film, art, design, music etc. that have largely been treated as issues for cultural policy and debate but are now recognized as important economic fields in their own right. The terms have been used in many ways but are usually thought to signify industries that deal with the following activity areas:   Advertising  Broadcast media  Gaming software, new media     Architecture Design - Fashion design, graphic design, interior design, product design Film The “finer” arts – literary, visual and performance arts Libraries, museums, heritage   Music  Print media  Photography Object d‟art - Glass, ceramics, cutlery, crafts, jewelry Moreover these industries, rightly or wrongly, are suggested to share something that makes treating them as interlinked or similar meaningful and worthwhile. Both terms attempt to group together diverse sectors or industries that (a) have previously been seen as marginal to economic and industrial concerns or primarily cultural, and (b) that despite their obvious diversity seem to be similar, interlinked or interdependent. The main difference between different concepts within this area is that they tend to either place importance on outputs or on inputs and process. Concepts such as „cultural industries‟, „copyright industries‟ and „content industries‟ tend to define industries for inclusion by reference to their principal outputs or core products. Definitions of this type emphasis the idea that industries for inclusion are those concerned in one way or another with the creation of products whose value rests primarily on their symbolic or aesthetic content and the ways in which the products stimulate the experiential reactions of consumers. In many cases the outputs of these industries are partly defined by the fact that they are intellectual property and in particular intellectual property subject to copyright. Copyright is one of the main branches of intellectual property and applies to “every production in the literary, scientific and artistic domain, whatever may be the mode or form of its expression” (Article 2, Berne Convention for the Protection of Literary and Artistic Works). Literary and artistic works are outputs based on original work of authorship and include books, music, plays, choreography, photography, films, paintings, sculptures, compute programs and databases (WIPO 2003). Concepts such as „creative industries‟ define industries for inclusion on the basis of the types of inputs and generative processes that characterize their core value creation. The idea of creative industries stresses the centrality of creativity - mental and social processes involving the discovery of new ideas, concepts or associations – to how firms and workers come up with and commercialize products. The types of products offered by creative industries can be both valued in their own right or valued as knowledge-based services. The range of industries, inputs and outputs of these activities makes viewing them as either a service sector or a producer sector impossible. Indeed firms in certain of these industries might be simultaneously engaged in both service provision and their own proprietary products. The stress on creative inputs and working processes means that the term can be interpreted as wider in scope than terms that stress cultural outputs: culture need not be particularly new to have profound value. However, as the Lisbon Treaty recognizes, culture as crucially related to and often an essential catalyst for creativity. It is fair to say that there has been considerable conceptual confusion and debate over these terms. Equally it is also fair to say that despite differences there is considerable overlap when considering 2 which industries are involved with creative and cultural outputs and those that are concerned with creative inputs and processes. In this sector priority report we have counted on a certain level of interchangeability between the two terms. This means that we use the terms interchangeably but also that we see them as conceptually linked and similar. Indeed given policy and academic debates in the area it is practical to talk of „creative and cultural industries‟. For the purposes of this report we use the following definition of creative and cultural industries: those concerned with the creation and provision of marketable outputs (goods, services and activities) that depend on creative and cultural inputs for their value. This definition shares much in common with the combination of creative and cultural industries certain European countries have adopted: “The Conference of German Ministers of Economic Affairs has defined culture and creative industries in the following way: Culture and creative industries comprise of all cultural and creative enterprises that are mainly market-oriented and deal with the creation, production, distribution and/or dissemination through the media of cultural/creative goods and services. The most important defining criterion is