EU sectoral competitiveness indicators

EU sectoral competitiveness indicators

EU sectoral competitiveness indicators A pocketbook prepared by the Enterprise and Industry Directorate-General Unit B2 Competitiveness and economic reforms European Commission

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Chapter I: Introduction... 5 Chapter II: Summary of the chapters of the pocketbook... 9 II.1. Introduction... 9 II.2. Industrial structure... 10 II.3. Industrial interrelations... 11 II.4. Growth and productivity... 12 II.5. External trade performance... 13 Chapter III: Sectoral structure... 15 III.1. Introduction... 15 III.2. Distribution of value added and employment: sectors and labour skills... 15 III.3. Economic activity by size of enterprises... 16 III.4. Capital intensity... 20 III.5. Specialisation of countries... 22 III.6. Concluding remarks... 25 III.7. Annexes... 26 Chapter IV: Industrial interrelations and competitiveness: An input-output approach... 33 IV.1. Introduction... 33 IV.2. The structure of the economy: a six-branch input-output table... 34 IV.3. The role of ICT in the production process... 48 IV.4. Human capital: labour skills-based input-output tables... 56 IV.5. Other input-output indicators... 63 IV.6. Concluding remarks... 76 IV.7. Annex... 77 EU sectoral competitiveness indicators 3 Contents

EU sectoral competitiveness indicators 4 Chapter V: Growth and productivity... 79 V.1. Introduction... 79 V.2. Growth and labour productivity in EU-15... 79 V.3. Growth and labour productivity: a disaggregated perspective... 83 V.4. Profitability... 92 V.5. Concluding remarks... 99 V.6. Annexes... 100 Chapter VI: External trade... 105 VI.1. Introduction... 105 VI.2. World trade structure... 105 VI.3. EU-15 sectoral performance and revealed comparative advantage... 107 VI.4. Intra-industry trade (IIT)... 112 VI.5. Labour skills and technology... 117 VI.6. Concluding remarks... 125 VI.7. Annexes... 128

EU sectoral competitiveness indicators 5 Chapter I: Introduction The production of EU sectoral competitiveness indicators is a response to the increasing interest in analysing the competitiveness of the EU economy from a sectoral perspective. This approach provides insight into the performance of each industry and contributes to explaining the competitiveness of the EU economy at large. The purpose of this publication is largely pedagogical. One objective is to present in a single publication, data and indicators that can be easily accessible and sufficiently comprehensive to provide answers albeit, in some cases, incomplete to questions about the factors that impinge upon various aspects of the performance of the EU industries. Better knowledge of the underlying data and of the fundamental economic relationships should, one hopes, provide the grounds for better policies. The choice of indicators and industries is the result of a selection constrained principally by data availability. A pocketbook should in fact be selective and the list of indicators ought to be parsimonious. Clearly, there is a large number of indicators that can, in principle, be developed to characterise the performance of each industry and such an approach is indeed followed in other publications ( 1 ). What distinguishes this pocketbook is the selection of the indicators, based in part on recent empirical work, and their relation to sectoral competitiveness. The indicators are defined over variables that reflect or determine sectoral competitiveness. Inevitably, comparisons with the United States are made across industry variables to provide a benchmark of the industrial performance of the EU. This pocketbook covers virtually all principal indicators that can be developed across EU industries at the level of the sectoral classification chosen. The time span of the series used depends upon data availability. Given the interest of observing growth and competitiveness developments in the long term, this publication covers the longest periods of time available for the indicators and sources used. The geographic coverage is limited, and the information refers to EU-15 or to individual Member States and the United States, notwithstanding the limitations imposed by this choice. Information on country performance on the basis of some of the indicators used in this publication can be found in O Mahony and van Ark (2003) ( 2 ). ( 1 ) industry perspective. Can Europe resume the catching-up process?, Enterprise Publications, European Commission, Luxembourg, Office for Official Publications of the See Eurostat (2003), European business: facts and figures, Luxembourg. ( 2 ) See Mary O Mahony and Bart van Ark (2003), EU productivity and competitiveness: An European Communities.

EU sectoral competitiveness indicators 6 The indicators presented concern key dimensions of industrial performance and the relevant characteristics. Some indicators convey information pertinent to aspects intrinsic to industrial performance and competitiveness. This is, for example, the case of labour productivity, and unit labour costs. Other indicators show how industries are performing in their market activities, as for example, measures of performance in international trade or indicators of revealed comparative advantage. The pocketbook, in addition to this introduction, is organised over the following chapters. Chapter II presents a summary and the main conclusions. Chapter III presents information on the industrial structure of the EU. It is worth mentioning two of the indicators presented in this chapter: first, an index of industrial specialisation which reveals comparative advantage of countries, localisation factors and the policy choices, if any, that may have determined the particular intensive presence (or absence) of an industry in a given Member State. Furthermore, the index encompasses the possible impact in each country of policy measures adopted at EU level as well as the strengths and weaknesses of countries depending upon the characteristics of the industries in which they are specialised (e.g. sensitivity to business cycles, labour intensity). The second indicator worth mentioning is the distribution of value added by size classes, an indicator about the organisation of the industry which in turn is influenced by technological and economic forces. Despite some methodological limitations ( 3 ), this distribution provides insight into the possible presence and importance of economies of scale. Chapter IV presents indicators derived from input-output tables. Modern economies are characterised by complex interrelations between industries that need to be taken into consideration in formulating policy measures. The complexity of industrial interrelations increases with the level of industrialisation, and the development of new activities and products. Of particular relevance is the interrelationship between the manufacturing and the services sectors. The concerns about the declining share of manufacturing in value added and the increasing share of services can be understood better through the use of input-output relationships. The indicators provide a picture of the industrial structure that goes beyond the consideration of each industry separately. Chapter V presents data measuring industrial growth. Growth of value added in constant prices provides information related to industrial dynamism, degree of industrial maturity, speed of structural change and direction, and competitiveness. Although competitiveness is a multidimensional concept, productivity plays a crucial role in determining competitiveness: in this chapter growth rates of labour productivity per hour worked are presented. To characterise sectoral growth, a cluster analysis of sectors is presented, which groups sectors according to their performance in output, employment and labour productivity. The last indicator in this chapter is gross operating rate. ( 3 ) Related basically to the fact that the distribution is based on enterprises, rather than more homogeneous units such as establishments or kind-of-activity units.

Chapter VI is devoted to measuring EU industrial performance in external trade. Industrial competitiveness is invariably associated with performance in international trade. Here, world trade matrices, product composition of trade, trade balances, indexes of revealed comparative advantage (RCA) and intra-industry trade across various groups of countries grouped according to their income per capita are some of the indicators chosen to measure the performance of EU industries in external trade. EU sectoral competitiveness indicators 7

Chapter II: Summary of the chapters of the pocketbook EU sectoral competitiveness indicators 9 II.1. Introduction There is increasing interest in analysing the competitiveness of the economy in general, and of EU-15, in particular, from a sectoral perspective, reflecting the notion that the competitiveness of the economy at large cannot be properly understood without looking into the performance of individual sectors, and, what is even more important, at how these interrelate. In analysing individual sectors separately, particular attention can be paid to industry-specific factors that characterise that sector in particular. The approach taken in this pocketbook is different. It is based on a set of indicators, which can be applied simultaneously to all sectors. This approach aims at identifying the performance of each sector, relative to the rest, and seeks to establish statistical regularities across sectors and Member States, and over time, which not only provide insight into the competitiveness of each sector separately but also of the economy as a whole. This should also lay the grounds for further economic and quantitative analysis of competitiveness-related facets. Clearly, limitations related to data availability especially at sectoral level dictate to a considerable extent the content and breadth of the pocketbook. The data have been drawn from various statistical sources. Eurostat s NewCronos database has provided very useful information on distribution of economic activity by size categories of enterprises, investment intensity and gross operating surplus. Input-output tables have been provided by Eurostat and are now available in the Eurostat s NewCronos database. Data on value added, employment and labour productivity long-term developments come from the study entitled EU productivity and competitiveness: An industry perspective edited by Mary O Mahony and Bart van Ark ( 4 ). Readers interested in details of the data used are referred to that publication, and more specifically to Chapter VII on methodology. Data on external trade are from Eurostat s Comext database and the United Nations Comtrade database. The indicators presented in this pocketbook concern key aspects of industrial performance. Some indicators convey especially pertinent information about aspects intrinsic to competitiveness: this is, for example, the case with labour productivity and unit labour costs. Other indicators show how industries are performing in their market activities, as for example, measures of performance in international trade or indicators of revealed comparative advantage. The indica- ( 4 ) See footnote 2.

EU sectoral competitiveness indicators 10 tors are grouped in four main chapters: industrial structure, industrial interrelations, growth and productivity, and external trade, and each of these chapters focuses on some selected issues. A brief summary of the material is presented below. II.2. Industrial structure The first group consists of indicators on the industrial structure of the EU. Two indicators are worth mentioning here. First, the index of industrial specialisation is an index that reveals comparative advantage of countries, localisation factors, and the policy choices, if any, that may have determined the intensive presence (or absence) of an industry in one specific Member State. In doing so it helps interpret the results obtained from other indicators, and particularly from those on external trade performance. Furthermore, the index points to the possible impact in each Member State of policy measures adopted at EU level, and the forces and weaknesses of Member States depending upon the characteristics of the industries in which they are specialised (e.g. sensitivity to business cycles, labour intensity). There is high variation in specialisation across EU-15 Member States, and some exhibit high degrees of specialisation in certain industries. In general, these are small or medium-sized countries, since there is obviously a country size effect in measuring specialisation ( 5 ). The most outstanding cases are those of Finland in telecommunication equipment and Ireland in office machinery. However, these are not unique cases. Denmark in water transport, Luxembourg in financial intermediation, and the Netherlands in radio and television receivers also fall into this category. Specialisation indexes are lower in big countries since country size tends to lower specialisation. But France in research and development, Italy in textiles, the United Kingdom in radio and television receivers and other instruments are some examples of the opposite effect. In Germany the highest indexes correspond to other electrical machinery and motor vehicles, but in general there is not a clear specialisation pattern in this country. A different perspective is provided by specialisation profiles in terms of various categories of labour skills. Member States can be placed in three groups. The first includes countries specialised in high labour skills sectors (Belgium, France, and Luxembourg) and high-intermediate labour skills (Denmark, Finland, Sweden, and to a lesser extent the United Kingdom); the second includes countries specialised in the two lowest categories of labour skills: Austria, Spain, Greece, Italy and Portugal. Finally, Germany, the Netherlands and Ireland belong to a group that does not have a clear profile of specialisation, which implies that the distribution of value added is very similar to the one of EU-15 as a whole. These results are based on all industries, and, therefore, incorporate the effect of both market and non-market services. The ( 5 ) The specialisation index compares the industry structure of one country with the one of EU-15. Since big countries determine largely the industry structure of EU-15, significant differences between big countries and the EU as a whole cannot be expected, at least to the extent as those for small and intermediate countries.

EU sectoral competitiveness indicators 11 data permit the singling out of the performance of the manufacturing sector. This is particularly relevant for the analysis of external trade. On this basis, a first group of countries exhibit a marked specialisation in high labour skills manufacturing sectors (Belgium, Finland, Ireland, the Netherlands, France and the United Kingdom). At the opposite end are countries such as Spain, Greece, Italy, Luxembourg, and Portugal characterised by specialisation in low labour skills activities. A third group is characterised by specialisation in low-intermediate labour skills. This group consists of Austria, Germany and Sweden. Denmark occupies an intermediate position since this country is specialised in both high and low-intermediate labour skills. Finland also occupies a situation similar to Denmark s although it has been included in the first group because its specialisation in high labour skills is much higher than the one on low-intermediate skills. Another aspect relevant for the analysis of sectoral performance and competitiveness is the organisation of the industry, more specifically the market organisation and the possible presence of economies of scale in the operation of various sectors. Data on the distribution of value added by size classes of the enterprises, despite some methodological limitations ( 6 ), are useful here. This indicator shows industries where the largest part of their activity is undertaken in large enterprises (with more than 1 000 persons employed). To the extent that these industries are characterised by economies of scale, they can benefit from international trade, since this gives access to larger markets, and opens the possibility for these industries to achieve lower average costs. Some of these manufacturing industries are tobacco, mineral oil refining, office machinery, telecommunications equipment, motor vehicles, and aircraft and spacecraft. Within services, concentration is high in air transport and communications. II.3. Industrial interrelations Modern economies are characterised by complex interrelations between industries and these must be considered in the analysis of competitiveness and in formulating policy measures. The complexity of industrial interrelations increases with the level of industrialisation, and the development of new activities and products. A group of indicators derived from input-output (IO) tables takes the description of industrial structure beyond the consideration of each industry separately. Four types of aggregated IO tables are used. First, a traditional aggregation to six branches shows, among other things, the relationship between manufacturing industry and market services. Secondly, an aggregation showing industrial interrelations between information and communication technologies (ICT) categories and the role of ICT in the production process is the basis for an ICT by ICT table. Thirdly, for the role of human capital, a labour skills by labour skills table has been created. Finally, an IO table of 42 ( 6 ) Due basically to the fact that the distribution is based on enterprises, rather than more homogeneous units, such as establishments or kind-of-activity units. In any case, the prevalence of high enterprises in an industry would indicate the influence of economies of scale in functions related to the activities of enterprises.

EU sectoral competitiveness indicators 12 branches provides indicators at the most detailed level. One purpose here is to highlight stylised facts and to underscore the role of ICT and of labour skills categories. Despite the high level of aggregation, especially in the sixbranch tables, the discussion has singled out some important characteristics that deserve attention in industrial policy reflections. First, supplier-user links, as captured by the intermediate transaction matrix of the IO table, are carriers of strengths and weaknesses, and therefore, promoters of, or obstacles to, the competitiveness of industries. The links between manufacturing industry and market services, and between various ICT and labour skills categories, can be seen as channels of transmission of, for example knowledge, innovation, product and services quality, and good (or bad) productivity performance. The data reveal clearly the importance of market services as suppliers of inputs to manufacturing industry. Secondly, backward linkages, present in all industries purchasing intermediate inputs from other industries, are channels of transmission of growth and shocks in a given sector to the rest and, more specifically, to those with which an industry is strongly linked. Industries in recession (expansion) transmit their growth performance to their suppliers. Thirdly, the data show the importance of external trade not only as a vehicle to satisfy consumer demand (imported goods and services to meet final demand), but also as a way to provide domestic branches with access to intermediate inputs. While the main part of the discussion has been carried out on the basis of the aggregated IO tables mentioned above, technical coefficients and output multipliers have been calculated at more disaggregated levels (42 branches), and are presented in Section IV.5. These two indicators provide two measures of the requirements, in a particular sector, of inputs from other branches of the economy. The first (technical coefficients) takes into account all inputs consumed in a given branch, regardless of their geographical origin (domestic or imported), and reflects the technology of sectors. The second (output multipliers), which takes into consideration inputs of domestic origin only, measures the total impact (both direct and indirect) of the demand for the products of one branch on the production of the rest of the branches of the economy, and therefore captures the effect of the expansion, or regression, of a given sector, on the rest of the economy. II.4. Growth and productivity Various indicators are used to illustrate growth and productivity of EU sectors. First, developments in value added in constant prices provide information related to industrial dynamism, the degree of industrial maturity, speed of structural change and direction, and competitiveness. Growth rates of the number of persons employed across industries provide a measure of the reallocation process of resources among sectors. Finally, although competitiveness is a multidimensional concept, labour productivity per hour worked is one crucial determinant.

EU sectoral competitiveness indicators 13 Secondly, labour productivity growth affects competitiveness indicators such as unit labour costs developments as well as developments in relative prices. Labour productivity growth in manufacturing improves its competitiveness in international markets and this superior productivity performance of manufacturing relative to market services has made possible a favourable evolution of the relative prices of manufacturing products. Supplying relatively cheaper intermediate goods is one of the ways through which productivity growth in manufacturing is transmitted to the rest of the economy. Thirdly, profitability is a key indicator of competitiveness and success. The gross operating rate indicator presented in this pocketbook shows substantial variation across sectors and over time, which reflect differences in market structure, technology, cyclical patterns and sector-specific shocks. As a way to summarise sectoral growth in the EU the results of a hierarchical cluster analysis of sectors are presented in Chapter V. Five sectoral growth clusters have been identified, which are characterised by their performance (low, intermediate, or high) in value added, employment and labour productivity growth in the period 1979 2001. indicators such as world trade matrices, product composition of trade, relative trade balances, indexes of revealed comparative advantage (RCA) and relative trade balance, an intra-industry trade (IIT) index (Grubel-Lloyd), and trade with countries classified by income level are used here. First, data are presented about the place of EU-15 in the world trade network (exports originating in EU-15 countries, including intra-eu-15 trade, account for 45.6 % of total world exports). Secondly, measures of revealed comparative advantage (RCA) of EU-15 industrial sectors are constructed. RCA measures show that the following six are top products in EU-15 trade performance: mechanical engineering, chemicals, non-metallic mineral products, aircraft and spacecraft, printing and publishing, and scientific instruments. And, also according to RCA measures, the following are at the bottom of the ranking: radio and television receivers, clothing, electronic valves and tubes, office machinery, wood and products of wood, railroad and other transport equipment, basic metals, and other instruments. The income level of trade partners plays an important role in determining trade patterns, particularly IIT. Indicators of IIT in EU-15 trade are constructed that measure IIT intensity by product and income levels of trade partners. II.5. External trade performance EU industrial performance in external trade constitutes conventionally understood competitiveness, or lack of. Various To characterise further EU-15 trade with the rest of the world, trade flows are also classified according to labour skills and technology categories. This is particularly important in trade between high-income countries, but it is also

EU sectoral competitiveness indicators 14 important for trade flows among countries of different levels of development. The degree of IIT is significant because its determinants (e.g. economies of scale and demand for variety) are different from those of inter-industry trade and, consequently, the policy conclusions also differ. Inter-industry trade with low-intermediate income countries can be identified as the segment of trade, and of the industry, for which the threat from international competition is highest. These flows correspond to trade explained by comparative advantage, such as low wage levels, which are clearly a characteristic of lowintermediate income countries. The data suggest that EU-15 trades primarily with high-income countries and it is mostly IIT. Trade with low-intermediate income countries accounts for a relatively small share of total trade, and while EU-15 trade with high-, upper-medium, and low-income countries corresponds to the general pattern that IIT is positively related to the level of income of the trade partners, the distinctive feature with respect to low-intermediate countries is the coexistence of IIT and inter-industry trade. In other words, these countries play a dual role: their trade is based on products embodying low labour skills but they also exchange with EU-15 other categories of more sophisticated products and technologies, based predominantly on standardised technology that permits product imitation.

EU sectoral competitiveness indicators 15 Chapter III: Sectoral structure III.1. Introduction This chapter describes the basic characteristics of the EU-15 sectoral structure. The indicators used are, first, the distribution of value added and employment by sector and labour skills; second, the distribution of value added by size of enterprises; third, an indicator of capital intensity; and fourth, an index of sectoral specialisation for each Member State. This information is pertinent for interpreting the indicators presented in the rest of the pocketbook. Another approach to sectoral structure based on input-output tables is discussed in Chapter IV. III.2. Distribution of value added and employment: sectors and labour skills The distribution of value added in EU-15 grouped according to main sectors of economic activity is presented in Graph III.1. As sustained productivity increases in each sector have made it possible to meet demand with less resources, these have been shifting from agriculture to manufacturing industry and from this to services activities. Agriculture, fishing and forestry account for 1.7 % of total value added, manufacturing industry for 21 % and market services for 48.1 %. For comparison, the share of manufacturing industry in the United States is 16 % of total value added and the share of market services 52 %. The reallocation of resources that has taken place over the long run is better reflected in the distribution of employment shown in Graph III.2. Market and non-market services account now for the dominant part of employment in the EU and in the United States. Graph III.3 presents the distribution of value added according to the labour skills taxonomy ( 7 ). The graph shows the prevalence of high labour skills in the United States and, to a lesser extent, in the EU. However, low and low-intermediate skills are clearly present in both areas and more so in the EU. ( 7 ) This taxonomy is based on O Mahony and van Ark (2003), op. cit., footnote 2. The basic sectoral classification used in Chapters III, V, and VI is the one used by these authors (see Table III.A.2), which is based on International Standard Industry Classification Rev. 3 (ISIC Rev. 3). Where necessary the data on economic activities originally presented in NACE Rev.1 have been converted into ISIC Rev.3.