the market-orientation of the enterprises. This set of enterprises includes all market-oriented companies that are financed through the market, liable to pay turnover taxes or simply all those that want to earn money with art, culture and creativity.” (Söndermann, Backes, Arndt et al. 2009, p. 20) Lastly we take an industrial and innovation systems perspective to these industries. Inspired by the work of Michael Porter (Porter 1990) we include not just core creative or cultural talent but also broader supporting and related industries that are essential to the commercialization of creative and cultural products. For example in our definition the competitiveness of the book industry is not just defined by the creative talent of the author but also by the printers, accountants, publishers and specialist book shops involved in a book‟s value chain. Since this report is focused on clusters and competitiveness in the creative and cultural industries we use an industrial systems approach and do not only concentrate on the act of creation itself. Statistical definition For the purposes of this Cluster Observatory report we have developed a new statistical definition of creative and cultural industries. As discussed above this new reflects both the creative industries idea as well cultural industries ideas. Our original intention was not to develop a new definition or add to the long list of available alternative methodologies. Our original intention was to use one of the existing approaches and apply it to the data and regions the Cluster Observatory includes. However, it became apparent that none of the available methodologies was suitable for use with cross-national comparative data. Using an off-the-shelf definition originally designed for specific national contexts may give unreliable results when used for all European countries. Additionally there are transparency issues with certain definitions meaning that we could not fully verify and replicate their methodologies. 3 In developing a new statistical definition our ambition has not been to reinvent the wheel but rather to develop a statistically operational definition that builds on the work and ideas of existing definitions whilst erring on the side of caution and not attempting to include everything. Considerable work has gone into finding a definition of the creative and cultural industries that is statistically operational at a pan-European level. Existing definitions are seldom appropriate to cross national or comparative levels of analysis since they tend to utilize more specific national statistical measures and contexts. Thus the primary definition used in the report is one developed by the authors for the purposes of cross-national comparison, with a specific view to analysis at NUTS2 regional levels using four digit level standard industrial classifications. The definition was informed by our conceptual understanding of the cultural and creative industries (see above). Moreover the definition attempts to incorporate common elements of other prominent definitions. This means that the definition builds upon comparison of the statistical categories used in a number of prominent international measures for creative, content and cultural industries. The operational definition we developed was - largely due to data collection issues - based on standard industrial classifications: in particular the standard industrial Classification of Economic Activities in the European Community NACE Revision 1.1. It is essential note that we use NACE Revision 1.1 only in this report due to the time series of the data we aimed to treat. NACE coding has been revised since and the new revision includes new codes and classifications that allow for much more accurate definition of creative and cultural industries: codes that will be used in future analyses. In the statistical definition used for this report we started out by only including those codes that several other definitions included: i.e. NACE Rev.1.1 and equivalent codes that several other definitions use. In other words we tried to find a minimal commonly held definition that reflected available definitions whilst remaining true to the concept of creative and cultural industries we hold. The other statistical definitions and code classifications we primarily used and compared in designing our own operational definition were:   Department Culture Media and Sport [UK] (1998). Creative industries mapping document. London, DCMS. Department for Culture, Media and Sport and Department of Environment Transport and Regions, [UK] (2000). Creative Industries: the regional dimension. The report of the Regional   Issues Working Group. London, DCMS. Department Culture Media and Sport [UK] (2009). Creative Industries Economic Estimates Statistical Bulletin January 2009. London, DCMS. European Commission Directorate-General for Education and Culture (2006). The Economy of Culture in Europe. Report prepared by KEA European Affairs, Media Group - Turku School of  Economic and Business Administration, MKW Wirtschaftsforschung GMbH. Brussels. Frontier Economics (2007). Creative industry performance. A statistical analysis for the DCMS. London, Frontier Economics Ltd. 4  Geppert, J. and P. Geppert (2008). La Valeur Economique de la Culture dans la Province du Limbourg et ses Régions Voisines - Rapport 2008. Maastricht, MKW Wirtschaftsforschung  GmbH, Sarrebruck comissioned by Gouvernement de la Province du Limbourg (Pays-Bas). Heng, T., A. Choo, T. Ho (2003). Economic Contributions of Singapore’s Creative Industries. Economic Survey Of Singapore First Quarter 2003. Singapore, Creative Industries Strategy Group Ministry of Information, Communications and the Arts, Economics Division Ministry of  Trade and Industry. Myndigheten för tillväxtpolitiska utvärderingar och analyser [Swedish Agency for Growth Policy Evaluations and Analyses] (2009). Kulturnäringar i svensk statistik Dnr 2009/054. Östersund,  Myndigheten för tillväxtpolitiska utvärderingar och analyser. Ministry of Culture and Communication [France] (2008). Expert Report on Sources - The Collection of Cultural Statistics in Europe. Call for tenders 2006/S 143-153056 – Contract n° 34100 2006 Power, D. (2002). ""Cultural industries" in Sweden: An assessment of their place  in the Swedish economy." Economic Geography 78(2): 103-127. National Office for the Information Economy and Department of Communications Information Technology and the Arts [Australia] (2002). Creative Industries Cluster Study - Stage One  Report. Canberra. Power, D. (2003). "The Nordic 'Cultural Industries': a cross-national assessment of the place of the cultural industries in Denmark, Finland, Norway and Sweden." Geografiska Annaler B   85(3): 167-180. Pratt, A. (1997). "The cultural industries production system: a case study of employment change in Britain 1984-91." Environment and Planning A 29: 1953-1974. Söndermann, M., C. Backes, O. Arndt and D. Brünink (2009). Culture and Creative Industries in Germany - Research Report. Initiative Culture and Creative Industries of the German Federal Government. Cologne, Bremen, Berlin, Federal Ministry of Economics and  Technology and Federal Government Commissioner for Culture and the Media. Söndermann, M., C. Backes, O. Arndt and D. Brünink (2009). Final Report: Culture and Creative Industries in Germany Defining the Common Characteristics of the Heterogeneous Core Branches of the "Cultural Industries" from a Macro-economic Perspective. Cologne,   Bremen, Berlin, Bundesministerium für Wirtschaft und Technologie. UNESCO Institute for Statistics (2008). The 2009 UNESCO Framework For Cultural Statistics: Draft. Montreal, UNESCO Institute for Statistics. WIPO (2003). Guide on Surveying the Economic Contribution of the Copyright-Based Industries. Geneva, World Intellectual Property Organisation. A pilot statistical definition was developed and all the measures and operations presented in this report were produced in preliminary form using the pilot definition. The preliminary results and methodology were presented at the expert workshop entitled “Towards a Pan-European initiative in support of innovative creative industries in Europe” organized by the European Commission‟s Enterprise and Industry Directorate General in cooperation with the City of Amsterdam, the European 5 Design Centre, the Association of Dutch Designers and IIP Create in Amsterdam, 4–5 February 2010. Detailed was obtained during the workshop from prominent European experts in the field. In addition to the workshop a small working group gave very detailed feedback on the statistical methodology, they included:   Hasan Bakshi, National Endowment for Science, Technology and the Arts (NESTA), London  Maya Jolles, DG ENTR.B4 - Economic Analysis and Evaluation    Rahel Falk, WIFO – Austrian Institute for Economic Research, Vienna Mette Koefoed Quinn, DG ENTR.D2 - Support for Innovation Carsten Schierenbeck, DG ENTR.D2 - Support for Innovation Michael Söndermann, Office of Cultural Industries Research, Cologne The valuable feedback and recommendations from this group and workshop resulted in direct changes to our methodology. It is important to note that whilst in theory we would like to have developed a definition that included all stages of the value and commodity chains that characterize these industries we have opted to largely exclude retail and related manufacturing activities. Statistics based on NACE Rev.1.1 are not sufficiently disaggregated to distinguish, for instance, cultural industries retail outlets from other types of retail, or to separate the related manufacturing processes behind fashion clothing from the general clothing and textile industries. In our selection of codes we have erred on the side of caution and minimalism. In particular we have not included a number of codes that other definitions include a proportion or part of. Whilst many of these codes include firms that