EU sectoral competitiveness indicators 16 III.3. Economic activity by size of enterprises Graph III.1: Value added by main sectors (%) 2001 A distinctive characteristic of industrial structure concerns the distribution of economic activity according to the size of the enterprises. This provides a measure of the degree of concentration and of the share of large/small enterprises in the economy. Graph III.4 shows the distribution of the value added of each sector by enterprise size intervals ( 8 ). There is high variation across industries. In nine sectors more than 50 % of the value added is concentrated in the largest enterprises, namely those employing more than 1 000 persons. Six of these sectors are manufacturing industries: tobacco, mineral oil refining, office machinery, telecommunications equipment, motor vehicles, and aircraft and spacecraft. ( 8 ) These intervals are defined in terms of the number of persons employed in the enterprise. Data in Graph III.4 are for 2001, excepting the following sectors, which refer to 2000: sale and repair of motor vehicles, wholesale trade, retail trade, hotels and catering, inland transport, water transport, air transport, supporting transport activities, communications, real estate activities, renting of machinery, computer and related activities, and research and development. Source: Based on O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 17 Graph III.2: Employment by main sectors (%) 2001 Graph III.3: EU-15 and US value added shares (%) by labour skills taxonomy 2001 Source: Based on O Mahony and van Ark (2003), op. cit., footnote 2. HS = high skill; HIS = high-intermediate skill; LIS = low-intermediate skill; LS = low skill. This classification and the data are from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 18 Two belong to services activities: air transport and communications followed by electricity, gas and water supply. A considerable degree of concentration is also found in chemicals, basic metals and electronic valves and tubes, which record more than 40 % of value added in the largest enterprises. At the other extreme are sectors that exhibit a very low level of concentration with a significant share of total value added produced by small and medium-sized enterprises (SMEs) ( 9 ). For example, in the following manufacturing sectors more than 70 % of value added is originated in SMEs: textiles, clothing, leather and footwear, wood and products of wood, metallic products and furniture and other manufacturing. Also, 70 % of value added in construction originates in SMEs, and among services activities, sale of motor vehicles, wholesale trade, hotels and catering, real estate activities and renting of machinery also fall within this group ( 10 ). The level of industrial aggregation presented in Graph III.4 masks significant variation within some of the sectors presented. For example, rubber and plastics can be sub- divided into rubber and rubber products, and plastic products, and these two sectors exhibit completely different distributions: rubber products is characterised by a high level of concentration (54 % of value added in enterprises with more than 1 000 persons employed), and plastic products, where most of the activity (63 % of value added) corresponds to SMEs ( 11 ). ( 9 ) SMEs are defined as enterprises with 250 or fewer persons employed. ( 10 ) The units underlying these distributions are enterprises or firms. The concentration of value added in large enterprises, characteristic of some of the sectors, does not necessarily imply that these industries operate under economies of scale in production since enterprises, and more particularly the largest ones, can operate several small plants. The origin of economies of scale can be found in different functions of the enterprise such as production, marketing, financing, and R & D. The first is directly linked to the activity carried out in plants, while the others are more linked to the enterprise level. The distribution shown in Graph III.4 might reflect economies related to the enterprise but this is a rough approximation. It is nevertheless worth mentioning that some of the sectors with the highest levels of concentration are characterised by economies of scale in production. Examples are motor vehicles, electronic valves and tubes, and aircraft and spacecraft. ( 11 ) There are also variations across countries (not discussed in this pocketbook), an example of which is the textile industry that shows different levels of concentration.

EU sectoral competitiveness indicators 19 Graph III.4: EU-15 value added distribution by enterprise size (%) 2001 Source: Calculated from Eurostat s NewCronos database.

EU sectoral competitiveness indicators 20 III.4. Capital intensity An indicator to characterise the technology of sectors is capital intensity. Not only is it useful for descriptive purposes, but also as a determinant of industry conditions and behaviour. High levels of investment can operate as a barrier to entry, imply a higher degree of risk, and determine cost structures and price strategies of firms. In this section an indicator of capital intensity is presented, which is based on investment in fixed assets per person employed. The indicator has been constructed as follows. First, gross investment in tangible goods per person employed has been estimated across sectors and countries for years 1999, 2000 and 2001 ( 12 ). The average over these three years is the indicator of capital intensity for each country and sector. Using this approach an estimate has been obtained for 13 countries: all EU-15, with the exception of Greece and Luxembourg, although the coverage by industry and country is uneven ( 13 ). The second step consists of calculating the median and mean across countries for each sector. The results are presented in Graph III.5. This shows the mean and median for each sector across the countries available. The sectors are ranked from high to low values of the mean ( 15 ). For nearly all sectors the two values (mean and median) are close to each other, which indicates that the distribution across countries is not skewed. The exceptions are mining and water transport. In the first case the very high value in Denmark (and to a lesser extent in the United Kingdom), and in the second case the high values in Denmark and Austria, have a strong influence in the mean of the distribution ( 16 ). Nevertheless, also in terms of the median value these sectors appear in the top places of the ranking. Strictly speaking this is not an indicator of capital stock per person employed but of investment (that is, addition to the capital stock) by person employed. A drawback is that investment is highly cyclical and therefore the results must be interpreted as an approximation, although the cyclical effect is partially offset by taking average values over three years. Nevertheless, the results are consistent with estimates of stock of capital per person employed from other sources ( 14 ). ( 12 ) The source used is Eurostat s NewCronos database (domain: Structural Business Statistics SBS). ( 13 ) Table III.A.3 shows the data actually available, on which the indicator has been calculated. ( 14 ) See O Mahony and van Ark (2003), op. cit., footnote 2. ( 15 ) Renting of machinery and real estate activities have been excluded from the graph. These activities are outliers, with very high values of investment per person, due to the nature of their activity. ( 16 ) An extreme case in the graph is the case of legal, technical and advertising already mentioned, for which the mean and median values are identical because data are available for one single country.

EU sectoral competitiveness indicators 21 50.0 Mean Median Mining and quarryng Electricity, gas and water supply Water transport Mineral oil refining and nuclear fuel Air transport Communications Electronic valves and tubes Chemicals Supporting transport activities Pulp, paper and paper products Research and development Inland transport Basic metals Motor vehicles Non-metallic mineral products Telecommunication equipment Food, drink and tobacco Aircraft and spacecraft Rubber and plastics Office machinary Other instruments Wood and products of wood Insulated wire Printing and publishing Radio and television receivers Wholesale trade Other electrical machinery n.e.c. Sale and repair of motor vehicles Fabricated metal products Computer and related activities Railroad and transport equipment n.e.c. Textiles Mechanical enginering Scientific instruments Furniture, manufacturing n.e.c. Building and reparing of ships Construction Hotels and catering Retail trade Leather and footwear Other business activities n.e.c. Legal, technical and advertising Clothing Graph III.5: EU-13 Capital intensity Investment in tangibles per person employed 1999 2001 (1 000 EUR) 45.0 40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0 Source: Calculated from Eurostat NewCronos database (SBS domain).

EU sectoral competitiveness indicators 22 III.5. Specialisation of countries Examples of countries that exhibit a high degree of specialisation are Ireland and Finland, the former in office machinery An indicator of sectoral specialisation of EU-15 Member States (index = 16.6) and the latter in telecommunication equipment that compares a country s III.5. Specialisation value added of shares countries across industries (index = 18.9). Other cases worth mentioning are Luxembourg in financial intermediation (index = 5.6) and Denmark with the average EU-15 industry s shares is presented here. The An indicator of sectoral specialisation of EU-15 Member States in that water compares transport a countrys (index = 6.1). Small countries are not necessarily synonymous shares is presented with high degrees of specialisation; in- indicator is defined, for country i and industry j, as follows: value added shares across industries with the average EU-15 industrys here. The indicator is defined, for country i and industry j, as follows: deed, countries like Greece, Portugal, Sweden and Belgium VAi, j exhibit lower indexes of specialisation, and therefore, production structures that are closer to that of EU-15 as a whole. VA i, j j Si, j = (1) VAEU, j Member States for which the six top sectors belong to manufacturing are Austria, Finland, and Ireland. At the other ex- VA EU, j j treme are Luxembourg and the Netherlands, but also Greece and Denmark, in which services activities play an important the indicator, role in the their higher economic the specialisation. Country speciali- where VA is value added and EU is EU-15; a value of 1 for a given industry indicates specialisation equal to the average. The higher the value of where VA is value added and EU is EU-15; a value of 1 for a countrys compared with the EU average. sation is the result of factor endowments, historical factors, given industry indicates specialisation equal to the EU average. The higher the Table value III.A.1 of (in annex) the indicator, shows the values the of higher the indicator the for each understanding of the Member States various and aspects of industrial performance and public policy, for example. The data can be useful in country s specialisation industries. compared A summary is with provided the in EU Table average. III.1 which reports the and six the top sectors likely (those impact with of public policy. For example, the exposure the highest values of the specialisation index) in each Member State. Clearly, there is a Table III.A.1 (in annex) country shows size effect the in values this index of that the must indicator be taken for into consideration in of interpreting a country the to sectoral fluctuations and shocks each of the Member results States ( 17 ). More and industries. precisely, large A summary countries are is less pro-likelvided in Table III.1 specialisation. which reports The the index six shows top sectors a large diversity (those with across EU-15 pean countries industrial exhibiting policies quite both depend upon the degree of to (both exhibit domestic extreme levels and of international) and the impact of Euro- distinctive patterns of sectoral specialisation. Moreover, the pattern varies in the highest values of the specialisation index) in each Member specialisation of each Member State in each sector. that some Member States are mostly or totally specialised in manufacturing sectors but others State. Clearly, there in services is a country activities. size effect in this index that must be taken into consideration in interpreting the results ( 17 ). More precisely, large Examples countries of countries are less that likely exhibit to a high exhibit degree extreme of specialisation are Ireland and Finland, the levels of specialisation. former The in office index machinery shows a (index large = diversity 16.6) and across the latter in telecommunication equipment (index = 18.9). Other cases worth mentioning are Luxembourg ( in financial intermediation EU-15 countries exhibiting quite distinctive patterns of sectoral 17 ) The specialisation index compares the industrial structure of one country with that of (index = 5.6) and Denmark in water transport (index = 6.1). Small EU-15. Since countries big countries are not determine largely the industrial structure of EU-15, significant countries difference like between Greece, big countries and the EU as a whole are not likely, at least to specialisation. Moreover, necessarily the synonymous specialisation with high pattern degrees of varies specialisation; in indeed, the extent of those found for small and intermediate-sized countries. Furthermore, in that some Member Portugal, States Sweden are mostly and Belgium or totally exhibit specialised lower indexes of specialisation, small Member and States therefore, the sizeable presence of an industry determines significantly their manufacturing sectors production but others structures in that services are closer activities. to that of EU-15 as a whole. industrial structure, and differentiates it from the one of EU-15. Member States for which the six top sectors belong to manufacturing are Austria, Finland, and Ireland. At the other extreme are Luxembourg and the Netherlands, but also Greece and

Country 1 2 3 4 5 6 AT Mineral oil refining and nuclear fuel Wood and products of wood Telecommunication equipment Electronic valves and tubes Basic metals Pulp, paper and paper products BE Basic metals Legal, technical and advertising Insurance and pension funding Chemicals Private households with employees Other business activities, not elsewhere classified n.e.c. DE Motor vehicles Other electrical machinery n.e.c. Scientific instruments Mechanical engineering Renting of machinery Electronic valves and tubes DK Water transport Mining and quarrying Radio and television receivers Wholesale trade Building and repairing of ships Health and social work FI Telecommunication equipment Pulp, paper and paper products Water transport Building and repairing of ships Other instruments Wood and products of wood FR Research and development Private households with employees Mineral oil refining and nuclear fuel Electronic valves and tubes Insulated wire Public administration and defence EL Water transport Hotels and catering Clothing Retail trade Sale and repair of motor vehicles Food, drink and tobacco IE Office machinery Electronic valves and tubes Chemicals Printing and publishing Other instruments Scientific instruments IT Private households with employees Leather and footwear Clothing Textiles Railroad and transport equip. n.e.c. Non-metallic mineral products LU Financial intermediation Auxiliary to financial intermediation Basic metals Research and development Communications Inland transport NL Radio and television receivers Mining and quarrying Insurance and pension funding Water transport Auxiliary to financial intermediation Wholesale trade PT Leather and footwear Clothing Textiles Wood and products of wood Financial intermediation Radio and television receivers ES Hotels and catering Inland transport Mineral oil refining and nuclear fuel Construction Non-metallic mineral products Sale and repair of motor vehicles SE Pulp, paper and paper products Telecommunication equipment Insulated wire Health and social work Wood and products of wood Water transport UK Radio and television receivers Mining and quarrying Other instruments Air transport Insurance and pension funding Office machinery EU sectoral competitiveness indicators 23 Table III.1: Six top sectors in country specialisation Source: Calculated from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 24 Table III.2: Specialisation index in labour skills categories Manufacturing Total economy Country HS HIS LIS LS HS HIS LIS LS AT 0.97 0.47 1.11 1.00 0.91 0.79 1.19 1.10 BE 1.62 0.38 0.72 1.09 1.13 0.97 0.95 0.81 DE 0.92 0.91 1.15 0.92 1.02 0.98 1.03 0.94 DK 1.11 0.80 1.10 0.90 0.94 1.10 1.05 0.97 ES 0.94 0.57 0.83 1.23 0.81 0.85 1.08 1.44 FI 1.75 0.74 1.28 0.51 0.94 1.11 1.17 0.80 FR 1.16 1.17 0.87 1.03 1.13 0.97 0.86 0.95 EL 0.75 0.63 0.58 1.51 0.86 0.81 1.05 1.43 IE 3.07 0.81 0.72 0.49 1.04 0.95 1.00 0.93 IT 0.72 0.77 1.03 1.11 0.94 0.84 1.09 1.14 LU 0.56 0.48 0.77 1.44 1.31 0.82 0.85 0.68 NL 1.41 0.72 0.89 0.98 1.00 0.99 1.00 1.01 PT 0.67 0.33 0.74 1.45 0.83 1.03 1.11 1.19 SE 0.95 0.90 1.25 0.82 0.98 1.34 0.94 0.83 UK 1.28 1.19 0.96 0.89 1.00 1.07 0.94 1.02 HS = high skill; HIS = high-intermediate skill; LIS = low-intermediate skill; LS = low skill. Source: Calculated from O Mahony and van Ark (2003), op. cit., footnote 2. A complementary view is provided by the specialisation index based on labour skills categories, shown in Table III.2 ( 18 ). The index has been calculated for the total economy and for the manufacturing sector alone. Three groups of countries can be identified on the basis of the index for the total economy. The first includes countries specialised in high labour skills sectors (Belgium, France, and Luxembourg) and high-intermediate labour skills (Denmark, Finland, Sweden, and to a lesser extent the United Kingdom). The second group includes countries specialised in the two lowest categories of labour skills: Austria, Spain, Greece, Italy and Portugal. Finally, Germany, the Netherlands and Ireland belong to a group that has no clear specialisation profile. This implies that the distribution of value added is very similar to the one of the EU-15 as a whole. ( 18 ) Sectors have been grouped according to the labour skills taxonomy to which they belong, and the value added of the specialisation index has been calculated using the value added of these groups of sectors.

EU sectoral competitiveness indicators 25 The calculation of the index for the manufacturing sector is based on the distribution of value added of manufacturing industries (excluding services). Also in this case, countries can be grouped into three groups. A first group of countries exhibit a marked specialisation in high labour skills manufacturing sectors (Belgium, Finland, Ireland, the Netherlands, France and the United Kingdom). At the opposite end of the scale are countries such as Spain, Greece, Italy, Luxembourg, and Portugal, characterised by specialisation in low labour skills activities. A third group is characterised by specialisation in low-intermediate labour skills. This group consists of Austria, Germany and Sweden. Denmark occupies an intermediate position since this country is specialised in both high and low-intermediate labour skills. Finland also occupies a situation similar to Denmark s although it has been included in the first group because its specialisation in high labour skills is much higher than the one on low-intermediate skills. Clearly, services activities play an important role in explaining differences between the two definitions (total economy and manufacturing) of the specialisation index. This is especially evident in the case of Luxembourg where also the country-size effect is important ( 19 ). III.6. Concluding remarks services in the EU represent 48.1 % of total value added against 52 % in the United States. The distribution of value added by size of enterprises in EU- 15 varies markedly. The weight of value added generated by the largest enterprises those with more than 1 000 persons employed amounts to more than 50 % in nine sectors (including both manufacturing and services). But in another 12 sectors more than 70 % of value added is generated by SMEs. This distribution reflects in part different sectoral organisation and the presence of economies of scale. Finally, the degree of sectoral specialisation in each Member State shows considerable variation. Member States show quite distinctive patterns of specialisation in manufacturing and services activities. This variation naturally persists when the four categories of labour skills are used. This suggests that the impact of sectoral shocks and challenges can vary substantially across Member States depending upon their sectoral specialisation and the relative abundance of different categories of labour skills. The EU manufacturing industry represents 21 % of total value added in the economy, some 5 percentage points higher than in the United States. At the same time, market ( 19 ) See footnote 17.

EU sectoral competitiveness indicators 26 III.7. Annexes Graph III.A.1: EU-15 and US value added shares (%) 2001 Source: Based on O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 27 Graph III.A.2: EU-15 and US employment shares (%) 2001 12 EU-15 US 10 Mining and quarryng Food, drink and tobacco Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Basic metals Non-metallic mineral products Fabricated metal products Mechanical enginering Office machinery Insulated wire Other electrical machinery n.e.c. Electronic valves and tubes Telecommunication equipment Radio and television receivers Scientific instruments Other instruments Motor vehicles Building and reparing of ships Aircraft and spacecraft Railroad and transport equipment n.e.c. Furniture, manufacturing n.e.c. Electricity, gas and water supply Construction Sale and repair of motor vehicles Wholesale trade Retail trade Hotels and catering Inland transport Water transport Air transport Communications Supporting transport activities Financial intermediation Insurance and pension funding Auxiliary to financial intermediation Real estate activities Renting of machinery Computer and related activities Research and development Legal, technical and advertising Other business activities n.e.c. Public administration and defence Education Health and social work Other services 8 6 4 2 0 Source: Based on O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 28 Table III.A.1: EU-15 countries specialisation index Industry AT BE DK FI FR EL IE IT LU NL PT ES SE UK DE Mining and quarrying 0.46 0.17 1.94 0.27 0.22 0.68 0.71 0.52 0.16 3.39 0.52 0.49 0.26 3.11 0.34 Food, drink and tobacco 1.19 1.20 1.42 0.80 1.29 1.37 2.48 1.02 0.45 1.47 1.53 1.24 0.77 1.12 1.01 Textiles 0.80 1.42 0.41 0.36 0.57 0.84 0.22 2.07 1.25 0.38 2.47 0.76 0.28 0.49 0.45 Clothing 0.33 0.31 0.35 0.33 0.59 2.22 0.21 2.17 0.23 0.13 2.95 0.94 0.07 0.48 0.35 Leather and footwear 0.54 0.15 0.17 0.29 0.48 0.81 0.04 2.22 0.00 0.15 3.41 1.14 0.08 0.29 0.21 Wood and products of wood 2.22 0.71 1.08 2.09 0.74 0.77 0.42 1.25 0.35 0.53 1.85 0.87 1.94 0.57 0.98 Pulp, paper and paper products 1.82 0.94 0.76 7.25 0.88 0.37 0.42 0.80 0.02 0.85 1.53 1.15 3.28 0.84 0.92 Printing and publishing 0.77 0.77 1.13 1.12 0.77 0.50 4.91 0.79 0.61 1.20 0.84 0.74 1.09 1.46 1.00 Mineral oil refining and nuclear fuel 2.25 1.07 0.17 1.01 1.41 1.33 0.19 0.62 0.00 1.49 0.92 1.59 0.76 0.97 0.79 Chemicals 0.66 1.86 1.28 0.68 1.05 0.31 5.85 0.86 0.46 1.06 0.46 0.87 0.91 0.90 1.10 Rubber and plastics 0.91 0.75 1.22 0.78 0.87 0.35 0.36 0.84 1.68 0.50 0.59 0.90 0.59 0.85 1.13 Non-metallic mineral products 1.22 1.04 0.67 0.82 0.72 0.93 0.40 1.47 1.00 0.68 1.50 1.44 0.43 0.59 0.89 Basic metals 1.90 2.04 0.58 1.62 0.96 0.78 0.17 0.98 3.14 0.63 0.49 1.11 1.47 0.68 1.38 Fabricated metal products 1.10 0.69 0.82 0.90 0.95 0.31 0.23 1.20 0.72 0.71 0.53 0.85 0.95 0.73 1.15 Mechanical engineering 1.23 0.58 1.35 1.45 0.70 0.22 0.25 1.31 0.36 0.64 0.22 0.62 1.20 0.71 1.69 Office machinery 0.65 0.12 0.42 0.13 1.00 0.05 16.56 0.36 0.17 0.66 0.07 0.73 0.58 1.65 1.24 Insulated wire 1.23 0.51 0.42 1.38 1.31 1.08 0.81 0.83 0.51 1.14 1.13 0.74 2.02 0.90 0.87 Other electrical machinery n.e.c. 1.01 0.67 0.62 0.78 0.77 0.16 1.25 0.96 0.04 0.16 0.65 0.62 0.57 0.61 1.92 Electronic valves and tubes 1.92 0.97 0.62 1.14 1.39 0.06 7.90 0.88 0.03 0.24 1.21 0.41 0.49 1.21 1.39 Telecommunication equipment 1.96 1.16 0.60 18.87 1.12 0.86 1.64 0.76 0.02 0.40 0.98 0.37 2.42 1.55 0.85 Radio and television receivers 1.06 1.59 1.67 0.40 0.30 0.03 0.56 0.16 0.04 4.83 1.53 0.36 0.40 3.30 1.35 Scientific instruments 0.75 0.38 1.05 0.68 1.25 0.09 2.77 0.82 0.38 0.72 0.24 0.51 1.40 0.38 1.84 Other instruments 0.62 0.10 1.17 2.39 0.44 0.07 2.98 0.77 1.11 0.48 0.34 0.21 0.35 2.57 0.90 Motor vehicles 0.95 1.03 0.20 0.22 1.18 0.05 0.09 0.54 0.02 0.28 0.63 1.20 1.84 0.66 1.96 Building and repairing of ships 0.06 0.17 1.48 2.79 1.09 1.37 0.12 0.86 0.05 1.17 0.72 0.92 0.64 0.95 0.39 Aircraft and spacecraft 0.02 0.54 0.06 0.34 1.25 0.37 0.00 0.56 0.02 0.30 0.09 0.33 0.60 1.35 0.71 Source: Own calculation based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

Industry AT BE DK FI FR EL IE IT LU NL PT ES SE UK DE Railroad and transport equipment n.e.c. 1.78 0.29 0.49 0.20 0.80 0.46 1.29 1.63 0.06 0.45 0.76 1.04 1.32 0.54 0.68 Furniture; manufacturing n.e.c. 1.31 0.67 1.09 0.69 0.84 1.01 0.69 1.24 0.19 1.43 0.96 1.04 0.69 0.90 0.83 Electricity, gas and water supply 1.00 1.18 0.92 0.86 1.01 0.91 0.60 1.03 0.56 0.72 1.22 1.04 1.12 0.79 0.88 Construction 1.26 0.86 0.71 0.98 0.81 1.33 1.25 0.84 1.01 1.02 1.40 1.50 0.67 0.87 0.82 Sale and repair of motor vehicles 1.01 0.90 0.77 0.82 0.98 1.56 0.78 1.21 0.73 0.90 1.41 1.29 0.73 1.08 0.86 Wholesale trade 1.33 1.38 1.49 1.02 0.83 0.80 0.68 1.02 0.99 1.55 1.50 0.67 1.03 1.09 1.07 Retail trade 0.92 0.82 0.82 0.66 0.96 1.65 1.10 1.30 0.74 0.83 1.14 1.16 0.65 0.93 1.00 Hotels and catering 1.58 0.59 0.62 0.50 1.00 2.70 1.10 1.37 0.77 0.72 0.84 2.97 0.55 1.16 0.48 Inland transport 1.49 1.35 1.29 1.53 0.90 1.17 0.42 1.32 1.73 0.99 0.65 1.61 1.18 0.99 0.76 Water transport 0.05 0.33 6.10 3.20 0.44 2.85 0.71 0.86 0.18 1.79 0.34 0.87 1.88 1.06 0.83 Air transport 0.64 0.53 1.06 1.27 0.81 1.07 1.72 0.31 0.00 1.38 1.15 1.21 0.71 2.42 1.00 Supporting transport activities 0.84 1.14 1.21 1.66 1.17 0.59 0.63 1.01 0.64 0.98 1.01 1.00 0.86 1.60 0.89 Communications 0.73 0.67 0.80 1.23 0.78 1.27 1.00 0.86 2.16 0.92 1.06 1.04 0.96 1.07 0.86 Financial intermediation 1.35 1.12 1.07 0.70 0.92 1.09 0.86 1.19 5.60 0.92 1.60 1.25 0.58 0.84 0.76 Insurance and pension funding 1.32 1.90 1.26 0.69 0.65 0.28 0.97 0.58 0.31 1.89 0.05 0.45 0.94 1.79 0.80 Auxiliary to financial intermediation 0.25 0.19 0.29 0.45 1.05 0.79 0.39 1.21 4.60 1.60 0.00 0.89 0.35 1.29 0.83 Real estate activities 0.86 0.20 1.11 1.14 1.20 1.33 0.12 0.98 0.95 0.79 0.24 0.84 1.10 0.92 1.22 Renting of machinery 1.12 1.56 0.39 0.23 0.79 0.29 1.41 1.11 0.49 0.89 1.37 0.33 0.41 0.87 1.57 Computer and related activities 0.67 1.61 0.67 0.92 1.07 0.14 1.66 0.92 0.72 1.06 0.50 0.42 1.49 1.35 0.94 Research and development 0.49 1.04 0.64 1.10 2.97 0.20 0.12 0.33 2.39 0.97 0.09 0.08 0.58 0.99 0.94 Legal, technical and advertising 0.76 1.91 0.71 0.53 1.05 0.32 1.55 1.07 0.85 0.99 0.58 0.66 0.97 1.11 0.96 Other business activities n.e.c. 0.55 1.63 0.65 0.44 1.10 0.46 0.65 0.69 0.53 1.18 0.78 0.42 0.52 1.15 1.39 Public administration and defence 1.00 1.26 1.00 0.75 1.30 1.08 0.61 0.84 0.86 1.18 1.44 0.95 0.88 0.70 0.95 Education 1.03 1.25 1.00 0.94 0.97 0.93 0.74 0.99 0.73 0.78 1.50 0.93 1.44 1.11 0.80 Health and social work 0.73 1.01 1.47 1.20 1.01 0.80 0.90 0.72 0.60 1.19 1.04 0.82 1.99 1.01 0.96 Other services 0.86 0.62 0.98 0.87 0.73 0.67 0.59 0.84 0.60 0.88 0.84 1.00 1.09 1.17 1.21 Private households with employees 0.73 1.64 0.43 0.38 2.24 1.03 0.27 2.28 1.50 1.28 0.00 0.00 0.04 0.00 0.42 EU sectoral competitiveness indicators 29 Table III.A.1 (cont.) Source: Own calculation based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 30 Table III.A.2: Industry classification (*) Industry ISIC Rev. 3 code Mining and quarrying 10 14 Food, drink and tobacco 15 16 Textiles 17 Clothing 18 Leather and footwear 19 Wood and products of wood and cork 20 Pulp, paper and paper products 21 Printing and publishing 22 Mineral oil refining, coke and nuclear fuel 23 Chemicals 24 Rubber and plastics 25 Non-metallic mineral products 26 Basic metals 27 Fabricated metal products 28 Mechanical engineering 29 Office machinery 30 Insulated wire 313 Other electrical machinery and apparatus n.e.c. 31 ex313 Electronic valves and tubes 321 Telecommunication equipment 322 Radio and television receivers 323 Scientific instruments 331 Other instruments 33 ex331 Motor vehicles 34 Building and repairing of ships and boats 351 Aircraft and spacecraft 353 Source: O Mahony and van Ark (2003), op. cit., footnote 2. (*) For the sake of presentation the headings of some industries have been abridged in tables and graphs. Railroad equipment and transport equipment n.e.c. 352 + 359 Furniture, miscellaneous manufacturing; recycling 36 37 Electricity, gas and water supply 40 41 Construction 45 Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of automotive fuel Wholesale trade and commission trade, except of motor vehicles and motorcycles Retail trade, except of motor vehicles and motorcycles; repair of personal and household goods Hotels and catering 55 Inland transport 60 Water transport 61 Air transport 62 Supporting and auxiliary transport activities; activities of travel agencies 63 Communications 64 Financial intermediation, except insurance and pension funding 65 Insurance and pension funding, except compulsory social security 66 Activities auxiliary to financial intermediation 67 Real estate activities 70 Renting of machinery and equipment 71 Computer and related activities 72 Research and development 73 Legal, technical and advertising 741 743 Other business activities n.e.c. 749 Public administration and defence; compulsory social security 75 Education 80 Health and social work 85 Other community, social and personal services 90 93 50 51 52

BE DK DE ES FR IE IT NL AT PT FI SE UK Mining and quarrying * * * * n.a. * * * * * * * * Food, drink and tobacco * * n.a. * n.a. * * n.a. n.a. * n.a. n.a. n.a. Textiles * * * * * * * * * * * * * Clothing * * * * * * * * * * * * * Leather and footwear * n.a. * * * * * * n.a. * * * * Wood and products of wood * * * * * * * * * * * * * Pulp, paper and paper products * * * * * * * * * * * * * Printing and publishing * * * * * * * * * * * * * Mineral oil refining and nuclear fuel * n.a. * * * n.a. * * n.a. n.a. * * n.a. Chemicals * * * * * * * * * * * * * Rubber and plastics * * * * * * * * * * * * * Non-metallic mineral products * * * * n.a. * * * * * * * n.a. Basic metals * * * * * * * * * * * * * Fabricated metal products * * * * * * * * * * * * * Mechanical engineering * * * * * * * * * * * * * Office machinery * * n.a. * * * * n.a. * * * * * Insulated wire * n.a. * * * * * * * * * * * Other electrical machinery n.e.c. * n.a. * * * * * n.a. * * * * * Electronic valves and tubes * * n.a. * * * * * * * * n.a. * Telecommunication equipment * * * * * * * n.a. * * * n.a. * Radio and television receivers * * * * * * * n.a. * * * * * Scientific instruments * * * * * n.a. * n.a. * * * * n.a. Other instruments * * * * * n.a. * * * * * * n.a. Motor vehicles * * n.a. * * * * * * * * * * Building and repairing of ships * * n.a. * * * * * * * * * * Aircraft and spacecraft * * * * * n.a. * n.a. * * * * n.a. Railroad and transport equipment n.e.c. n.a. n.a. n.a. * * n.a. * n.a. * * * * n.a. EU sectoral competitiveness indicators 31 Table III.A.3: Data used to calculate figures in Graph III.5

EU sectoral competitiveness indicators 32 BE DK DE ES FR IE IT NL AT PT FI SE UK Furniture; manufacturing n.e.c. * n.a. * * n.a. n.a. * n.a. * * * * * Electricity, gas and water supply * n.a. n.a. * * n.a. * * * * * * n.a. Construction * * * n.a. * n.a. * n.a. * * * * n.a. Sale and repair of motor vehicles * * * * * n.a. * * * * * * n.a. Wholesale trade * * * * * n.a. * * * * * * n.a. Retail trade * * * * * n.a. * n.a. * * * * n.a. Hotels and catering * * * * * n.a. * * * * * * * Inland transport * * * * * n.a. * n.a. * * * * n.a. Water transport * * * * * n.a. * * * * * * * Air transport * * n.a. * * n.a. * n.a. * * * * n.a. Supporting transport activities * * * * * n.a. * n.a. * * * * * Communications * * * * * n.a. * n.a. * * * * * Computer and related activities * * n.a. * * n.a. * n.a. * * * * n.a. Research and development * * n.a. * * n.a. * n.a. * * * * n.a. Legal, technical and advertising n.a. n.a. n.a. n.a. n.a. n.a. * n.a. n.a. n.a. n.a. n.a. n.a. Other business activities n.e.c. * * n.a. * * n.a. * n.a. * * * * n.a. Table III.A.3 (cont.) *: Data available. n.a.: not available.

Chapter IV: Industrial interrelations and competitiveness: An input-output approach EU sectoral competitiveness indicators 33 IV.1. Introduction Modern economies are characterised by strong interrelation between industries; these interrelationships are central for the analysis of competitiveness. This section presents basic elements and measures of industrial interrelations based on standard input-output (IO) techniques ( 20 ). Sound industrial policy requires going beyond the analysis of each industry separately by considering each industry as part of a complex set of interdependencies. mation on all the countries available is presented at the end of each section. The chapter is organised as follows. In Section IV.2 the original IO table has been aggregated into six branches ( 22 ), and the basic characteristics of industrial interrelations are reviewed using technical coefficients and the Leontief inverse matrix ( 23 ). The output multiplier effect, direct and indirect impact, stage by stage, of the production of one branch on all the others, is illustrated graphically using the power series approximation ( 24 ) of the Production is a combination of primary inputs (services of labour and capital), intermediate inputs (from other sectors of the economy), and technology. Input-output tables, which concern the web of intermediate inputs, encapsulate interrelations through which innovation and technology embedded in intermediate inputs diffuse throughout the economy. Input-output analysis shows that the competitiveness of the EU economy is not the result of merely aggregating individual industries performance but the result of a complex network of relationships between them. The discussion in this chapter is carried out using as a basis the IO table for Germany ( 21 ). A summary of relevant infor- ( 20 ) A classical reference is Leontief, Wassily (1986), Input-output economics, second edition, Oxford University Press. See also Miller and Blair (1984), Input-output analysis: Foundations and extensions, Prentice-Hall. For applications in various fields and recent developments see: Lahr, Michael L. and Erik Dietzenbacher (eds.) (2001), Input-output analysis: Frontiers and extensions, Palgrave MacMillan; Peterson, William (1991), Advances in input-output analysis, Oxford University Press; and Miller, Ronald E., Karen R. Polenske, and Adam Z. Rose (eds.) (1989), Frontiers of input-output analysis, Oxford University Press. For a detailed methodological presentation of IO tables compilation and related issues see Eurostat (2002), The ESA 95 input-output manual: Compilation and analysis. ( 21 ) The source of data for this chapter is Eurostat s input-output tables for various EU- 15 Member States. The tables currently available refer to 1995 (Austria, Belgium, Spain, Sweden and the United Kingdom), 1998 (Greece) and 2000 (Denmark, Germany, Italy, the Netherlands, Austria, and Finland). ( 22 ) The list of the 59 homogeneous branches in the Eurostat IO tables is presented in the annex to this chapter. ( 23 ) In the context of the input-output model, technical coefficients measure the value of the inputs needed to produce one unit of final production. The Leontief inverse is a matrix expression that captures both the direct and indirect effects of a given vector of final demand on the production of all the other sectors of the economy. ( 24 ) This is an expression that allows calculating the Leontief inverse based on successively summing up the inputs needed for producing each unit of output.

EU sectoral competitiveness indicators 34 Leontief inverse. This six-branch aggregation gives a compact view of the structure of the economy, and shows relationships between the main sectors, especially between manufacturing industry and market services. Section IV.3 is based on an ICT by ICT table, which is the result of regrouping the original 59 branches according to the seven categories of the information and communication technology taxonomy. This table is also analysed using technical coefficients and the Leontief inverse, and shows the role of ICT technologies in the economy. In Section IV.4 the IO table is aggregated to show the interrelations between industries that have been previously grouped according to the labour skills taxonomy to underline the role of human capital. Section IV.5 presents indicators derived from IO tables aggregated at 42 branches. Section IV.6 concludes. Even at this highly aggregated level Table IV.1 highlights a crucial feature of modern economies: industries are characterised by strong links, which are reflected in the intermediate transactions matrix. The analysis of these links sheds light on current competitiveness-related issues of the economy at large, which cannot be properly understood on the basis of the performance of each sector separately. In IO tables these interrelations are between suppliers and users of intermediate goods and services, and are the channels that convey technology embedded in the goods and services that are used as inputs in the production process of each branch. Yet, this network of interrelations can also become the carrier of inefficiency and cause the creation of bottlenecks. Thus, the crucial message from this approach is that competitiveness of the economy as a whole is more than adding up the competitiveness of each of its components (sectors). IV.2. The structure of the economy: a six-branch input-output table Table IV.1 shows a traditional presentation of the IO table for Germany ( 25 ) aggregated to six branches: agriculture, mining, manufacturing industry, construction, market services and non-market services ( 26 ). The table consists of three sections: an intermediate transaction matrix ( 27 ), final demand vectors ( 28 ), and value added vectors. Imports of products, from both intra-eu and extra-eu, of the branch are added to total output to provide total supply. Some aspects of this table are of interest for the analysis of competitiveness. An example of the usefulness of this approach is given by the possibility of identifying groups of industries characterised by strong mutual supply-demand links ( 29 ). These in- ( 25 ) Prior to the aggregation, FISIM (financial intermediation services indirectly measured) has been allocated to the intermediate consumption by branch on the basis of the share of each branch in total value added, and the corresponding adjustments have been made in the total intermediate consumption and operating surplus vectors. ( 26 ) Strictly speaking, the table is a product by product representing relationships between homogeneous branches of production, defined in terms of CPA (classification of products by activity) codes. ( 27 ) Sectors of origin are in rows and those of destination are in columns. ( 28 ) Final consumption encompasses both private and public consumption. ( 29 ) The techniques used for identifying clusters are not discussed here. However, high levels of detail in the branches of the table are necessary in order to achieve an operational identification of clusters.