are undoubtedly central to the creative and cultural industries it is difficult to use them accurately for cross-national comparison. For example we did not include code 74.20 (Architectural and engineering activities and related technical consultancy). We agree that architecture as a service industry is undoubtedly a core part of the creative and cultural industries but the code in this revision of NACE covers architecture as well as a wide variety of engineering and construction industry firms. Some studies that have used this code have only used a proportion of those firms involved – for instance, the UK DCMS studies included only 16.1% of firms registered under code 74.20. However, it is extremely problematic to suggest that the same percentage applies in all 30 countries in our study: in some countries it may be substantially more or less. In order to avoid inaccuracies we have excluded a number of codes that are commonly included on a proportional basis even though many reports have suggested as being core to definitions:  17.7 Manufacture of knitted and crocheted articles  18.1 Manufacture of leather clothes 18.10 Manufacture of leather clothes  18.2 Manufacture of other wearing apparel and accessories 18.22 Manufacture of other outerwear   6   18.23 Manufacture of underwear 18.24 Manufacture of other wearing apparel and accessories n.e.c.  18.30 Dressing and dyeing of fur; manufacture of articles of fur 19.30 Manufacture of footwear  74.87 Other business activities n.e.c. 52.48 Other retail sale in specialized stores  52.50 Retail sale of second-hand goods in stores 71.40 Renting of personal and household goods n.e.c.  74.20 Architectural and engineering activities and related technical consultancy 92.72 Other recreational activities n.e.c.     The exclusion of the above codes means in particular that the fashion industry is significantly underrepresented in our study; despite the fact that fashion industry‟s competitive advantage rests upon products defined by their creative and cultural content. In order to ground our definition and to show how important the exact definition used can be we also prepared figures for two other definitions that have attracted considerable attention in the field. The first of these was developed for the European Commission (Directorate-General for Education and Culture) 2006 report „The Cultural Economy of Europe‟ (CEOE); the authors of that report were KEA European Affairs, Media Group - Turku School of Economic and Business Administration, and MKW Wirtschaftsforschung GMbH. The NACE codes used for the „Cultural Economy of Europe‟ (CEOE) definition are from pages 308-311 of that report. The other definition we use is that developed by the World Intellectual Property Organization (WIPO 2003). In particular we used the coding and definition contained in “ANNEX III European Classification Codes, Corresponding to some of the Copyright-Based Industries” (p. 91). This sets out the NACE Rev.1.1 codes which WIPO suggests best approximates what they call „core and interdependent copyright industries‟:   Press and literature  Motion picture and video  Photography  Visual and graphic arts     Music, theatrical productions, operas Radio and television Software and databases Advertising services Copyright collective management societies The following table shows the NACE Rev.1.1 codes used in each definition and used in our analysis. The codes we have used in this report are labeled „CCI‟. 7 Code Description CCI 17.1 Preparation and spinning of textile fibres 17.11 Preparation and spinning of cotton-type fibres 17.12 Preparation and spinning of woollen-type fibres 17.13 Preparation and spinning of worsted-type fibres 17.14 Preparation and spinning of flax-type fibres 17.15 Throwing and preparation of silk, including from noils, and throwing and texturing of synthetic or artificial filament yarns 17.16 Manufacture of sewing threads 17.17 Preparation and spinning of other textile fibres 17.2 Textile weaving 17.21 Cotton-type weaving 17.22 Woollen-type weaving 17.23 Worsted-type weaving 17.24 Silk-type weaving 17.25 Other textile weaving 17.3 Finishing of textiles 17.30 Finishing of textiles 17.4 Manufacture of made-up textile articles, except apparel 17.40 Manufacture of made-up textile articles, except apparel 17.5 Manufacture of other textiles 17.51 Manufacture of carpets and rugs 17.52 Manufacture of cordage, rope, twine and netting 17.53 Manufacture of non-wovens and articles made from non-wovens, except apparel 17.54 Manufacture of other textiles n.e.c. 17.6 Manufacture of knitted and crocheted fabrics 17.60 Manufacture of knitted and crocheted fabrics 17.7 Manufacture of knitted and crocheted articles 17.71 Manufacture of knitted and crocheted hosiery 17.72 Manufacture of knitted and crocheted pullovers, cardigans and similar articles 18.1 Manufacture of leather clothes 18.10 Manufacture of leather clothes 18.2 Manufacture of other wearing apparel and accessories 18.21 Manufacture of workwear 18.22 Manufacture of other outerwear 18.23 Manufacture of underwear 18.24 Manufacture of other wearing apparel and accessories n.e.c. 18.3 Dressing and dyeing of fur; manufacture of articles of fur 18.30 Dressing and dyeing of fur; manufacture of articles of fur 19.3 Manufacture of footwear 19.30 Manufacture of footwear 22.11 Publishing of books 22.12 Publishing of newspapers 22.13 Publishing of journals and periodicals 22.14 Publishing of sound recordings 22.15 Other publishing CEOE  WIPO                                           8            22.21 Printing of newspapers 22.22 Printing n.e.c. 22.23 Bookbinding 22.24 Pre-press activities 22.25 Ancillary activities related to printing 22.31 Reproduction of sound recording 22.32 Reproduction of video recording 22.33 Reproduction of computer media 24.65 Manufacture of prepared unrecorded media 26.24 Manufacture of other technical ceramic products 30.02 Manufacture of computers and other information processing equipment 32.30 Manufacture of television and radio receivers, sound or video recording or reproducing apparatus and associated goods 33.20 Manufacture of instruments and appliances for measuring, checking, testing, navigating and other purposes, except industrial process control equipment 36.30 Manufacture of musical instruments 51.16 Agents involved in the sale of textiles, clothing, footwear and leather goods 51.41 Wholesale of textiles 51.42 Wholesale of clothing and footwear 51.47 Wholesale of other household goods 52.12 Other retail sale in non-specialized stores 52.47 Retail sale of books, newspapers and stationery 52.48 Other retail sale in specialized stores 52.61 Retail sale via mail order houses 64.20 Telecommunications 70.20 Letting of own property 71.40 Renting of personal and household goods n.e.c. 72.21 Publishing of software 72.22 Other software consultancy and supply 72.3 Data processing 72.40 Database activities 74.20 Architectural consultancy 74.40 Advertising 74.81 Photographic activities 74.87 Other business activities n.e.c. 92.11 Motion picture and video production 92.12 Motion picture and video distribution 92.13 Motion picture projection 92.20 Radio and television activities 92.31 Artistic and literary creation and interpretation 92.32 Operation of arts facilities 92.33 Fair and amusement park activities 92.34 Other entertainment activities n.e.c. 92.40 News agency activities 92.51 Library and archives activities 92.52 Museums activities and preservation of historical sites and buildings 93.05 Other service activities n.e.c.   and  engineering                                  activities   and related    technical                               9            The importance of definitions can be seen in the Table below which shows how employment figures and focus measures for Europe look for each definition. CCI Europe CEOE unfiltered WIPO Employment Focus Employment Focus Employment Focus 6,576,558 2.71% 17,921,109 7.56% 6,805,181 2.87% The figure of nearly 18 million employees the CEOE definition generates is in stark contrast to the figure of 5.8 million employees in 2003 the CEOE report presented. The figures presented in the CEOE report were based on NACE codes but data was heavily filtered using supplementary business register data. Thus it is important to understand that: different operationalizations of similar conceptual terms can generate very different figures; the methods by which data is treated and filtered have crucial implications. For these reasons we have chosen to err on the side of caution with the operational definition used in this report and avoid the inclusion of codes where significant levels of proportional and supplementary data filtering is needed. Data The data used for this report came from The European Cluster Observatory Cluster Mapping Database. The Cluster Mapping database is built in the intersection of regions and sectors in Europe. By combining the two dimensions of geography and industry it is possible to statistically trace regional agglomerations of employment, defined as statistical regional clusters, across Europe. The geographical dimension is operationalised through 259 regions, predominantly NUTS 2 regions, which the EU has uses to subdivide member countries for statistical purposes. We use NUTS 1 regions for Belgium, Greece, Netherlands and Turkey so that the size of the regions both in terms of land area and employment are reasonably comparable. NUTS 1 is also used for Ireland due to data availability. On the sectoral side employment data on the 4-digit industry level (and in a few cases 3-digit data) is used. Unfortunately, no comparable data exists for wages, value added, or productivity at the level of regions and detailed industries. Instead we have used Regional Innovation Statistics (not separated by cluster category) to differentiate between regional clusters in high innovation environments from clusters in low innovation environments. Added to