identity ( 31 ) presented in Table IV.2 for the six branches. The role of both sides, supply and demand, in manufacturing is evident: 28 % (14 total supply of manufacturing goods is imported and 31.5 % (17.7 % EU sectoral competitiveness indicators 35 Constructi dustry clusters constitute a pool of specialised suppliers of goods and capital equipment, skilled labour, technology and innovation that create external economies for the businesses included in the cluster. These external economies play an important role in explaining external trade flows, and they determine the competitiveness of the businesses and industry and of the economy as a whole ( 30 ). Another aspect evident from Table IV.1 is the role of international trade. Beyond the traditional view of international trade as a source of goods and services for final consumption, the table shows international trade as providing domestic branches with access to intermediate inputs of foreign origin. Trade in intermediate goods enlarges business opportunities through access to foreign inputs and becomes a source of gains from trade and a factor of competitiveness for domestic industries. This is shown by the fact that for Germany s manufacturing industrial branch 28 % of total intermediate inputs are imported. This percentage is significantly higher than the one of goods and services imported to meet final consumption demand, which is 19 %. The importance of the internal market is also shown in the table as 51 % of total imports in Germany originate in the rest of the EU, although the table does not show the geographic origin (EU versus extra-eu) of the intermediate inputs imported. A first summary of the interrelationships in question is provided by the supply-demand identity ( 31 ) presented in Table IV.2 for the six branches. The role of international trade on uses are exports. both sides, supply and demand, in manufacturing is evident: 28 % (14.8 % plus 12.9 %) of total supply of manufacturing goods is imported and 31.5 % (17.7 % plus 13.8 %) of total uses are exports. Table IV.2: Supply-demand identity Germany 2 (% of each component on total supply and demand Manufactu Agriculture, Mining ring, hunting and and electricity, forestry, and quarrying gas and fishing water Output 73.2 24.0 72.3 98 + Imports from EU 15.1 15.7 14.8 0 + Imports from extra-eu 11.8 60.3 12.9 0 = = = = Intermediate demand 64.2 86.2 41.6 21 + Consumption 25.3 7.5 17.1 1 + Capital formation 1.8 3.6 9.8 77 + Exports to EU 4.9 1.9 17.7 0 + Exports to extra-eu 3.8 0.8 13.8 0 Source: Calculated from Table IV.1. Regardless of the geographical origin of intermediate flows, the columns of Table IV.1 provide information on the inputs (both intermediate and primary) combined by each branch to carry out their production process; in other words they represent the technology of the branches. This is better captured by the technical coefficients matrix ( 32 ) presented in Table IV.3. The importance of intra-branch flows, that is, the consumption of ( 30 ) See reference to clustering of competitive Regardless industries of the in geographical Porter, Michael origin of E. (1998), intermediate The flows, the co competitive advantage of nations, Palgrave, provide New information York. on the inputs (both intermediate and primary) com ( 31 ) In a given branch supply is composed to carry of domestic out their output production and process; imports in other of goods words (or they represent services) of the same branch. This branches. supply of This goods is better (or captured services) by is the broken technical down, coefficients matrix IV.3. The importance of intra-branch flows, that is, the consump from the demand point of view, into various uses: production of other goods and products by the manufacturing branch and the consumption of market s services (intermediate demand), private and public consumption, capital formation, and exports. By definition (capital formation includes variation in 33 ): the technical coeffic services branch is a first characteristic ( stocks) manufacturing is 0.42, and the technical coefficient market service these two variables are equal. From this identity production can be expressed as a 0.29. There is also some degree of circularity (although asymmetric) function of final demand: market services in the table about which more is said later. Z d + Z m + Y d + Y m = X + M Z d + Y d = X A d X + Y ( 31 d = ) XIn a given branch supply is composed of domestic output and imports of goods (or services) of the sa X = (I A d ) -1 (or services) is broken down, from the demand point of view, into various uses: production of other demand), Y d private and public consumption, capital formation, and exports. By definition (capital form these two variables are equal. From this identity production can be expressed as a function of final de where, Z d : domestic intermediate inputs; Zd + Zm Z+ Yd m : + intermediate Ym = X + M inputs imported; X: production; M: total imports; Y d Zd + Yd = X : final demand for domestic production; Y m : final demand for Ad X + Yd = X imported goods; A d : domestic technical X = (I coefficients. Ad) -1 Yd ( 32 ) Technical coefficients measure the relationship between inputs and output in each branch. More precisely they are calculated as follows: follows: Z ij a ij = X where, Zd: domestic intermediate inputs; Zm: intermediate inputs imported; X: production; M: total impor production; Ym: final demand for imported goods; Ad: domestic technical coefficients. ( 32 ) Technical coefficients measure the relationship between inputs and output in each branch. More j where Zij is intermediate consumption (both domestic and imported) by branch j of inputs from branch j. The technical coefficients matrix A is formed of the intermediate technical coefficients de primary inputs the corresponding vectors are divided by total output. ( 33 ) The size of intra-branch flows is magnified by the level of aggregation. where Z ij is intermediate consumption (both domestic and imported) by branch j of inputs from branch i, and X j is the output of branch j. The technical coefficients matrix A is formed of the intermediate technical coefficients defined in that way. Similarly, for primary inputs the corresponding vectors are divided by total output.

EU sectoral competitiveness indicators 36 >>> Table IV.1: Input-output table Germany 2000 (million EUR) 1 Agriculture, hunting and forestry, and fishing 1 2 3 4 5 6 7 = (1 + + 6) Agriculture, hunting and forestry, and fishing Mining and quarrying Manufacturing, electricity, gas and water Construction Market services Nonmarket services Total Final consumption expenditure 8 9 10 11 12 = 10 + 11 Gross capital formation Exports intra-eu fob Exports extra-eu fob Total exports 13 = 8 + 9 + 12 14 = 7 + 13 Final uses Total use 1 251 34 27 464 1 1 419 942 31 111 9 862 1 427 2 240 2 175 4 415 15 704 46 815 2 Mining and quarrying 224 490 6 195 2 027 175 364 9 475 1 324 203 790 315 1 105 2 226 11 701 3 Manufacturing, electricity, gas and water 7 615 2 173 336 902 56 023 60 756 30 049 493 518 213 350 106 916 261 000 205 874 466 874 787 140 1 280 658 4 Construction 381 365 6 388 2 828 27 089 7 845 44 896 4 187 174 720 86 23 109 179 016 223 912 5 Market services 8 987 3 161 227 344 48 933 400 264 78 947 767 636 594 128 53 763 51 602 43 469 95 071 742 962 1 510 598 6 Non-market services 1 678 467 16 486 1 491 31 610 27 136 78 868 490 839 4 211 1 272 1 586 2 858 497 908 576 776 7 = 1 + + 6 Total domestic intermediate inputs 8 Agriculture, hunting and forestry, and fishing 20 136 6 690 620 779 111 303 521 313 145 283 1 425 504 1 313 690 340 834 316 990 253 442 570 432 2 224 956 3 650 460 198 3 9 075 0 343 347 9 966 6 336 293 895 247 1 142 7 185 17 151 9 Mining and quarrying 225 248 30 608 291 702 522 32 596 2 333 1 979 147 61 208 4 520 37 116 10 Manufacturing, electricity, gas and water 3 457 595 196 840 12 952 18 951 10 719 243 514 89 801 66 919 51 914 38 426 90 340 247 060 490 574 11 Construction 2 281 508 1 819 128 28 2 766 0 812 0 0 0 812 3 578 12 Market services 115 85 9 828 1 620 42 710 3 075 57 433 7 568 1 729 2 15 17 9 314 66 747 13 Non-market services 0 0 807 0 614 7 741 9 162 672 0 2 18 20 692 9 854 14 = 9 + + 13 Total imported intermediate inputs 3 997 1 212 247 666 16 682 63 448 22 432 355 437 106 710 71 146 52 960 38 767 91 727 269 583 625 020

EU sectoral competitiveness indicators 37 Table IV.1 (cont.) 1 2 3 4 5 6 7 = (1 + + 6) Agriculture, hunting and forestry, and fishing Mining and quarrying Manufacturing, electricity, gas and water Construction Market services Nonmarket services Total 15 = 7 + 14 Total intermediate inputs 16 Taxes less subsidies on products 17 = 15 + 16 Total intermediate consumption at purchasers prices 18 Compensation of employees 19 Other net taxes on production 20 Consumption of fixed capital 24 133 7 902 868 445 127 985 584 761 167 715 1 780 941 1 176 111 6 470 1 651 20 310 16 281 45 999 25 309 8 013 874 915 129 636 605 071 183 996 1 826 940 9 533 5 430 309 780 65 521 403 199 306 497 1 099 960 1 830 4 075 7 395 773 16 168 8 081 10 350 7 722 1 679 65 152 5 591 167 800 54 416 302 360 21 Operating surplus, net 6 081 654 23 416 22 391 318 360 39 948 410 850 22=18+ +21 Value added to basic prices 21 506 3 688 405 743 94 276 905 527 392 780 1 823 520 22=17+22 Output at basic prices 46 815 11 701 1 280 658 223 912 1 510 598 576 776 3 650 460 24 Imports cif intra-eu 9 631 7 680 261 592 2 114 35 650 3 503 320 170 25 Imports cif extra-eu 7 520 29 436 228 982 1 464 31 097 6 351 304 850 26=24+25 Total import cif 17 151 37 116 490 574 3 578 66 747 9 854 625 020 27=23+26 Supply at basic prices 63 966 48 817 1 771 232 227 490 1 577 345 586 630 4 275 480 Source: Calculated from Eurostat IO tables.

EU sectoral competitiveness indicators 38 Table IV.2: Supply-demand identity Germany 2000 (% of each component on total supply and demand) Agriculture, hunting Mining and Manufacturing, Construction Market services Non-market services and forestry, and quarrying electricity, gas and fishing water Output 73.2 24.0 72.3 98.4 95.8 98.3 + Imports from EU 15.1 15.7 14.8 0.9 2.3 0.6 + Imports from extra-eu 11.8 60.3 12.9 0.6 2.0 1.1 = = = = = = = Intermediate demand 64.2 86.2 41.6 21.0 52.3 15.0 + Consumption 25.3 7.5 17.1 1.8 38.1 83.8 + Capital formation 1.8 3.6 9.8 77.2 3.5 0.7 + Exports to EU 4.9 1.9 17.7 0.0 3.3 0.2 + Exports to extra-eu 3.8 0.8 13.8 0.0 2.8 0.3 Source: Calculated from Table IV.1. manufactured products by the manufacturing branch and the consumption of market services by the market services branch is a first characteristic ( 33 ): the technical coefficient manufacturing-manufacturing is 0.42, and the technical coefficient market services-market services is 0.29. There is also some degree of circularity (although asymmetric) between industry and market services in the table about which more is said later. A second aspect that stands out in the table is total intermediate input use per unit of output. This is substantially higher in manufacturing industry (0.678) than in market services (0.387). This suggests the transforming nature of the industrial activity and also that manufacturing industry ( 33 ) The size of intra-branch flows is magnified by the level of aggregation.

EU sectoral competitiveness indicators 39 requires a large variety of inputs and by doing so sustains the activity of other sectors. In other words, the competitiveness of industry would rely on the competitiveness of a large number of other branches. The complexity of the system is due to the fact that each branch s production requires direct inputs from other branches, which in turn require inputs for their own production processes. This means that the total impact of the production activity of a given branch on the rest of the economy is the sum of direct and indirect consumption of inputs. It is in this way that a given branch multiplies its branch j from branch i per unit of output of branch j. For example, t manufacturing industry requires EUR 0.357 of market services, while th 0.178 ( 36 ). Obviously the multiplier of each branch on itself is higher than 1 will have to produce the initial EUR 1 and the industrial inputs requ branches. These interrelations and multipliers can vary between countrie activity throughout the whole system ( 34 ). This output multiplier effect is captured by the Leontief inverse matrix ( 35 ), their industrial structure. The relationship is bidirectional, and measures t industry on services but it also suggests the fact that efficient market serv for the competitiveness of industry. The asymmetry mentioned previou substantially lower size of the multiplier of market services on manuf (0.088). ( 34 ) This propagation process is illustrated and discussed below using an alternative way of calculating the Leontief inverse. Table IV.4: Leontief inverse Germany 2000 ( 35 ) The Leontief inverse is defined as follows: (I-A) -1, where I Agriculture, is the identity Mining matrix, Manufacturing, with Construction hunting and and electricity, gas the same dimension as the technical coefficients matrix A. To measure output multipliers (impact of final demand on domestic production) the calculation of the Leontief inverse in this chapter is ( 34 ) based This propagation on technical process is illustrated coefficients and discussed below of using domestic an alternative origin. The expression is therefore (I A d way of calculating the Leon ( 35 ) The ) -1 Leontief inverse is defined as follows: (I-A) -1, where I is the identity matrix, with the same dimension a matrix, A. where: To measure output multipliers (impact of final demand on domestic production) the calculation this chapter is based on technical coefficients of domestic origin. The expression is therefore (I Ad) -1, whe Z d, ij ad, ij = X j and Zd,ij is use of intermediate inputs of domestic origin from branch i for the production of branch j. ( 36 ) This is not shown in Table IV.3, which measures use of total intermediate inputs (domestic + imported), Table IV.1. and Z d,ij is use of intermediate inputs of domestic origin from branch i for the production of branch j. Table IV.3: Technical coefficients matrix Germany 2000 Agriculture, hunting and forestry, and fishing Mining and quarrying Manufacturing, electricity, gas and water Construction Market services Non-market services Agriculture, hunting and forestry, and fishing 0.0310 0.0032 0.0285 0.0000 0.0012 0.0022 Mining and quarrying 0.0096 0.0631 0.0287 0.0104 0.0006 0.0015 Manufacturing, electricity, gas and water 0.2365 0.2366 0.4168 0.3080 0.0528 0.0707 Construction 0.0082 0.0552 0.0054 0.0208 0.0180 0.0137 Market services 0.1944 0.2774 0.1852 0.2258 0.2932 0.1422 Non-market services 0.0358 0.0399 0.0135 0.0067 0.0213 0.0605 Total intermediate inputs 0.5155 0.6753 0.6781 0.5716 0.3871 0.2908 Compensation of employees 0.2036 0.4641 0.2419 0.2926 0.2669 0.5314 Operating surplus, gross 0.2948 0.1994 0.0692 0.1250 0.3218 0.1636 Value added at basic prices 0.4594 0.3152 0.3168 0.4210 0.5994 0.6810 Output at basic prices 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 Source: Calculated from Table IV.1.

EU sectoral competitiveness indicators 40 which is presented in Table IV.4. Each element (intersection of row i and column j ) of the matrix measures the total input requirement by branch j from branch i per unit of output of branch j. For example, to produce EUR 1 manufacturing industry requires EUR 0.357 of market services, while the direct impact is 0.178 ( 36 ). Obviously the multiplier of each branch on itself is higher than 1, since this branch will have to produce the initial EUR 1 and the industrial inputs required by the other branches. These interrelations and multipliers can vary between countries depending upon their industrial structure. The relationship is bidirectional, and measures the dependence of industry on services but it also suggests the fact that efficient market services are important for the competitiveness of industry. The asymmetry mentioned previously concerns the substantially lower size of the multiplier of market services on manufacturing industry (0.088). As indicated above, the multiplier effect works through several stages. In each of these stages each branch requires inputs from the other branches. This can be illustrated using the power series approximation of the Leontief inverse. The result is represented in Graphs IV.1 (multiplier effect of manufacturing industry) and IV.2 (multiplier effect of market services) ( 37 ). These graphs allow tracking the subsequent waves of production caused by an initial increase of output in the relevant sector. Using manufacturing industry as an example, Graph IV.1 shows that the first step is the production of EUR 1 of output by the industrial branch itself. This ( 36 ) This is not shown in Table IV.3, which measures use of total intermediate inputs (domestic + imported), but can be calculated from Table IV.1. ( 37 ) The power series approximation of the Leontief inverse captures the step-by-step propagation of the impact of the initial production in a given branch. This approximation is expressed as follows: (I-A d ) -1 = I + A d + A d 2 + A d 3 + A d 4 + A d 5 + where I is a unit diagonal matrix and A d is the technical coefficients matrix. Table IV.4: Leontief inverse Germany 2000 Agriculture, hunting and forestry, and fishing Mining and quarrying Manufacturing, electricity, gas and water Construction Market services Non-market services Agriculture, hunting and forestry, and fishing 1.0336 0.0106 0.0311 0.0087 0.0034 0.0041 Mining and quarrying 0.0067 1.0459 0.0074 0.0117 0.0009 0.0014 Manufacturing, electricity, gas and water 0.2583 0.3117 1.3920 0.3758 0.0884 0.0948 Construction 0.0171 0.0444 0.0144 1.0228 0.0263 0.0192 Market services 0.3492 0.4867 0.3566 0.4055 1.3969 0.2268 Non-market services 0.0504 0.0594 0.0282 0.0219 0.0322 1.0560 Source: Calculated from Table IV.1.

EU sectoral competitiveness indicators 41 Graph IV.1: Multiplier effect over six steps of a unit increase in manufacturing output 1 0.9 0.8 0.7 0.6 0.5 Agriculture Mining Industry Construction Market services Non-market services 0.4 0.3 0.2 0.1 0 1 2 3 4 5 6 Source: Calculated from Eurostat s IO table for Germany 2000.

EU sectoral competitiveness indicators 42 Graph IV.2: Multiplier effect over six steps of a unit increase in market services output 1 0.9 0.8 0.7 0.6 0.5 Agriculture Mining Industry Construction Market services Non-market services 0.4 0.3 0.2 0.1 0 1 2 3 4 5 6 Source: Calculated from Eurostat s IO table for Germany 2000.

EU sectoral competitiveness indicators 43 requires direct inputs from all the other branches, which are represented in step 2. The production of these additional inputs by their own respective branches requires in turn more inputs from other branches (step 3), and the process goes on (step 4, etc.) with successive input requirements that become smaller in absolute values in each step of the process ( 38 ). Graph IV.2 shows the multiplier effect for the market services sector. It is clear that the requirements of inputs from industry for the production process of market services are smaller as each of the six steps suggest. exports share in total demand range between 45.8 % in the Netherlands and 13.7 % in Greece. Countries seek to maximise the benefits from specialisation through this openness to external markets, and engage in both inter-industry and intra-industry trade ( 40 ) to exploit comparative advantages. For market services differences across countries are less marked as regards the structure of supply, characterised by more than 90 % being of domestic origin, but there are some cases worth mentioning on the demand side. Belgium, Denmark, Greece and the Netherlands exports share ranges between 14.7 % (Belgium) and 18.3 % (Denmark). So far the discussion has been based on the IO table for Germany. In the rest of this section three tables are presented, which summarise supply-demand identities (Table IV.5), technical coefficients (Table IV.6) and Leontief inverse (Table IV.7) respectively, for the 11 countries for which information is available ( 39 ). The tables focus on manufacturing industry and market services and do not include the information on the other four branches (agriculture, mining, construction and non-market services). Openness to external trade is a characteristic of all countries and this on both the supply and demand sides: for the manufacturing sector the share of imports in total supply goes from 27.7 % in Germany to 45.2 % in the Netherlands. This emphasises the role of international trade as a source of both intermediate inputs and final demand goods and services for consumption and investment purposes. On the demand side, external markets also play a crucial role, and Table IV.6 shows technical coefficients across countries. These reflect technology ( 41 ) and are assumed to be stable, within certain limits. However, several factors can affect their value and explain differences both across countries and over time: e.g. variations in the product mix within each branch, differences in relative prices, and different de- ( 38 ) In this example, the sum of the series converges rapidly towards the Leontief inverse and a small number of steps is sufficient to represent properly how the multiplier effect works. In a more realistic dynamic, setting other elements can play a role. For example, additional input requirements can be met by running down stocks, and will not necessarily increase production immediately. ( 39 ) These are the countries for which a symmetric IO table is available. Supply (make) and use (absorption) matrices are also available for France and Portugal. As indicated in Section IV.1 the IO tables available do not refer to the same year. This fact has to be taken into consideration regarding all tables in this chapter, which are based on data for several countries, namely tables in Sections IV.2 to IV.4 presenting data on individual countries and tables in Section IV.5, which are based on average values for 11 countries. ( 40 ) See Chapter VI on external trade. ( 41 ) Technical coefficients measure use of total (domestic + imported) intermediate inputs relative to production of the branch.