this, we have used national export data classified by cluster category (not separated by region) to separate out regional clusters in high export national environments from clusters in low export national environments. It is important to note that the employment data used in the report is exactly that: data on employees. The resulting numbers do not therefore include sole-traders or freelancers who are not also full-time 10 employed. Given that there are extremely high rates of sole trader activity the numbers underrepresent the true numbers of people actively working in creative and cultural industries. However, concentrating on employees (rather than all „workers‟) is important since firms‟ taking on employees is central to the spread of economic growth and knowledge. The data used was collected between December 2006 and June 2007. Each data point is coded by the “batch number” for traceability (e.g. to determine the name of the person who supplied the data, contact information and date of transfer) and “source code” for methodological purposes (data collection methodology, measurements explanations, reference period, etc). The following table lists the sources for the data used in this report: Country Institution Method NACE Level Austria Eurostat, Luxembourg Labour Force Survey 3 Austria Statistics Austria Structural Business Survey 4 Belgium National Office of Social Security, Belgium Business survey 4 Bulgaria National Statistical Institute, Bulgaria Enterprise survey 4 Croatia Eurostat, Luxembourg Labour Force Survey 3 Cyprus Statistical Service of Cyprus Business Register Survey 3 Czech Republic Eurostat, Luxembourg Labour Force Survey Denmark Statistics Denmark Register-based statistics Estonia Eurostat, Luxembourg Labour Force Survey 3 Estonia Eurostat, Luxembourg Structural Business Statistics 4 Finland Statistic Finland Labour Force Survey 4 France INSEE, France DADS 4 Germany Statistik der Bundesagentur fur Arbeit, Germany Employment statistics 4 Greece National Statistical Service of Greece Labour Force Survey 3 Hungary Eurostat, Luxembourg Labour Force Survey 3 Iceland Statistics Iceland Pay As You Earn register 4 Ireland Central Statistics Office, Ireland Quarterly National Survey 2 Ireland Eurostat, Luxembourg Structural Business Statistics Italy Eurostat, Luxembourg Labour Force Survey Latvia Central Statistical Bureau of Latvia Survey of institutions Lithuania Statistics Lithuania Structural Business Survey 4 Luxembourg Eurostat, Luxembourg Labour Force Survey 3 Malta Eurostat, Luxembourg Labour Force Survey 3 Netherlands Eurostat, Luxembourg Labour Force Survey 3 Norway Statistics Norway Structural Business Statistics 4 Poland Central Statistical Office of Poland Form Z6 4 Portugal Statistics Portugal Integrated system Romania Eurostat, Luxembourg Labour Force Survey 3 Slovakia Eurostat, Luxembourg Labour Force Survey 3 Slovenia Statistical Office of Slovenia Enterprise survey 4 Spain Eurostat, Luxembourg Labour Force Survey 3 11 3 labour force Household 4 3 enterprises business 4 and accounts 4 4 Sweden Statistiska Centralbyran, Sweden Register-based Labour Market Statistics 4 Switzlerland Swiss Statistics Census of Swiss enterprises 4 Turkey Turkish Statistical Institute General Census of Industry and Business Establishments 4 United Kingdom Department of Enterprise, Trade and Innovation of Northern Ireland Census of Employment 4 United Kingdom Office for National Statistics of United Kingdom Annual Business Inquiry 4 EU employment data is collected from two different sources: from the Labour Force Survey (LFS) and from the Structural Business Statistics (SBS), both administrated by Eurostat. LFS is a quarterly survey given to a sample of the population living in private households. The LFS includes data on at most 3-digit NACE level for most, but not all, NUTS 2 regions. SBS statistics is mainly sourced from business registers and includes structural data over the economy. On NUTS 2 regional level Eurostat only administers data on NACE 2 digit level. 4 digit level data are collected on national level, but not for all NACE categories. The 4 digit level is in turn available for NUTS 1 regions (countries) but not for NUTS 2 regions. In many cases more detailed data has been obtained from National Statistical Offices, but Eurostat still remains the main source for Italy, Spain, Czech Republic and Romania. In the countries where more than one source was used (Austria, Estonia and Ireland), the different sources were used only for different sections of the NACE classification, i.e. a code from one classification could not have a parent from another. This was done to combine the data from Structural Business Statistics, which is available on NACE 4-digit level, with 3-digit data from Labour Force Survey for the sections not covered in SBS (e.g. agriculture, public sector, education). There also are two sources in the United Kingdom because Northern Ireland has a separate statistical office. Due to heterogeneity of the data a number of steps were required to harmonize the data to the level where it can be matched with cluster definitions. The main portion of this process was bringing the whole dataset to NACE 4-digit level by splitting the data from higher levels of aggregation when not available. It is important to note that despite every effort being made to ensure accuracy, time series data is not fully reliable for every region. This is mainly due to changes to collection methodologies during the time series but also to artifacts from the processing of data in countries where only 3-digit data was available. Industry splitting algorithm The data were processed on the same regional division level as they were reported, which corresponds to NUTS 2 regions for all countries except for Ireland, where the data were only available for Ireland as a whole (Ireland is composed of two NUTS 2 regions). Initial processing was also done only for the years for which the data were reported. 12 The algorithm used for data harmonization works in the following way: 1. The script checks for availability of employment data for each combination of year, region and NACE 4-digit industry (for years/regions where at least some data was available). 2. If the data is present, it moves to the next combination. 3. If the data cell is blank, it searches for all the parent industries of the one that is missing until it finds a value. If all the parent industries are missing, the cell is left blank. 4. When a value is found, the script goes on to determine all the children (and sub-children) of the parent industry that are at the cluster definition level (i.e. NACE 4-digit) and have no intermediate industries that are available. The script than calculates the sum of all the cells that are already available within the given parent, deducts this sum from the value of the parent cell and then splits the result equally between the children determined previously. This method helped us not only to transform the data that we had only on NACE 3-digit level but also allowed us to use the data on multiple levels for the same country. This was particularly valuable with countries like United Kingdom that provides data on all NACE levels but the less aggregated the data is the more values are withheld due to confidentiality. There are certainly drawbacks to this method. One drawback lies in the fact that the splits are done equally among all the target industries. However, in most of the cases the split is close to reality, especially in the countries with NACE 4-digit coverage where normally only very small values are withheld (e.g. when less than ten people are employed in the industry). Some clusters, especially small ones that are composed of NACE 4-digit industries from different sections, are more prone to errors than the others. Regional Units and Aggregation Geographic regional data is used in the report and is reliant on geographical units defined according to the NUTS system, a nomenclature of territorial units for statistics. As a hierarchical classification, the NUTS system subdivides each EU member country into NUTS 1 regions, each of which is in turn subdivided into NUTS 2 regions. The EU has been divided into a total of 254 NUTS 2 regions. The different criteria used for subdividing national territory into regions are normally split by normative and analytical criteria. Normative regions are the expression of a political will: their limits are fixed according to the tasks allocated to the territorial communities, according to the sizes of population necessary to carry out these tasks efficiently and economically, and according to historical, cultural and other factors. Analytical (or functional) regions are defined according to analytical requirements; they group together zones using geographical criteria (e.g., altitude or type of soil) or using socioeconomic criteria (e.g., homogeneity, complementarity or polarity of regional economies). 13 NUTS2 regions have been used throughout the study. In certain cases it was necessary to make regional aggregations. This table depicts the way in which aggregations have been made in certain cases and the reasons for aggregation in each particular case. Original Region Original Region Name Modified Region Modified Region Name Belgium - Aggregated to NUTS1 due to very small land area of NUTS2 regions NUTS-BE10 Brussels NUTS-BE1 Brussels NUTS-BE21 Prov. Antwerpen NUTS-BE2 Vlaams Gewest NUTS-BE22 Prov. Limburg (B) NUTS-BE2 Vlaams Gewest NUTS-BE23 Prov. Oost-Vlaanderen NUTS-BE2 Vlaams Gewest NUTS-BE24 Prov. Vlaams-Brabant NUTS-BE2 Vlaams Gewest NUTS-BE25 Prov. West-Vlaanderen NUTS-BE2 Vlaams Gewest NUTS-BE31 Prov. Brabant Wallon NUTS-BE3 Région Wallonne NUTS-BE32 Prov. Hainaut NUTS-BE3 Région Wallonne NUTS-BE33 Prov. Liège NUTS-BE3 Région Wallonne NUTS-BE34 Prov. Luxembourg (B) NUTS-BE3 Région Wallonne NUTS-BE35 Prov. Namur NUTS-BE3 Région Wallonne Germany - NUTS2 codes