EU sectoral competitiveness indicators 44 Table IV.5: Supply-demand identity Manufacturing Manufacturing AT BE DE DK ES FI EL IT NL SE UK Output 66.7 60.0 72.3 61.5 78.5 76.8 61.7 78.2 54.8 71.8 71.8 + Imports from EU 24.9 31.4 14.8 27.9 15.7 13.8 27.7 25.5 16.6 + Imports from extra-eu 8.4 8.6 12.9 10.6 5.8 9.4 10.5 21.8 19.7 28.2 11.5 = Intermediate demand 42.7 39.8 41.6 39.3 54.0 48.4 42.9 46.6 36.4 43.9 48.3 + Consumption 16.8 12.0 17.1 13.6 21.4 7.8 33.5 20.0 11.7 13.1 19.4 + Capital formation 10.9 5.7 9.8 9.7 7.4 6.6 9.9 9.7 6.1 7.9 9.3 + Exports to EU 19.6 33.1 17.7 24.0 12.2 20.6 7.0 34.9 13.3 + Exports to extra-eu 10.1 9.5 13.8 13.3 5.0 16.7 6.7 23.7 10.9 35.1 9.7 grees of vertical integration of economic activities. Needless to say, changes in technology itself have a definitive effect on technical coefficients. Table IV.6 confirms the relevance of market services as input into the manufacturing production process, with technical coefficients that range between 0.13 for Greece and 0.19 for Germany, and the relatively lower value of manufacturing goods as inputs into the production process of market services. In interpreting these figures it has to be recalled that technical coefficients measure consumption of intermediate inputs. However, an important part of manufactured goods used by market services, and by all the other branches in the economy, appears under the form of capital stock in this branch. Examples of these are ships, aircraft, and railroad equipment used by transport services, and ICT and non-ict equipment used across all services branches such as, for example, financial intermediation (banking and insurance), and retail and wholesale trade. In effect, the contribution of capital as a

EU sectoral competitiveness indicators 45 Table IV.5 (cont.) Market services AT BE DE DK ES FI EL IT NL SE UK Output 95.3 91.5 95.8 89.9 97.0 93.4 95.5 95.9 92.3 94.7 96.2 + Imports from EU 2.7 5.8 2.3 5.9 2.0 4.3 2.1 3.3 1.6 + Imports from extra-eu 2.0 2.7 2.0 4.2 1.0 2.3 2.4 4.1 4.4 5.3 2.2 = Intermediate demand 44.1 52.7 52.3 47.4 43.3 51.7 32.0 49.8 45.8 51.5 50.2 + Consumption 43.6 29.4 38.1 29.6 47.2 40.1 50.1 41.0 33.3 34.6 39.3 + Capital formation 5.5 3.3 3.5 4.7 4.5 3.8 2.2 3.5 4.8 4.6 2.4 + Exports to EU 4.1 10.4 3.3 9.3 3.2 1.9 7.9 10.8 3.6 + Exports to extra-eu 2.8 4.3 2.8 9.0 1.8 2.5 7.7 5.6 5.3 9.3 4.6 Source: Calculated from Eurostat input-output tables. For Italy and Sweden: exports and imports are not split into intra-eu and extra-eu. The figure shown is total exports and imports. factor of production is measured by the services of capital. A measure of the importance of capital goods in the production process is reflected in the capital stock per person employed (see Chapter III for an indicator of capital intensity). Output multipliers of manufacturing industry and market services are presented in Table IV.7 ( 42 ). Focusing on the pair manufacturing-market services, this table emphasises the role of market services in the production of manufacturing, and shows wider variation across countries: EUR 1 of final demand for manufacturing goods requires a total EUR 0.2163 of direct and indirect inputs from market services in the Netherlands and of EUR 0.3388 in Italy. In all ( 42 ) The IO table for Greece does not indicate the geographical origin of intermediate inputs, and therefore the output multiplier has not been calculated.

EU sectoral competitiveness indicators 46 Table IV.6: Technical coefficients Manufacturing, electricity, gas and water AT BE DE DK ES FI EL IT NL SE UK Agriculture, hunting and forestry, and fishing 0.05 0.05 0.03 0.08 0.08 0.05 0.17 0.03 0.06 0.05 0.04 Mining and quarrying 0.02 0.03 0.03 0.04 0.04 0.05 0.06 0.04 0.09 0.02 0.04 Manufacturing, electricity, gas and water 0.40 0.47 0.42 0.35 0.42 0.43 0.29 0.41 0.42 0.38 0.40 Construction 0.00 0.00 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 Market services 0.15 0.16 0.19 0.15 0.16 0.16 0.13 0.18 0.14 0.18 0.15 Non-market services 0.01 0.01 0.01 0.01 0.00 0.01 0.00 0.01 0.01 0.01 0.01 Total intermediate consumption 0.64 0.72 0.68 0.64 0.70 0.70 0.65 0.68 0.72 0.65 0.64 Compensation of employees 0.25 0.18 0.24 0.23 0.18 0.16 0.18 n.a. 0.16 0.19 0.23 Operating surplus, net 0.06 0.06 0.02 0.07 0.12 0.10 0.14 n.a. 0.11 0.16 0.11 Value added at basic prices 0.37 0.28 0.32 0.36 0.30 0.30 0.36 0.29 0.27 0.34 0.35 Output at basic prices 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Market services AT BE DE DK ES FI EL IT NL SE UK Agriculture, hunting and forestry, and fishing 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 Mining and quarrying 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Manufacturing, electricity, gas and water 0.08 0.08 0.05 0.08 0.11 0.12 0.08 0.09 0.08 0.11 0.10 Construction 0.03 0.02 0.02 0.02 0.03 0.04 0.02 0.01 0.02 0.03 0.02 Market services 0.25 0.37 0.29 0.32 0.20 0.22 0.21 0.28 0.29 0.27 0.31 Non-market services 0.02 0.01 0.02 0.03 0.01 0.03 0.01 0.01 0.02 0.02 0.02 Total intermediate consumption 0.39 0.48 0.39 0.45 0.35 0.41 0.33 0.40 0.42 0.43 0.44 Compensation of employees 0.30 0.23 0.27 0.27 0.26 0.25 0.15 n.a. 0.30 0.27 0.28 Operating surplus, net 0.18 0.18 0.21 0.13 0.37 0.19 0.41 n.a. 0.26 0.28 0.24 Value added at basic prices 0.60 0.51 0.60 0.53 0.64 0.57 0.65 0.57 0.57 0.54 0.54 Output at basic prices 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Source: Calculated from Eurostat input-output tables.

EU sectoral competitiveness indicators 47 Table IV.7: Output multipliers Manufacturing, electricity, gas and water AT BE DE DK ES FI EL IT NL SE UK Agriculture, hunting and forestry, and fishing 0.0586 0.0442 0.0311 0.1014 0.1084 0.0839 n.a. 0.0419 0.0538 0.0575 0.0483 Mining and quarrying 0.0080 0.0029 0.0074 0.0331 0.0174 0.0065 n.a. 0.0124 0.0347 0.0055 0.0403 Manufacturing, electricity, gas and water 1.2937 1.2786 1.3920 1.2384 1.4933 1.4354 n.a. 1.4266 1.2925 1.3059 1.4047 Construction 0.0134 0.0125 0.0144 0.0176 0.0179 0.0110 n.a. 0.0124 0.0122 0.0183 0.0145 Market services 0.2535 0.2683 0.3566 0.2652 0.2893 0.2661 n.a. 0.3388 0.2163 0.3044 0.3181 Non-market services 0.0157 0.0114 0.0282 0.0197 0.0082 0.0188 n.a. 0.0148 0.0250 0.0182 0.0225 Total 1.6429 1.6179 1.8297 1.6755 1.9345 1.8218 n.a. 1.8469 1.6346 1.7098 1.8485 Source: Calculated from Eurostat input-output tables. Columns of the Leontief inverse corresponding to manufacturing. Market services AT BE DE DK ES FI EL IT NL SE UK Agriculture, hunting and forestry, and fishing 0.0084 0.0045 0.0034 0.0081 0.0180 0.0115 n.a. 0.0080 0.0054 0.0083 0.0095 Mining and quarrying 0.0014 0.0006 0.0009 0.0025 0.0026 0.0017 n.a. 0.0014 0.0027 0.0019 0.0064 Manufacturing, electricity, gas and water 0.1096 0.1147 0.0884 0.0851 0.1942 0.1778 n.a. 0.1455 0.0896 0.1335 0.1441 Construction 0.0409 0.0347 0.0263 0.0333 0.0453 0.0484 n.a. 0.0188 0.0359 0.0409 0.0311 Market services 1.3111 1.4821 1.3969 1.3516 1.2749 1.2983 n.a. 1.3850 1.3415 1.3621 1.4548 Non-market services 0.0245 0.0182 0.0322 0.0274 0.0089 0.0369 n.a. 0.0220 0.0294 0.0305 0.0305 Total 1.4960 1.6549 1.5481 1.5079 1.5438 1.5746 n.a. 15807 1.5045 1.5772 1.6763 Source: Calculated from Eurostat input-output tables. Columns of the Leontief inverse corresponding to market services.

EU sectoral competitiveness indicators 48 cases these figures show a large backward effect of manufacturing industries. The requirements of manufacturing goods as direct and indirect intermediate inputs by market services are less than for manufacturing, but the remarks made above as regards the use of capital goods also apply here. It is important to recall that the reading of both technical coefficients and output multipliers is twofold. On the one hand, they measure the impact of the production in one branch on the rest of the economy. Therefore they measure the downstream effect and can be useful to see how the effect of both shocks and steady decline (or growth of sectors) is propagated throughout the economy. From this point of view it is evident that manufacturing activity in all countries has a more important downstream effect on market services than the other way around. On the other hand, when the focus is on the rows of the matrix, what is being emphasised is the production of one branch that is needed to facilitate the production of other branches. In this case, branches that account for a significant part of the inputs required by other branches become crucial activities, and their potential lack of competitiveness can become a bottleneck for the competitiveness of the economy at large. For this perspective, market services are an important supplier of inputs to manufacturing as has been underlined by the examples mentioned above, and further improvements in the efficiency of market services will generate significant gains for the competitiveness of manufacturing industry, and of the economy as a whole. IV.3. The role of ICT in the production process Section IV.2 is based on the traditional presentation of IO tables, which shows interrelations between branches classified according to economic activities or product nomenclatures. A different perspective of the economy can be shown by regrouping the original 59 branches into ICT categories ( 43 ). The result for Germany is presented in Table IV.8, which, comparable to Table IV.1, shows an equally complex network of interrelations between ICT producing, ICT using and non-ict industries. Various aspects of interest are shown by the supply-demand identity (see Table IV.9). On the supply side the most striking feature is the high percentage of ICT producing manufacturing of foreign origin, and particularly from extra-eu: almost 50 % of the total supply of ICT producing manufacturing ( 43 ) See O Mahony and van Ark (2003): op. cit. footnote 2, for a description of how these taxonomies have been created. One remark is, nevertheless, necessary as regards the aggregation presented in this section. The IO original tables do not subdivide branches 31 (electrical machinery and apparatus) and 33 (medical precision and optical instruments), and therefore the ICT taxonomy cannot be applied as originally defined. Here ICTPM excludes insulated wire, which is assigned to ICTUM. Furthermore, ICTPM should include only scientific instruments, but includes the whole branch 33 (part of which should be with ICTUM). In empirical terms the noise caused by this reallocation is minor and does not imply a significant shift from the ICT taxonomy. The following figures (1991 2001 averages) referring to value added (source: Eurostat NewCronos database SBS domain) provide an order of magnitude of the error incurred. Insulated wire accounts for 4.7 % of EU- 15 total value added of ICTPM, and for 1.2 % of ICTUM (where included in the IO aggregation). Scientific instruments accounts for 86.3 % of branch 33 ( other instruments, 13.7 %), which has been entirely reallocated to ICTPM. As regards other business services, originally split between ICTUS and NICTS, this branch has been assigned to ICTUS ( ICT using services ).

EU sectoral competitiveness indicators 49 Table IV.8: Input-output table ICT taxonomy (EUR million) Germany 2000 1 2 3 4 5 6 7 8 = 1 + + 7 ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO Total Final consumption expenditure 9 10 11 12 13 = 11 + 12 14 = 9 + 10 + 13 Gross capital formation Exports intra-eu fob Exports extra-eu fob 15 = 8 + 14 Exports Final uses Total use 1 ICTPM 7 387 2 105 1 124 1 274 1 706 6 483 739 20 818 5 173 21 181 20 738 23 411 44 149 70 503 91 321 2 ICTPS 1 653 18 330 5 441 18 576 6 390 17 651 2 066 70 107 25 267 17 163 3 502 3 369 6 871 49 301 119 408 3 ICTUM 2 190 1 166 49 079 9 609 23 799 12 817 13 190 111 850 43 814 58 564 71 713 62 098 133 811 236 189 348 039 4 ICTUS 15 317 7 090 46 395 171 954 95 875 114 348 47 862 498 840 238 423 24 165 29 089 21 257 50 346 312 934 811 774 5 NICTM 6 474 545 36 184 7 804 183 339 33 903 55 071 323 320 139 952 27 179 168 089 120 284 288 373 455 504 778 824 6 NICTS 3 171 2 500 15 557 71 088 38 611 116 421 30 209 277 557 821 277 16 646 20 283 20 429 40 712 878 635 1 156 192 7 NICTO 943 1 669 3 911 10 254 48 642 41 010 16 583 123 012 39 784 175 936 3 576 2 594 6 170 221 890 344 902 8 = 1 + + 7 Total domestic intermediate inputs 37 135 33 405 157 691 290 559 398 362 342 633 165 720 1 425 504 1 313 690 340 834 316 990 253 442 570 432 2 224 956 3 650 460 9 ICTPM 17 993 848 3 573 982 1 306 3 381 280 28 363 7 145 25 553 18 802 8 137 26 939 59 637 88 000 10 ICTPS 628 6 170 215 1 044 273 447 24 8 801 660 937 0 0 0 1 597 10 398 11 ICTUM 768 126 32 843 1 162 7 610 3 532 4 635 50 676 26 206 25 402 14 594 16 977 31 571 83 179 133 855 12 ICTUS 129 292 452 21 054 3 532 3 253 252 28 964 410 451 2 15 17 878 29 842 13 NICTM 3 314 249 19 873 4 176 107 887 15 034 13 432 163 965 56 290 15 964 18 518 13 312 31 830 104 084 268 049 14 NICTS 199 149 1 039 3 080 3 814 18 651 1 898 28 830 7 170 341 2 18 20 7 531 36 361 15 NICTO 48 42 357 578 37 812 1 630 5 371 45 838 8 829 2 498 1 042 308 1 350 12 677 58 515 16 = 9 + + 15 Total imported intermediate inputs 23 079 7 876 58 352 32 076 162 234 45 928 25 892 355 437 106 710 71 146 52 960 38 767 91 727 269 583 625 020

EU sectoral competitiveness indicators 50 Source: Calculated from Eurostat input-output tables. ICTPM(S) = ICT producing manufacturing (services); ICTUM(S) = ICT using manufacturing (services); NICTM(S) = Non-ICT manufacturing (services); NICTO = Non-ICT other. Table IV.8 (cont.) 17 Total intermediate inputs 18 Taxes less subsidies on products 19 = 17 + 18 Total intermediate consumption at purchasers prices 20 Compensation of employees 21 Other net taxes on production 22 Consumption of fixed capital 23 Operating surplus, net 24 = 20 + + 23 Value added at basic prices 25 = 19 + 24 Output at basic prices 26 Imports cif intra-eu 27 Imports cif extra-eu 1 2 3 4 5 6 7 8 = 1 + + 7 ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO Total 60 214 41 281 216 043 322 635 560 596 388 561 191 612 1 780 941 758 969 1 594 10 019 3 384 25 603 3 672 45 999 60 972 42 250 217 637 332 654 563 980 414 164 195 284 1 826 940 25 598 31 469 100 175 267 339 169 076 410 888 95 415 1 099 960 463 574 1 927 10 291 3 737 2 778 3 864 10 350 3 969 12 731 14 086 59 588 35 443 149 897 26 646 302 360 319 32 384 14 214 141 902 6 588 184 021 31 421 410 850 30 349 77 158 130 402 479 120 214 844 742 028 149 618 1 823 520 91 321 119 408 348 039 811 774 778 824 1 156 192 344 902 3 650 460 29 263 5 653 57 638 14 825 174 240 18 675 19 876 320 170 58 737 4 745 76 217 15 017 93 809 17 686 38 639 304 850 28 = 26 +27 Total imports cif 88 000 10 398 133 855 29 842 268 049 36 361 58 515 625 020 29 = 25 + 28 Supply at basic prices 179 321 129 806 481 894 841 616 1 046 873 1 192 553 403 417 4 275 480

EU sectoral competitiveness indicators 51 Table IV.9: Supply-demand identity (%) ICT categories Germany 2000 ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO Output 50.9 92.0 72.2 96.5 74.4 97.0 85.5 + Imports from EU 16.3 4.4 12.0 1.8 16.6 1.6 4.9 + Imports from extra-eu 32.8 3.7 15.8 1.8 9.0 1.5 9.6 = Intermediate demand 27.4 60.8 33.7 62.7 46.5 25.7 41.9 + Consumption 6.9 20.0 14.5 28.4 18.7 69.5 12.1 + Capital formation 26.1 13.9 17.4 2.9 4.1 1.4 44.2 + Exports to EU 22.0 2.7 17.9 3.5 17.8 1.7 1.1 + Exports to extra-eu 17.6 2.6 16.4 2.5 12.8 1.7 0.7 Source: Calculated from Table IV.8. goods is imported (16.3 % from the EU and another 32.8 % from outside the EU). Although less intensively than for the case of ICT producing manufacturing (ICTPM) in the two other categories of industrial branches (ICT using manufacturing, ICTUM, and non-ict using manufacturing (NICTM)) more than 25 % of supply is of foreign origin. This evidence supports the idea that international trade in intermediate goods facilitates access to key inputs for the domestic production process, and contributes to the competitiveness of individual industries and of the economy at large. Given the less tradable nature of services it is not surprising to see that more than 90 % of the supply of services (more than 95 % in the cases of ICT using services and non- ICT services) are of domestic origin. On the demand side, Table IV.9 shows some interesting characteristics of the various branches. ICT producing services (ICTPS) and ICT using services (ICTUS) are, to a large extent, consumed as inputs by all branches (including themselves): over 60 % of these services are re-injected into

EU sectoral competitiveness indicators 52 their own production process. This confirms empirically the crucial role of these services for the productive activity of the rest of the economy ( 44 ). It is also interesting to note that 13.9 % of ICT producing services contributes to capital formation, which is an additional channel of contribution to the productive activity of the economy. As regards industry, the demand destination of ICT producing manufacturing is basically intermediate demand and capital formation but also exports. In other words, ICTPM goods are essentially embedded in other categories of goods and services, either as intermediate inputs or as services of capital or are exported. Further details about the role of ICT technologies is provided by the matrix of technical coefficients and the Leontief inverse, which are shown in Table IV.10 and Table IV.11, respectively. The technical coefficients of ICTPM and ICTPS for all branches are relatively low compared with those of other inputs. In other words, this reveals the strategic nature of this technology, which although with a small share in the total value of inputs consumed (for example, ICTPM inputs account for 0.4 % of the total value of production of NICTM, and ICTPS account for 1.6 % of ICTUM), plays a crucial role in the production of other goods and services. It is nevertheless important to mention here that this refers to the consumption of ICT inputs by other branches, but this reflects only part of the use of ICT technologies. As indicated earlier, part of ICT manufactured goods is used as services of accumulated capital and this is not measured as intermediate input. This brings the idea that the production process requires a combination of inputs whose importance is not given by Table IV.10: Technical coefficients ICT taxonomy aggregation Germany ICTPM ICTPS ICTUM ICTUS NICTM NICTS ICTPM Compensation of employees 0.2803 0.2635 0.2878 0.3293 0.2171 0.3554 Operating surplus, gross 0.0470 0.3778 0.0813 0.2482 0.0540 0.2888 Value added at basic prices 0.3323 0.6462 0.3747 0.5902 0.2759 0.6418 Output at basic prices 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.2779 0.0247 0.0135 0.0028 0.0039 0.0085 ICTPS 0.0250 0.2052 0.0163 0.0242 0.0086 0.0157 ICTUM 0.0324 0.0108 0.2354 0.0133 0.0403 0.0141 ICTUS 0.1691 0.0618 0.1346 0.2378 0.1276 0.1017 NICTM 0.1072 0.0066 0.1611 0.0148 0.3739 0.0423 NICTS 0.0369 0.0222 0.0477 0.0914 0.0545 0.1168 NICTO 0.0109 0.0143 0.0123 0.0133 0.1110 0.0369 Total 0.6594 0.3457 0.6207 0.3974 0.7198 0.3361 the magnitude of the inputs consumed alone but also by their quality and nature. In the present case, and compared with other categories of goods and services, the magnitude of consumption of ICTPM and ICTPS inputs is low (as shown in the examples of coefficients mentioned above), but this reflects the weight of ICTPM and ICTPS in the Source: Calculated from Table IV.8. economy. As in the case of the aggregation to six NACE branches a summary of the information for the 11 countries is provided in the rest of this section. In this case the summary is presented as follows. As regards the supply-demand identity only the two ICT categories with the greatest variation across countries in the share of domestic production in total Source: Calculated from Table IV.8. supply have been selected for reporting: these are ICT producing manufacturing (ICTPM) and ICT using manufacturing (ICTUM). As regards technical coefficients and the output multipliers, rather than focusing on selected ICT categories, the approach taken is to present the mean value across countries and the coefficient of variation as a measure of dispersion around of the countries mean ( around the mean ( 45 ). 45 ). Table IV.11: Leontief inverse ICT taxonomy aggregation ICTPM ICTPS ICTUM ICTUS NICTM NICTS ICTPM 1.0901 0.0234 0.0063 0.0040 0.0052 0.0081 ICTPS 0.0343 1.1863 0.0322 0.0386 0.0238 0.0266 ICTUM 0.0411 0.0179 1.1770 0.0224 0.0575 0.0219 ICTUS 0.2751 0.1097 0.2480 1.3022 0.2536 0.1683 NICTM 0.1191 0.0194 0.1745 0.0304 1.3440 0.0600 NICTS 0.0809 0.0433 0.0965 0.1331 0.1118 1.1385 NICTO 0.0273 0.0222 0.0328 0.0251 0.0968 0.0493 As in the case of the aggregation to six NACE branches a summary of the informatio 11 countries is provided in the rest of this section. In this case the summary is pre follows. As regards the supply-demand identity only the two ICT categories with th variation across countries in the share of domestic production in total supply h selected for reporting: these are ICT producing manufacturing (ICTPM) and IC manufacturing (ICTUM). As regards technical coefficients and the output multiplie than focusing on selected ICT categories, the approach taken is to present the me across countries and the coefficient of variation as a measure of dispersion of Table IV.12 shows an intense exchange across borders (both intra-eu and extr ICTPM goods It is important to recall that the branches included in this ICT cate office machinery, insulated wire, electronic valves and tubes, telecommunication eq ( 44 ) The intermediate radio demand and orientation television receivers of these services and scientific is stronger instruments. than the Some percentage EU countries exhib indicated in the table. level Indeed, of specialisation it is more in appropriate the production to calculate of these the goods intermediate ( 46 ), relative final to the EU (e.g. I demand distribution office excluding machinery, exports, and Finland for which in telecommunication no indication is equipment), given as regards and play an impo their demand destination. this exchange Demand of is goods, broken both down within into the domestic EU and demand worldwide. (intermediate demand plus domestic consumption production plus in capital total supply formation) is relatively and external low, and imports demand from (ex-extra-eu acco However, the perc ports). A more accurate significant measure share of of the the demand supply of destination these goods, would showing be obtained the importance by excluding exports in as the a source calculation of supply of percentages. of goods (for both intermediate inputs, and consumer and in of internatio ( 45 ) The coefficient of variation expresses the standard deviation relative to the average of the distribution: ( 45 ) The coefficient of variation expresses the standard deviation relative to the average of the distribution: StdDev Coefficien t of variation = Mean ( 46 ) See Chapter III.

Table IV.10: Technical coefficients ICT taxonomy aggregation Germany 2000 ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO ICTPM 0.2779 0.0247 0.0135 0.0028 0.0039 0.0085 0.0030 ICTPS 0.0250 0.2052 0.0163 0.0242 0.0086 0.0157 0.0061 ICTUM 0.0324 0.0108 0.2354 0.0133 0.0403 0.0141 0.0517 ICTUS 0.1691 0.0618 0.1346 0.2378 0.1276 0.1017 0.1395 NICTM 0.1072 0.0066 0.1611 0.0148 0.3739 0.0423 0.1986 NICTS 0.0369 0.0222 0.0477 0.0914 0.0545 0.1168 0.0931 NICTO 0.0109 0.0143 0.0123 0.0133 0.1110 0.0369 0.0637 Total 0.6594 0.3457 0.6207 0.3974 0.7198 0.3361 0.5556 Compensation of employees 0.2803 0.2635 0.2878 0.3293 0.2171 0.3554 0.2766 Operating surplus, gross 0.0470 0.3778 0.0813 0.2482 0.0540 0.2888 0.1684 Value added at basic prices 0.3323 0.6462 0.3747 0.5902 0.2759 0.6418 0.4338 Output at basic prices 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 EU sectoral competitiveness indicators 53 Source: Calculated from Table IV.8. Table IV.11: Leontief inverse ICT taxonomy aggregation Germany 2000 ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO ICTPM 1.0901 0.0234 0.0063 0.0040 0.0052 0.0081 0.0050 ICTPS 0.0343 1.1863 0.0322 0.0386 0.0238 0.0266 0.0209 ICTUM 0.0411 0.0179 1.1770 0.0224 0.0575 0.0219 0.0624 ICTUS 0.2751 0.1097 0.2480 1.3022 0.2536 0.1683 0.2591 NICTM 0.1191 0.0194 0.1745 0.0304 1.3440 0.0600 0.2428 NICTS 0.0809 0.0433 0.0965 0.1331 0.1118 1.1385 0.1472 NICTO 0.0273 0.0222 0.0328 0.0251 0.0968 0.0493 1.0765 Source: Calculated from Table IV.8.

EU sectoral competitiveness indicators 54 Table IV.12 shows an intense exchange across borders (both intra-eu and extra-eu) of ICTPM goods. It is important to recall that the branches included in this ICT category are office machinery, insulated wire, electronic valves and tubes, telecommunication equipment, radio and television receivers and scientific instruments. Some EU countries exhibit a high level of specialisation in the production of these goods ( 46 ), relative to the EU (e.g. Ireland in office machinery, and Finland in telecommunication equipment), and play an important role in this exchange of goods, both within the EU and worldwide. However, the percentage of domestic production in total supply is relatively low, and imports from extra-eu account for a significant share of the supply of these goods, showing the importance of international trade as a source of supply of goods (for both intermediate inputs, and consumer and investment goods) that play ( 46 ) See Chapter III. Table IV.12: Supply-demand identity ICTPM ICTPM AT BE DE DK EL ES FI IT NL SE UK Output 50.8 36.2 50.9 38.4 17.7 47.5 73.8 54.9 22.3 56.0 52.5 + Imports from EU 27.6 45.1 16.3 48.0 64.7 29.1 9.8 27.1 20.6 + Imports from extra-eu 21.6 18.7 32.8 13.6 17.6 23.4 16.4 45.1 50.6 44.0 26.9 = Intermediate demand 26.6 24.4 27.4 28.6 20.3 25.9 38.8 26.9 18.2 27.4 31.7 + Consumption 7.1 5.9 6.9 7.3 11.9 13.2 2.4 13.9 5.3 4.0 5.0 + Capital formation 28.5 24.5 26.1 19.4 60.5 39.5 13.3 34.7 8.1 25.1 20.9 + Exports to EU 24.3 34.3 22.0 29.0 3.1 13.9 22.3 52.9 26.5 + Exports to extra-eu 13.5 10.8 17.6 15.8 4.2 7.5 23.1 24.4 15.5 43.5 15.8 Source: Calculated from Eurostat input-output tables. For Italy and Sweden exports and imports are not sub-divided into intra-eu and extra-eu. The figure shown is total exports and imports.

EU sectoral competitiveness indicators 55 Table IV.13: Supply-demand identity ICTUM ICTUM AT BE DE DK EL ES FI IT NL SE UK Output 62.3 54.9 72.2 63.4 55.2 75.5 72.5 81.9 54.5 67.3 70.7 + Imports from EU 28.1 30.1 12.0 23.3 30.5 17.7 16.4 25.6 14.5 + Imports from extra-eu 9.6 15.0 15.8 13.2 14.3 6.8 11.1 18.1 19.9 32.7 14.9 = Intermediate demand 32.1 32.0 33.7 32.5 27.2 39.6 43.0 27.3 39.3 42.0 37.4 + Consumption 16.2 13.5 14.5 10.0 36.9 25.3 9.1 18.7 14.8 10.3 18.9 + Capital formation 20.0 15.4 17.4 19.4 19.0 17.6 13.1 17.6 11.5 13.8 16.7 + Exports to EU 19.6 25.4 17.9 23.6 9.8 10.8 13.8 22.9 12.2 + Exports to extra-eu 12.0 13.8 16.4 14.4 7.2 6.7 21.0 36.4 11.6 33.8 14.9 Source: Calculated from Eurostat input-output tables. For Italy and Sweden exports and imports are not sub-divided into intra-eu and extra-eu. The figure shown is total exports and imports. an important role in the competitiveness of all branches and of the economy as a whole. Tables IV.14 and IV.15 show the mean value of technical coefficients and of the Leontief inverse matrix coefficients. The former represents the average technology to produce these categories of goods. It is an unweighted average of the 11 country observations and the coefficient of variation indicates, in some cases, substantial deviations from the average. Some factors that can explain these differences have already been mentioned in this chapter. One example of an extreme case in the ICTPM category is Finland, which falls apart from the rest, particularly as regards the intensity of transactions within this category of goods. On average the consumption of ICTPM inputs to produce one monetary unit of ICTPM goods is 0.262, while for Finland this coeffi-

EU sectoral competitiveness indicators 56 Source: Calculated from Eurostat input-output tables. (*) The mean and coefficient of variation of compensation of employees and operating surplus are calculated on 10 countries, since Italy does not provide this information. cient takes up the value of 0.366. At this level of aggregation this is evidence of the ICT pole of activity in this country revolving around the telecommunication equipment sector, which is also reflected in the high level of specialisation in this sector (see Chapter III). IV.4. Human capital: labour skills-based input-output tables IO tables can also be used to show the role of human capital in the production process. Such an IO table for Germany is presented in this section (see Table IV.16) where the economy is aggregated into four branches, each of which groups industries belonging to the same labour skills category. Like in Sections IV.2 and IV.3, supply-demand identities, technical coefficients, and output multipliers have been derived from the aggregated IO Table IV.16. Some aspects that are worth mentioning follow. The accounting identities presented in Table IV.17 show some interesting aspects. On the supply side almost 25 % of total supply of goods embodying low labour skills is imported in Germany, divided almost equally between imports from the Table IV.14: Technical coefficients across countries Mean and coefficient of variation (*) ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation ICTPM 0.262 0.224 0.027 0.532 0.016 0.690 0.008 1.380 0.003 0.793 0.006 0.449 0.006 0.642 ICTPS 0.019 0.526 0.107 0.482 0.014 0.446 0.037 0.322 0.008 0.429 0.016 0.305 0.006 0.330 ICTUM 0.084 0.697 0.023 0.701 0.180 0.299 0.028 0.460 0.031 0.227 0.020 0.259 0.036 0.332 ICTUS 0.132 0.241 0.106 0.367 0.115 0.144 0.190 0.245 0.102 0.212 0.087 0.257 0.103 0.296 NICTM 0.102 0.208 0.021 0.646 0.236 0.228 0.032 0.470 0.340 0.148 0.060 0.251 0.168 0.159 NICTS 0.042 0.485 0.069 0.457 0.051 0.410 0.111 0.249 0.054 0.441 0.124 0.315 0.043 0.509 NICTO 0.010 0.322 0.023 0.559 0.015 0.423 0.015 0.324 0.173 0.380 0.043 0.250 0.160 0.508 Total intermediate consumption 0.651 0.066 0.377 0.247 0.627 0.073 0.421 0.105 0.711 0.044 0.357 0.130 0.522 0.137 Compensation of employees 0.230 0.289 0.331 0.137 0.269 0.093 0.315 0.183 0.179 0.202 0.351 0.064 0.203 0.228 Operating surplus, net 0.090 0.683 0.194 0.518 0.077 0.606 0.205 0.301 0.083 0.484 0.190 0.465 0.215 0.419 Value added at basic prices 0.342 0.126 0.613 0.155 0.366 0.123 0.562 0.081 0.289 0.115 0.616 0.083 0.464 0.137

To conclude, Tables IV.20, IV.21 and IV.22 at the end of the section present the three derived tables for the 11 countries. EU sectoral competitiveness indicators 57 Table IV.15: Leontief inverse coefficients across countries Average and coefficient of variation ICTPM ICTPS ICTUM ICTUS NICTM NICTS NICTO Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation Mean Coefficient of variation ICTPM 1.0923 0.0608 0.0127 0.9831 0.0065 0.4744 0.0046 1.2789 0.0036 0.7554 0.0038 0.7674 0.0047 1.1336 ICTPS 0.0331 0.4070 1.1039 0.0456 0.0294 0.3266 0.0526 0.3209 0.0222 0.3026 0.0272 0.2795 0.0199 0.2954 ICTUM 0.0519 0.5960 0.0308 0.5424 1.1263 0.0363 0.0388 0.3095 0.0403 0.2904 0.0250 0.2002 0.0408 0.3019 ICTUS 0.1866 0.2729 0.1635 0.2598 0.1883 0.2174 1.2425 0.0498 0.1855 0.2375 0.1453 0.1865 0.1907 0.2385 NICTM 0.1191 0.4487 0.0419 0.4837 0.2255 0.4638 0.0541 0.4399 1.2841 0.0576 0.0776 0.4361 0.2110 0.2780 NICTS 0.0850 0.3539 0.1056 0.5068 0.1054 0.3033 0.1540 0.2919 0.1127 0.2929 1.1521 0.0410 0.0981 0.2777 NICTO 0.0351 0.3035 0.0416 0.4632 0.0528 0.3836 0.0378 0.2857 0.1619 0.2684 0.0704 0.2244 1.2155 0.0941 Total 1.6031 0.0818 1.5000 0.0908 1.7342 0.0782 1.5845 0.0528 1.8104 0.0679 1.5015 0.0454 1.7807 0.0844 Source: Calculated from Eurostat input-output tables. rest of the EU (12.4 %) and from outside the EU (11.5 %). This percentage is substantially higher than the percentage corresponding to the other categories of labour skills. The technical coefficients and Leontief inverse (Tables IV.18 and IV.19) matrices also provide some information of interest. These refer to the technology of each category of industries and to the importance of high-skilled labour in the economy. Production by industries employing low-skill labour is basically a transformation activity in which intermediate inputs account for 64 % of the total value of production, with inputs from low-skill labour industries themselves (intra-branch consumption) amounting to 32 %. The Leontief inverse shows the role of high labour skills in the production process of other categories of goods and services. Low labour skilled production requires a significant (both direct and indirect) contribution of high labour skilled branches. For example, to produce EUR 1 of low-skill goods it is necessary to use EUR 0.24 of goods of high-skill labour and EUR 0.09 of goods of high-intermediate-skill labour. Similarly, EUR 1 of high-skill goods utilises EUR 0.05 of low-intermediate-skill and EUR 0.09 of low-skill goods. Therefore, low labour skills branches production embodies high-skilled labour inputs to a substantial extent, and vice versa, but ultimately this production is undertaken by lowskilled labour.

EU sectoral competitiveness indicators 58 Table IV.16: Input-output table Labour skills taxonomy Germany 2000 1 2 3 4 5 = 1 + + 4 HS HIS LIS LS Total Final consumption expenditure 6 7 8 9 10 = 8 + 9 Gross capital formation Exports intra-eu fob Exports extra-eu fob 11 = 6 + 7 12 = 5 + 11 + 10 Exports Final uses Total use 1 HS 252 114 60 484 155 699 92 510 560 808 528 205 52 824 64 293 57 539 121 832 702 861 1 263 669 2 HIS 27 849 77 150 53 557 39 326 197 882 247 080 13 230 29 433 17 978 47 411 307 721 505 603 3 LIS 64 251 31 976 185 846 87 772 369 845 258 048 252 253 103 255 92 985 196 240 706 541 1 076 386 4 LS 30 798 14 634 74 094 177 443 296 969 280 357 22 527 120 009 84 940 204 949 507 833 804 802 5 = 1 + +4 Total intermediate consumption/final demand (domestic) 375 012 184 244 469 196 397 051 1 425 504 1 313 690 340 834 316 990 253 442 57 043 2 224 956 3 650 460 6 HS 67 458 8 236 14 883 20 277 110 854 17 697 24 297 20 168 10 126 30 294 72 288 183 142 7 HIS 1 742 19 627 7 773 956 30 098 6 345 10 916 3 647 11 222 14 869 32 130 62 228 8 LIS 4 924 2 783 52 051 16 178 75 936 9 963 21 644 11 288 7 170 18 458 50 065 126 001 9 LS 30 057 5 640 23 265 79 587 138 549 72 705 14 289 17 857 10 249 28 106 115 100 253 649 10 = 6 + + 9 Total intermediate consumption/final demand (imported) 104 181 36 286 97 972 116 998 355 437 106 710 71 146 52 960 38 767 91 727 269 583 625 020 12 Taxes less subsidies on products 13 = 11 + 12 Total intermediate consumption at purchasers prices 14 Compensation of employees 19 827 9 694 9 388 7 090 45 999 499 020 230 224 576 556 521 139 1 826 940 380 775 157 515 364 033 197 637 1 099 960 15 Other net taxes on production 7 209 2 392 10 214 4 681 10 350

EU sectoral competitiveness indicators 59 Table IV.16 (cont.) 16 Consumption of fixed capital 17 Operating surplus, net 18 = 14 + + 17 Value added at basic prices 1 2 3 4 5 = 1 + + 4 HS HIS LIS LS Total 140 878 60 003 49 155 52 324 302 360 235 787 60 253 76 428 38 383 410 850 764 649 275 379 499 830 283 663 1 823 520 19 = 13 + 18 Output at basic prices 1 263 669 505 603 1 076 386 804 802 3 650 460 20 Imports cif intra-eu 95 302 28 079 65 282 131 507 320 170 21 Imports cif extra-eu 87 840 34 149 60 719 122 142 304 850 22= 20 + 21 Total imports cif 183 142 62 228 126 001 253 649 625 020 23 = 19 + 22 Supply at basic prices 1 446 811 567 831 1 202 387 1 058 451 4 275 480 Source: Calculated from Eurostat IO tables. HS = high skills; HIS = high-intermediate skills; LIS = low-intermediate skills; LS = low skills.