changes in 2004 NUTS-DE40 Brandenburg NUTS-DE4 Brandenburg NUTS-DE41 Brandenburg - Nordost NUTS-DE4 Brandenburg NUTS-DE42 Brandenburg - Südwest NUTS-DE4 Brandenburg Spain - African territories merged with the mainland NUTS-ES63 Ciudad Autónoma de Ceuta NUTS-ES61 Andalucía NUTS-ES64 Ciudad Autónoma de Melilla NUTS-ES61 Andalucía NUTS-FI18 Etelä-Suomi Finland - Minor islands merged with the mainland NUTS-FI20 Åland France - Overseas possessions removed NUTS-FR91 Guadeloupe NUTS-FR92 Martinique NUTS-FR93 Guyane NUTS-FR94 Réunion Greece - Aggregated to NUTS1 due to very small population of NUTS2 regions NUTS-GR11 Anatoliki Makedonia, Thraki NUTS-GR1 Voreia Ellada NUTS-GR12 Kentriki Makedonia NUTS-GR1 Voreia Ellada NUTS-GR13 Dytiki Makedonia NUTS-GR1 Voreia Ellada NUTS-GR14 Thessalia NUTS-GR1 Voreia Ellada NUTS-GR21 Ipeiros NUTS-GR2 Kentriki Ellada NUTS-GR22 Ionia Nisia NUTS-GR2 Kentriki Ellada NUTS-GR23 Dytiki Ellada NUTS-GR2 Kentriki Ellada NUTS-GR24 Sterea Ellada NUTS-GR2 Kentriki Ellada NUTS-GR25 Peloponnisos NUTS-GR2 Kentriki Ellada NUTS-GR30 Attiki NUTS-GR3 Attiki NUTS-GR41 Voreio Aigaio NUTS-GR4 Nisia Aigaiou, Kriti NUTS-GR42 Notio Aigaio NUTS-GR4 Nisia Aigaiou, Kriti NUTS-GR43 Kriti NUTS-GR4 Nisia Aigaiou, Kriti Ireland - Aggregated to NUTS1 due to unavailability of data for NUTS2 NUTS-IE01 Border, Midland and Western NUTS-IE0 Ireland NUTS-IE02 Southern and Eastern NUTS-IE0 Ireland 14 References Caves, R. (2000). Creative Industries: contracts between art and commerce. Cambridge, Mass., Harvard University Press. Fleming, T. (2007). A Creative Economy Green Paper for the Nordic Region. Oslo, Nordic Innovation Centre. Galloway, S. and S. Dunlop (2007). "A critique of definitions of the cultural and creative industries in public policy." International Journal of Cultural Policy 13(1): 17 - 31. Hesmondhalgh, D. (2002). The Cultural Industries. London, Sage. Jeffcutt, P. and A. Pratt, Eds. (2009). Creativity and Innovation in the Cultural Economy. London, Routledge. Kolmodin, A., A. Pelli, L. Bager-Sjögren, F. Junkka, M. Lindberg, K. Hovlin and A. Karlsson (2008). Kreativ tillväxt? - En rapport om kreativa näringar i politik och statisik (Creative growth? A report on creative industries in policy and statistics). Stockholm, ITPS - Institutet för tillväxtpolitiska studier. Mato, D. (2009). "All industries are cultural." Cultural Studies 23(1): 70 - 87. Miller, T. (2009). "From Creative to Cultural Industries." Cultural Studies 23(1): 88 - 99. Nielsen, T. (2008). The Eriba Model: An effective and successful policy framework for the creative industries. Stockholm, KK-Stiftelsen. Porter, M. (1990). The Competitive Advantage of Nations. New York, The Free Press. Power, D. (2002). ""Cultural industries" in Sweden: An assessment of their place in the Swedish economy." Economic Geography 78(2): 103-127. Power, D. (2009). "Culture, creativity and experience in Nordic and Scandinavian cultural policy." International Journal of Cultural Policy 15(4): 445 - 460. Power, D. and A. Scott (2004). Cultural Industries and the Production of Culture. London, Routledge. Pratt, A. (2005). "Cultural industries and public policy: An oxymoron?" International Journal of Cultural Policy 11(1): 31-44. Scott, A. (2000). The Cultural Economy of Cities: essays on the geography of image-producing industries. London, Sage. Söndermann, M., C. Backes, O. Arndt and D. Brünink (2009). Final Report: Culture and Creative Industries in Germany Defining the Common Characteristics of the Heterogeneous Core Branches of the "Cultural Industries" from a Macro-economic Perspective. Cologne, Bremen, Berlin, Bundesministerium für Wirtschaft und Technologie. WIPO (2003). Guide on Surveying the Economic Contribution of the Copyright-Based Industries. Geneva, World Intellectual Property Organisation. 15 About the European Cluster Observatory The European Cluster Observatory, launched in June 2007, is the most comprehensive database on clusters, cluster organisations, and cluster reports in Europe. It is managed by the Center for Strategy and Competitiveness (CSC) at the Stockholm School of Economics and funded by the European Commission's Directorate General for Enterprise and Industry. The European Cluster Observatory website provides a wide variety of data on clusters in Europe, and is focused on the following issues:  Cluster Mapping providing information on 38 cluster categories in 259 NUTS II regions  Information, maps and lists of regional or local private-public partnerships focused on cluster improvements  Providing reports on national and regional cluster policies and programmes;  Providing detailed knowledge thorough publishing Observatory reports, cluster case studies and other cluster-related documents In 2009, the Observatory entered the second phase of development bringing new features and introducing a collaboration platform for cluster organisations and SMEs. Please visit the European Cluster Observatory at www.clusterobservatory.eu. 16