EU sectoral competitiveness indicators 60 Table IV.17: Supply-demand identities (%) Labour skills categories Germany 2000 HS HIS LIS LS Output 87.3 89.0 89.5 76.0 + Imports from EU 6.6 4.9 5.4 12.4 + Imports from extra-eu 6.1 6.0 5.0 11.5 = = = = = Intermediate demand 46.4 40.1 37.1 41.1 + Consumption 37.7 44.6 22.3 33.4 + Capital formation 5.3 4.3 22.8 3.5 + Exports to EU 5.8 5.8 9.5 13.0 + Exports to extra-eu 4.7 5.1 8.3 9.0 Table IV.18: Technical coefficients Labour skills taxonomy Germany 2000 HS HIS LIS LS HS 0.2529 0.1359 0.1585 0.1401 HIS 0.0234 0.1914 0.0570 0.0501 LIS 0.0547 0.0687 0.2210 0.1292 LS 0.0482 0.0401 0.0904 0.3194 Total 0.3792 0.4362 0.5269 0.6387 Compensation of employees 0.3013 0.3115 0.3382 0.2456 Operating surplus, gross 0.2981 0.2378 0.1167 0.1127 Value added at basic prices 0.6051 0.5447 0.4644 0.3525 Output at basic prices 1.0000 1.0000 1.0000 1.0000 Source: Calculated from Table IV.16. Source: Calculated from Table IV.16. Table IV.19: Leontief inverse Labour skills taxonomy Germany 2000 HS HIS LIS LS HS 1.2784 0.2077 0.2557 0.2373 HIS 0.0413 1.1956 0.0869 0.0932 LIS 0.0882 0.1122 1.2470 0.1945 LS 0.0493 0.0608 0.1213 1.3109 Source: Calculated from Table IV.16.

HS HIS AT BE DE DK EL ES FI IT NL SE UK AT BE DE DK EL ES FI IT NL SE UK Output 87.6 81.9 87.3 84.9 86.4 89.6 85.0 89.6 74.6 87.4 88.9 91.7 85.6 89.0 77.5 88.1 93.1 91.0 90.0 84.0 90.8 92.5 + Imports from EU 8.2 14.0 6.6 11.5 9.5 7.0 7.3 11.9 5.8 5.0 8.4 4.9 12.5 5.5 4.2 4.4 7.1 3.1 + Imports from extra-eu 4.2 4.1 6.1 3.6 4.1 3.5 7.8 10.4 13.6 12.6 5.3 3.3 6.0 6.0 10.0 6.4 2.7 4.6 10.0 8.9 9.2 4.4 = = = = = = = = = = = = = = = = = = = = = = = Intermediate demand 40.3 41.9 46.4 39.6 33.1 42.7 41.3 49.8 37.3 41.1 44.4 39.6 45.0 40.1 40.3 32.9 41.4 40.1 43.6 35.3 36.5 52.2 + Consumption 45.5 34.6 37.7 42.5 57.5 43.8 33.9 39.4 29.8 40.6 38.3 50.0 39.3 44.6 45.6 51.8 48.8 45.5 45.1 44.7 53.0 38.5 + Capital formation 4.9 2.9 5.3 5.4 3.7 7.0 6.9 4.0 4.7 6.1 3.8 3.2 2.3 4.3 4.2 5.5 3.7 4.1 4.3 2.2 2.0 2.0 + Exports to EU 5.8 15.1 5.8 7.9 2.3 3.9 9.4 21.4 7.3 4.2 9.0 5.8 5.8 4.1 4.0 4.3 10.4 2.8 + Exports to extra-eu 3.6 5.5 4.7 4.6 3.5 2.6 8.6 6.8 6.7 12.2 6.2 3.0 4.4 5.1 4.2 5.7 2.1 6.1 7.0 7.4 8.5 4.5 LIS LS AT BE DE DK EL ES FI IT NL SE UK AT BE DE DK EL ES FI IT NL SE UK Output 87.5 84.4 89.5 88.2 88.2 93.1 91.1 92.7 85.5 88.1 91.2 72.7 61.1 76.0 71.5 78.1 84.4 73.1 80.2 64.0 76.4 78.4 + Imports from EU 9.6 12.5 5.4 9.0 8.5 5.4 6.6 9.1 5.2 19.2 28.7 12.4 17.9 13.4 9.6 14.6 20.3 12.4 + Imports (total) 3.0 3.1 5.0 2.8 3.3 1.5 2.3 7.3 5.4 11.9 3.6 8.1 10.1 11.5 10.6 8.6 6.0 12.2 19.8 15.7 23.6 9.2 = = = = = = = = = = = = = = = = = = = = = = = Intermediate demand 36.3 44.1 37.1 34.9 29.4 44.1 44.4 38.5 39.3 44.1 43.1 37.9 39.5 41.1 40.9 37.4 44.0 57.1 43.4 43.1 45.9 43.5 + Consumption 21.4 17.0 22.3 17.1 30.9 23.5 14.9 26.2 18.1 14.6 28.3 36.5 19.2 33.4 24.5 42.0 39.8 25.1 35.5 21.3 28.3 36.7 + Capital formation 25.2 18.4 22.8 19.4 31.6 25.2 16.3 20.4 18.9 14.9 17.6 5.6 2.2 3.5 3.6 2.7 2.9 1.9 4.2 4.1 3.5 4.9 + Exports to EU 10.7 15.8 9.5 15.1 3.9 4.7 13.6 17.0 5.6 14.0 29.4 13.0 21.8 10.2 10.3 9.4 25.4 9.2 + Exports to extra-eu 6.5 4.9 8.3 13.5 4.2 2.5 10.8 14.9 6.8 26.4 5.5 6.0 9.7 9.0 9.1 7.7 2.9 6.5 16.9 6.2 22.3 5.8 Source: Calculated from Eurostat input-output tables. For Italy and Sweden exports and imports are not split into intra-eu and extra-eu. The figure shown is total exports and imports. EU sectoral competitiveness indicators 61 Table IV.20: Supply-demand identity Labour skills

EU sectoral competitiveness indicators 62 Table IV.21: Technical coefficients across countries HS HIS AT BE DE DK EL ES FI IT NL SE UK AT BE DE DK EL ES FI IT NL SE UK HS 0.18 0.26 0.25 0.18 0.15 0.17 0.24 0.22 0.26 0.21 0.23 0.10 0.13 0.14 0.13 0.08 0.14 0.13 0.17 0.14 0.16 0.13 HIS 0.04 0.04 0.02 0.04 0.03 0.04 0.06 0.04 0.03 0.06 0.06 0.18 0.16 0.19 0.09 0.10 0.10 0.09 0.17 0.17 0.11 0.28 LIS 0.09 0.06 0.05 0.08 0.07 0.09 0.11 0.06 0.07 0.11 0.09 0.07 0.12 0.07 0.09 0.05 0.06 0.12 0.09 0.07 0.08 0.07 LS 0.05 0.05 0.05 0.06 0.06 0.05 0.08 0.07 0.09 0.06 0.05 0.08 0.06 0.04 0.08 0.05 0.07 0.07 0.07 0.09 0.05 0.06 Total intermediate consumption Compensation of employees 0.35 0.41 0.38 0.37 0.31 0.35 0.48 0.39 0.46 0.44 0.43 0.42 0.47 0.44 0.38 0.27 0.37 0.40 0.50 0.47 0.41 0.55 0.35 0.32 0.30 0.33 0.32 0.36 0.24 n.a. 0.30 0.27 0.31 0.33 0.30 0.31 0.44 0.36 0.36 0.37 n.a. 0.30 0.40 0.29 Operating surplus, net 0.16 0.16 0.19 0.13 0.27 0.26 0.15 n.a. 0.22 0.26 0.23 0.11 0.13 0.12 0.06 0.23 0.25 0.09 n.a. 0.21 0.15 0.13 Value added at basic prices 0.63 0.58 0.61 0.60 0.67 0.63 0.49 0.58 0.52 0.52 0.55 0.57 0.51 0.54 0.59 0.70 0.61 0.58 0.47 0.51 0.56 0.43 LIS LS AT BE DE DK EL ES FI IT NL SE UK AT BE DE DK EL ES FI IT NL SE UK HS 0.12 0.14 0.16 0.14 0.11 0.11 0.12 0.17 0.15 0.13 0.14 0.12 0.11 0.14 0.12 0.08 0.10 0.13 0.13 0.12 0.12 0.14 HIS 0.04 0.08 0.06 0.14 0.04 0.05 0.06 0.05 0.05 0.06 0.07 0.04 0.04 0.05 0.03 0.03 0.04 0.04 0.04 0.05 0.04 0.04 LIS 0.22 0.29 0.22 0.21 0.15 0.25 0.28 0.20 0.25 0.23 0.23 0.13 0.12 0.13 0.12 0.08 0.11 0.14 0.14 0.10 0.14 0.12 LS 0.10 0.10 0.09 0.08 0.11 0.11 0.13 0.10 0.09 0.11 0.11 0.27 0.43 0.32 0.29 0.32 0.36 0.32 0.29 0.33 0.30 0.28 Total intermediate consumption Compensation of employees 0.48 0.61 0.53 0.57 0.41 0.51 0.58 0.53 0.54 0.53 0.55 0.56 0.71 0.64 0.55 0.51 0.61 0.63 0.60 0.59 0.61 0.59 0.34 0.24 0.34 0.30 0.16 0.26 0.24 n.a. 0.29 0.30 0.28 0.26 0.17 0.25 0.22 0.14 0.19 0.21 n.a. 0.17 0.23 0.24 Operating surplus, net 0.09 0.08 0.07 0.06 0.34 0.21 0.12 n.a. 0.16 0.16 0.15 0.11 0.06 0.05 0.13 0.32 0.20 0.11 n.a. 0.22 0.15 0.17 Value added at basic prices 0.51 0.38 0.46 0.42 0.55 0.48 0.41 0.44 0.45 0.46 0.44 0.45 0.28 0.35 0.44 0.50 0.39 0.38 0.37 0.40 0.37 0.41 Source: Calculated from Eurostat input-output tables.

HS HIS AT BE DE DK EL ES FI IT NL SE UK Mean AT BE DE DK EL ES FI IT NL SE UK Mean HS 1.177 1.239 1.278 1.208 n.a. 1.182 1.230 1.253 1.258 1.247 1.269 1.234 0.126 0.185 0.208 0.159 n.a. 0.162 0.155 0.242 0.170 0.215 0.212 0.184 HIS 0.055 0.053 0.041 0.062 n.a. 0.057 0.078 0.053 0.046 0.074 0.105 0.063 1.165 1.150 1.196 1.097 n.a. 1.088 1.099 1.187 1.147 1.112 1.395 1.164 LIS 0.126 0.102 0.088 0.120 n.a. 0.136 0.174 0.097 0.110 0.163 0.146 0.126 0.100 0.179 0.112 0.124 n.a. 0.110 0.178 0.147 0.107 0.125 0.140 0.132 LS 0.054 0.041 0.049 0.071 n.a. 0.063 0.080 0.080 0.067 0.073 0.079 0.066 0.065 0.070 0.061 0.085 n.a. 0.104 0.088 0.090 0.112 0.067 0.107 0.085 Total 1.412 1.436 1.457 1.461 n.a. 1.438 1.562 1.484 1.481 1.556 1.598 1.489 1.456 1.585 1.576 1.465 n.a. 1.464 1.520 1.666 1.537 1.519 1.855 1.564 LIS LS AT BE DE DK EL ES FI IT NL SE UK Mean AT BE DE DK EL ES FI IT NL SE UK Mean HS 0.167 0.218 0.256 0.177 n.a. 0.172 0.170 0.262 0.198 0.183 0.237 0.204 0.155 0.162 0.237 0.162 n.a. 0.161 0.187 0.225 0.165 0.182 0.219 0.185 HIS 0.063 0.112 0.087 0.071 n.a. 0.077 0.090 0.075 0.058 0.085 0.138 0.085 0.071 0.073 0.093 0.058 n.a. 0.078 0.080 0.077 0.064 0.074 0.101 0.077 LIS 1.215 1.340 1.247 1.230 n.a. 1.323 1.363 1.240 1.267 1.258 1.295 1.278 0.177 0.183 0.195 0.168 n.a. 0.212 0.251 0.223 0.140 0.209 0.206 0.196 LS 0.093 0.111 0.121 0.084 n.a. 0.184 0.178 0.141 0.095 0.121 0.148 0.128 1.229 1.279 1.311 1.274 n.a. 1.428 1.334 1.323 1.279 1.273 1.295 1.303 Total 1.538 1.780 1.711 1.562 n.a. 1.756 1.801 1.718 1.618 1.647 1.818 1.695 1.631 1.698 1.836 1.662 n.a. 1.878 1.852 1.848 1.647 1.737 1.820 1.761 EU sectoral competitiveness indicators 63 Table IV.22: Leontief inverse coefficients across countries Source: Calculated from Eurostat input-output tables. IV.5. Other input-output indicators So far the discussion has focused on aggregate tables which present a concise view of the economy (six-branch aggregation) and the role of specific technologies (ICT aggregation) and human capital (labour skills aggregation). This section presents three indicators calculated from IO tables aggregated at 42 branches ( 47 ). These indicators are exports/total production, technical coefficients, and output multiplier. Table IV.23 shows an indicator that measures exports of domestic production relative to total output, for an aggregate of ( 47 ) In the 42-branch table some of the original branches (see Annex IV.7) have been aggregated into six new sectors as follows: (1) Agriculture, forestry and fishing products = Products of agriculture, hunting and related services, Products of forestry, logging and related services, and Fish and other fishing products; services incidental of fishing ; (2) Mining products = Coal and lignite, Crude petroleum and natural gas, Uranium and thorium ores, Metal ores, and Other mining and quarrying products ; (3) Furniture; other manufactured goods n.e.c.; secondary raw materials = Furniture; other manufactured goods n.e.c., and Secondary raw materials ; (4) Electricity, gas and water = Electrical energy, gas, steam and hot water, and Collected and purified water, distribution services of water ; (5) Sale and repair of motor vehicles; wholesale and retail trade = Trade, maintenance and repair services of motor vehicles and motorcycles; retail sale of automotive fuel, Wholesale trade and commission trade services, except of motor vehicles and motorcycles, and Retail trade services, except of motor vehicles and motorcycles; repair services of personal and household goods ; (6) Non-market services = Public administration and defence services; compulsory social security services, Education services, Health and social work services, Sewage and refuse disposal services, sanitation and similar services, Membership organisation services n.e.c., Rec-

EU sectoral competitiveness indicators 64 nine countries ( 48 ). These are the countries for which the export destination is split into intra-eu and extra-eu. The extent to which these results represent EU-15 at large is constrained by the fact that a big country like France is not included in the sample, which can be particularly relevant as regards the figures for some specific branches (e.g. aircraft). Nevertheless, the table is particularly useful to assess the difference in the export ratio between manufacturing and services branches. With a few exceptions (e.g. food products, wood and products of wood, and fabricated metal products) most of manufacturing branches export more than 10 % of their output to markets external to the EU, and in some cases this percentage is above 20 %: 23 % for chemicals, 26 % for machinery n.e.c., 22 % for office machinery, 27 % for radio, television, and communications equipment, 28 % for scientific and other instruments, and 22 % for other transport equipment (which includes aircraft). The table also measures the relevance of the internal market (intra-eu exports), which accounts in most cases for a higher percentage of output than those corresponding to extra-eu exports. In general market services are much less traded than manufactured goods, but there are a few exceptions: water transport services, air transport services, and research and development. The last two tables of this section show the technical coefficients and the output multiplier for the NACE42 aggregation. Table IV.24 shows the mean of the technical coefficients across the 11 countries: it is an unweighted mean that represents the average technology in each branch. Table IV.25 shows the output multiplier by country and the average value across countries. The output multiplier is the sum of the Leontief inverse columns, which measures the output required, both directly and indirectly, from all branches of the economy to satisfy EUR 1 of final demand for the products of the corresponding branch. It is important to recall here that the output multipliers measure the requirement of output of domestic origin, while the technical coefficients measure the total value of inputs (both domestic and imported) to produce EUR 1 of output. Technical coefficients are more stable across countries, since they represent the technology used in each branch, and their value does not depend on the geographic origin of the inputs. On the contrary, output multipliers show higher variation since they are affected, among others, by the openness of the economy, the tradability of each input (goods and services) and the organisation of each branch in each country ( 49 ). For example, the presence of industry clusters in one country implies strong backward linkages that are translated into reational, cultural and sporting services, Other services, Private households with employed persons. The fifth group of branches ( Sale and repair of motor vehicles; wholesale and retail trade ) has been created because the IO table for Sweden does not present the three sub-groups separately. Agriculture, forestry and fishing products and non-market services have been omitted in the presentation of the results. ( 48 ) The countries are: Austria, Belgium, Germany, Denmark, Greece, Finland, Spain, Netherlands, and the United Kingdom. ( 49 ) There is less variation across countries when the output multipliers are calculated from technical coefficients as presented along this chapter, in other words, when these take into account input consumption regardless of their geographical origin. The results are not presented here since they would make sense only in the hypothetical case of complete autarchy of the countries, but the correlation coefficient in this case is higher than in the case of inputs of domestic origin, and significant for nearly all pairs of countries. This shows that, as expected, there is less variation in inter-industry relationships when these aim at capturing the technology of the branches, rather than when the focus is on the way production is organised across countries.

EU sectoral competitiveness indicators 65 Table IV.23: Export/Production (%) Product Intra-EU Extra-EU Mining products 24.1 8.7 Food products and beverages 15.1 6.4 Tobacco products 34.2 11.0 Textiles 27.1 17.4 Clothing 19.5 10.4 Leather and footwear 20.4 15.1 Wood and products of wood 13.3 6.1 Pulp, paper and paper products 27.9 12.9 Printing and publishing 6.8 4.4 Mineral oil refining and nuclear fuel 22.1 9.7 Chemicals 36.9 23.0 Rubber and plastics 23.3 11.5 Non-metallic mineral products 11.9 7.6 Basic metals 33.0 15.5 Fabricated metal products 12.3 7.7 Machinery n.e.c. 24.5 26.1 Office machinery 35.2 22.3 Electrical machinery n.e.c. 20.5 17.9 Radio, television and communication equipment 34.0 26.8 Scientific and other instruments 23.3 27.6 Motor vehicles 34.6 18.6 Other transport equipment 40.3 21.8 Furniture; manufactured goods n.e.c; secondary raw materials 15.1 10.4 Electricity, gas and water 0.9 0.1 Construction 0.2 0.1 Source: Calculated from Eurostat IO tables. Sale and repair of motor vehicles; wholesale and retail trade 7.5 3.8 Hotels and catering 2.9 2.2 Inland transport 9.9 5.1 Water transport 29.8 49.8 Air transport 15.5 19.1 Supporting transport activities 7.7 4.8 Communications 2.6 2.1 Financial intermediation 1.4 1.2 Insurance and pension funding 1.2 1.8 Auxiliary to financial intermediation 7.2 8.0 Real estate services 0.1 0.1 Renting of machinery 1.5 1.6 Computer and related activities 6.5 5.5 Research and development 10.7 12.6 Other business activities 4.4 4.4

Table IV.24: EU-11 mean of technical coefficients Mining products Food products and beverages Tobacco products Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Agriculture, forestry and fishing products 0.001 0.313 0.255 0.040 0.008 0.012 0.109 0.026 0.000 Mining products 0.045 0.001 0.000 0.001 0.000 0.000 0.000 0.009 0.000 Food products and beverages 0.002 0.201 0.006 0.002 0.002 0.075 0.001 0.005 0.001 Tobacco products 0.000 0.000 0.036 0.000 0.000 0.000 0.000 0.000 0.000 Textiles 0.001 0.000 0.009 0.245 0.303 0.025 0.001 0.006 0.001 Clothing 0.001 0.000 0.001 0.002 0.089 0.001 0.000 0.000 0.000 Leather and footwear 0.000 0.000 0.000 0.001 0.011 0.241 0.000 0.000 0.000 Wood and products of wood 0.002 0.002 0.001 0.001 0.001 0.002 0.239 0.021 0.001 Pulp, paper and paper products 0.004 0.019 0.057 0.009 0.007 0.012 0.010 0.276 0.165 Printing and publishing 0.002 0.006 0.008 0.005 0.009 0.004 0.003 0.009 0.148 Mineral oil refining and nuclear fuel 0.014 0.003 0.000 0.003 0.002 0.002 0.004 0.005 0.001 Products Chemicals 0.021 0.010 0.016 0.117 0.010 0.045 0.025 0.052 0.027 Rubber and plastics 0.006 0.015 0.005 0.011 0.007 0.037 0.012 0.015 0.006 Non-metallic mineral products 0.009 0.006 0.000 0.004 0.001 0.000 0.009 0.001 0.000 Basic metals 0.005 0.001 0.001 0.003 0.001 0.000 0.006 0.003 0.002 Fabricated metal products 0.019 0.012 0.010 0.005 0.005 0.013 0.026 0.006 0.004 Machinery n.e.c. 0.044 0.006 0.006 0.010 0.005 0.007 0.010 0.015 0.006 Office machinery 0.001 0.001 0.000 0.001 0.001 0.001 0.001 0.002 0.001 Electrical machinery n.e.c. 0.005 0.001 0.001 0.001 0.001 0.001 0.002 0.001 0.001 Radio, television and communication equipment 0.000 0.000 0.005 0.000 0.000 0.001 0.000 0.000 0.003 Scientific and other instruments 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Motor vehicles 0.003 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000 Other transport equipment 0.000 0.000 0.001 0.008 0.024 0.003 0.000 0.001 0.000 Furniture; manufactured goods n.e.c., secondary raw materials 0.000 0.001 0.000 0.002 0.007 0.003 0.002 0.004 0.003 Electricity, gas and water 0.041 0.013 0.006 0.023 0.009 0.012 0.016 0.035 0.010

Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Nonmetallic mineral products Basic metals Fabricated metal products Machinery n.e.c. Office machinery Electrical machinery n.e.c. Radio, television and communication equipment Scientific and other instruments 0.000 0.003 0.007 0.002 0.001 0.000 0.001 0.000 0.000 0.000 0.000 0.619 0.021 0.001 0.073 0.052 0.002 0.000 0.000 0.001 0.000 0.000 0.002 0.014 0.001 0.001 0.001 0.001 0.001 0.002 0.001 0.001 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.009 0.002 0.000 0.001 0.001 0.000 0.002 0.000 0.001 0.000 0.000 0.000 0.000 0.001 0.001 0.001 0.001 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.001 0.003 0.006 0.002 0.004 0.002 0.001 0.003 0.002 0.002 0.001 0.017 0.016 0.012 0.002 0.004 0.004 0.005 0.005 0.006 0.008 0.001 0.009 0.006 0.005 0.003 0.004 0.005 0.005 0.005 0.010 0.007 0.075 0.033 0.003 0.014 0.017 0.003 0.002 0.001 0.003 0.001 0.001 0.031 0.274 0.268 0.029 0.027 0.017 0.011 0.005 0.025 0.013 0.016 0.001 0.014 0.080 0.010 0.006 0.012 0.019 0.028 0.026 0.024 0.033 0.001 0.007 0.005 0.117 0.011 0.006 0.005 0.003 0.011 0.005 0.014 0.002 0.005 0.010 0.015 0.297 0.204 0.078 0.015 0.115 0.022 0.028 0.005 0.012 0.015 0.015 0.044 0.134 0.079 0.027 0.040 0.018 0.027 0.008 0.011 0.012 0.016 0.021 0.021 0.149 0.021 0.020 0.006 0.012 0.000 0.001 0.001 0.001 0.002 0.001 0.002 0.183 0.002 0.003 0.006 0.001 0.002 0.003 0.003 0.005 0.008 0.048 0.058 0.177 0.076 0.035 0.000 0.001 0.002 0.001 0.001 0.001 0.011 0.095 0.027 0.281 0.052 0.000 0.002 0.001 0.001 0.001 0.002 0.006 0.008 0.005 0.005 0.124 0.000 0.000 0.002 0.001 0.001 0.002 0.016 0.001 0.001 0.000 0.000 0.000 0.002 0.001 0.000 0.004 0.002 0.003 0.014 0.003 0.005 0.002 0.000 0.001 0.004 0.006 0.025 0.003 0.009 0.001 0.001 0.001 0.002 0.010 0.028 0.023 0.037 0.044 0.016 0.009 0.005 0.010 0.007 0.009 >>>

Table IV.24 (cont.) Mining products Food products and beverages Tobacco products Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Construction 0.014 0.002 0.001 0.003 0.002 0.002 0.005 0.003 0.002 Sale and repair of motor vehicles; 0.028 0.049 0.022 0.053 0.045 0.061 0.067 0.064 0.037 wholesale and retail trade Hotels and catering 0.002 0.002 0.003 0.003 0.003 0.003 0.002 0.002 0.003 Inland transport 0.041 0.022 0.017 0.015 0.013 0.013 0.034 0.031 0.015 Water transport 0.003 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 Air transport 0.003 0.001 0.003 0.002 0.002 0.001 0.002 0.002 0.002 Supporting transport activities 0.010 0.008 0.005 0.006 0.004 0.003 0.008 0.008 0.005 Products Communications 0.005 0.004 0.005 0.004 0.007 0.009 0.004 0.005 0.022 Financial intermediation 0.024 0.013 0.020 0.019 0.018 0.016 0.019 0.018 0.018 Insurance and pension funding 0.003 0.001 0.002 0.002 0.003 0.002 0.003 0.002 0.002 Auxiliary to financial 0.001 0.001 0.002 0.001 0.001 0.002 0.001 0.001 0.001 intermediation Real estate services 0.009 0.005 0.006 0.007 0.008 0.006 0.006 0.005 0.011 Renting of machinery 0.016 0.004 0.004 0.003 0.004 0.003 0.005 0.005 0.008 Computer and related activities 0.004 0.003 0.006 0.003 0.002 0.002 0.002 0.003 0.005 Research and development 0.002 0.001 0.002 0.001 0.001 0.001 0.000 0.000 0.000 Other business activities 0.033 0.042 0.090 0.032 0.043 0.037 0.026 0.028 0.048 Non-market services 0.009 0.007 0.011 0.008 0.007 0.010 0.006 0.008 0.028

Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Nonmetallic mineral products Basic metals Fabricated metal products Machinery n.e.c. Office machinery Electrical machinery n.e.c. Radio, television and communication equipment Scientific and other instruments 0.002 0.003 0.003 0.005 0.005 0.003 0.002 0.002 0.002 0.003 0.002 0.019 0.041 0.046 0.055 0.063 0.042 0.055 0.062 0.043 0.041 0.041 0.001 0.005 0.003 0.003 0.002 0.004 0.004 0.004 0.003 0.005 0.005 0.014 0.023 0.018 0.044 0.023 0.014 0.012 0.006 0.011 0.008 0.009 0.002 0.002 0.002 0.003 0.002 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.003 0.002 0.002 0.002 0.002 0.003 0.003 0.002 0.004 0.004 0.005 0.008 0.006 0.010 0.007 0.005 0.005 0.002 0.004 0.004 0.004 0.002 0.007 0.006 0.006 0.004 0.006 0.007 0.011 0.006 0.007 0.010 0.008 0.017 0.019 0.022 0.016 0.022 0.020 0.016 0.022 0.020 0.020 0.001 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.001 0.002 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.004 0.001 0.001 0.002 0.003 0.005 0.006 0.006 0.003 0.008 0.006 0.009 0.009 0.004 0.008 0.001 0.004 0.005 0.007 0.003 0.005 0.004 0.004 0.004 0.005 0.005 0.002 0.005 0.003 0.004 0.003 0.004 0.005 0.015 0.005 0.011 0.005 0.002 0.009 0.002 0.001 0.001 0.001 0.004 0.003 0.003 0.017 0.003 0.021 0.062 0.038 0.039 0.025 0.032 0.042 0.039 0.040 0.058 0.055 0.004 0.011 0.007 0.007 0.006 0.006 0.006 0.005 0.006 0.007 0.009

Table IV.24: EU-11 mean of technical coefficients (cont.) Motor vehicles Other transport equipment Furniture; manufactured goods n.e.c; secondary raw materials Electricity, gas and water Construction Sale and repair of motor vehicles; wholesale and retail trade Hotels and catering Inland transport Water transport Agriculture, forestry and fishing products 0.000 0.000 0.004 0.002 0.001 0.001 0.022 0.000 0.003 Mining products 0.000 0.000 0.006 0.121 0.011 0.001 0.001 0.001 0.000 Food products and beverages 0.001 0.001 0.002 0.001 0.001 0.005 0.192 0.001 0.011 Tobacco products 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.000 Textiles 0.006 0.004 0.020 0.000 0.001 0.002 0.002 0.000 0.001 Clothing 0.000 0.001 0.001 0.000 0.000 0.002 0.001 0.001 0.001 Leather and footwear 0.000 0.000 0.007 0.000 0.000 0.001 0.000 0.000 0.000 Wood and products of wood 0.003 0.008 0.109 0.003 0.033 0.001 0.001 0.001 0.000 Pulp, paper and paper products 0.002 0.002 0.013 0.002 0.001 0.008 0.005 0.002 0.001 Printing and publishing 0.003 0.004 0.006 0.002 0.002 0.013 0.005 0.005 0.003 Products Mineral oil refining and nuclear fuel 0.002 0.002 0.004 0.026 0.006 0.007 0.003 0.042 0.050 Chemicals 0.017 0.013 0.032 0.005 0.010 0.006 0.004 0.002 0.003 Rubber and plastics 0.045 0.018 0.031 0.003 0.020 0.010 0.002 0.011 0.001 Non-metallic mineral products 0.010 0.005 0.007 0.001 0.085 0.001 0.003 0.001 0.000 Basic metals 0.067 0.052 0.053 0.004 0.018 0.002 0.000 0.001 0.000 Fabricated metal products 0.052 0.065 0.032 0.007 0.046 0.004 0.002 0.003 0.002 Machinery n.e.c. 0.043 0.061 0.009 0.011 0.020 0.004 0.003 0.003 0.002 Office machinery 0.000 0.007 0.001 0.001 0.000 0.003 0.001 0.001 0.001 Electrical machinery n.e.c. 0.033 0.026 0.003 0.015 0.018 0.003 0.001 0.004 0.001 Radio, television and communication equipment 0.003 0.010 0.002 0.001 0.006 0.003 0.001 0.000 0.000 Scientific and other instruments 0.004 0.012 0.000 0.002 0.002 0.001 0.000 0.000 0.000 Motor vehicles 0.283 0.006 0.003 0.000 0.000 0.015 0.000 0.011 0.000 Other transport equipment 0.001 0.170 0.001 0.000 0.000 0.001 0.000 0.007 0.039 Furniture; manufactured goods n.e.c. secondary raw materials 0.010 0.008 0.072 0.000 0.004 0.002 0.002 0.001 0.000 Electricity, gas and water 0.008 0.009 0.011 0.136 0.004 0.011 0.018 0.011 0.002

Air transport Supporting transport activities Communications Financial intermediation Insurance and pension funding Auxiliary to financial intermediation Real estate services Renting of machinery Computer and related activities Research and development Other business activities 0.000 0.001 0.000 0.000 0.000 0.000 0.001 0.001 0.000 0.001 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.001 0.001 0.008 0.003 0.001 0.001 0.002 0.002 0.001 0.002 0.002 0.002 0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.004 0.000 0.001 0.001 0.002 0.002 0.001 0.000 0.000 0.000 0.000 0.001 0.000 0.001 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.003 0.000 0.000 0.001 0.000 0.002 0.001 0.001 0.001 0.001 0.002 0.004 0.003 0.003 0.006 0.005 0.002 0.003 0.009 0.005 0.007 0.007 0.011 0.010 0.011 0.010 0.015 0.003 0.009 0.017 0.040 0.032 0.083 0.007 0.004 0.001 0.001 0.005 0.001 0.014 0.002 0.003 0.002 0.001 0.003 0.001 0.001 0.001 0.001 0.001 0.002 0.005 0.022 0.006 0.002 0.004 0.003 0.001 0.001 0.001 0.001 0.006 0.003 0.004 0.003 0.000 0.001 0.001 0.000 0.000 0.000 0.003 0.000 0.001 0.001 0.001 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.003 0.000 0.002 0.003 0.002 0.001 0.001 0.002 0.002 0.003 0.003 0.006 0.002 0.003 0.004 0.002 0.000 0.001 0.001 0.001 0.010 0.003 0.005 0.002 0.001 0.001 0.001 0.002 0.001 0.003 0.000 0.003 0.015 0.004 0.004 0.002 0.002 0.007 0.001 0.001 0.001 0.001 0.002 0.012 0.003 0.001 0.001 0.001 0.025 0.001 0.003 0.001 0.000 0.002 0.009 0.002 0.005 0.002 0.001 0.001 0.000 0.000 0.000 0.000 0.001 0.001 0.012 0.003 0.001 0.001 0.001 0.000 0.000 0.000 0.000 0.007 0.003 0.002 0.001 0.051 0.002 0.000 0.000 0.000 0.001 0.000 0.003 0.001 0.001 0.001 0.001 0.001 0.001 0.002 0.001 0.001 0.001 0.004 0.002 0.003 0.004 0.002 0.010 0.009 0.005 0.005 0.006 0.010 0.009 0.010 0.013 0.005 >>>

Table IV.24 (cont.) Motor vehicles Other transport equipment Furniture; manufactured goods n.e.c; secondary raw materials Electricity, gas and water Construction Sale and repair of motor vehicles; wholesale and retail trade Hotels and catering Inland transport Water transport Construction 0.002 0.003 0.003 0.020 0.112 0.005 0.008 0.008 0.004 Sale and repair of motor vehicles; 0.056 0.032 0.059 0.017 0.053 0.045 0.046 0.061 0.031 wholesale and retail trade Hotels and catering 0.002 0.003 0.003 0.002 0.003 0.008 0.010 0.007 0.020 Inland transport 0.012 0.008 0.019 0.007 0.013 0.030 0.007 0.055 0.004 Water transport 0.001 0.001 0.001 0.000 0.001 0.002 0.001 0.006 0.089 Air transport 0.001 0.003 0.002 0.001 0.001 0.004 0.002 0.002 0.005 Supporting transport activities 0.005 0.004 0.005 0.003 0.002 0.023 0.006 0.051 0.232 Products Communications 0.004 0.004 0.006 0.006 0.004 0.019 0.011 0.009 0.007 Financial intermediation 0.012 0.017 0.021 0.022 0.019 0.032 0.022 0.025 0.019 Insurance and pension funding 0.001 0.002 0.003 0.003 0.001 0.004 0.003 0.008 0.007 Auxiliary to financial 0.001 0.002 0.001 0.001 0.001 0.001 0.001 0.001 0.003 intermediation Real estate services 0.003 0.004 0.012 0.005 0.014 0.045 0.042 0.008 0.005 Renting of machinery 0.002 0.003 0.004 0.005 0.012 0.005 0.003 0.013 0.019 Computer and related activities 0.005 0.006 0.003 0.005 0.002 0.007 0.004 0.005 0.005 Research and development 0.003 0.005 0.001 0.001 0.000 0.001 0.000 0.001 0.001 Other business activities 0.029 0.033 0.042 0.028 0.043 0.070 0.039 0.027 0.043 Non-market services 0.004 0.006 0.008 0.011 0.005 0.013 0.024 0.015 0.004 Source: Calculated from Eurostat input-output tables.

Air transport Supporting transport activities Communications Financial intermediation Insurance and pension funding Auxiliary to financial intermediation Real estate services Renting of machinery Computer and related activities Research and development Other business activities 0.002 0.025 0.022 0.008 0.009 0.007 0.085 0.003 0.002 0.006 0.006 0.019 0.018 0.019 0.008 0.008 0.011 0.006 0.070 0.019 0.021 0.017 0.035 0.049 0.007 0.006 0.006 0.008 0.001 0.006 0.008 0.009 0.011 0.006 0.043 0.013 0.004 0.005 0.007 0.001 0.012 0.006 0.007 0.006 0.001 0.006 0.002 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.027 0.056 0.008 0.003 0.004 0.004 0.001 0.006 0.004 0.005 0.005 0.226 0.101 0.005 0.002 0.004 0.004 0.001 0.008 0.003 0.004 0.004 0.012 0.020 0.081 0.029 0.030 0.054 0.004 0.022 0.034 0.014 0.022 0.017 0.021 0.028 0.127 0.035 0.051 0.033 0.028 0.027 0.023 0.029 0.005 0.005 0.002 0.003 0.079 0.023 0.003 0.011 0.003 0.002 0.002 0.001 0.001 0.001 0.037 0.187 0.061 0.001 0.001 0.001 0.002 0.001 0.016 0.026 0.014 0.021 0.025 0.038 0.021 0.030 0.026 0.029 0.027 0.022 0.014 0.005 0.004 0.005 0.010 0.000 0.037 0.015 0.006 0.005 0.011 0.012 0.017 0.021 0.016 0.029 0.002 0.010 0.082 0.022 0.013 0.001 0.001 0.003 0.000 0.001 0.000 0.000 0.001 0.003 0.055 0.002 0.037 0.052 0.033 0.059 0.077 0.062 0.029 0.069 0.080 0.056 0.142 0.010 0.026 0.011 0.009 0.016 0.013 0.012 0.016 0.023 0.032 0.041

EU sectoral competitiveness indicators 74 Table IV.25: Output multiplier Branch AT BE DE DK ES FI IT NL SE UK Mean Mining products 1.6347 1.6112 1.9185 1.1521 1.6603 1.9232 1.4418 1.2158 1.6827 1.5877 1.5828 Food products and beverages 2.0327 1.9873 2.0772 2.0913 2.3424 2.3651 2.0349 1.8918 2.1169 2.1886 2.1128 Tobacco products 1.5891 1.5079 1.7823 1.4446 1.9861 1.6510 1.3705 1.3785 1.4950 1.6948 1.5900 Textiles 1.4770 1.6690 1.6882 1.5257 1.7137 1.4774 1.8270 1.5080 1.5096 1.6901 1.6086 Clothing 1.4070 1.5378 1.5905 1.5581 1.9823 1.5638 2.0119 1.3643 1.4846 1.5840 1.6084 Leather and footwear 1.4413 1.5927 1.7316 1.5029 2.4377 1.5649 1.9398 1.6420 1.8647 1.7769 1.7495 Wood and products of wood 1.8869 1.8431 1.9518 1.6098 1.9165 2.1393 1.8411 1.5308 1.9739 1.9354 1.8628 Pulp, paper and paper products 1.7313 1.5866 1.7172 1.5593 1.6862 1.9896 1.9740 1.4999 1.8208 1.7256 1.7291 Printing and publishing 1.6059 1.7915 1.8098 1.8015 2.0918 1.9680 1.8111 1.6149 1.9130 1.7014 1.8109 Mineral oil refining and nuclear fuel 1.3635 1.4794 1.2487 1.7120 1.3248 1.1903 1.2854 1.2346 1.2752 1.9481 1.4062 Chemicals 1.6025 1.4477 1.7218 1.5951 1.7967 1.6468 1.6091 1.6246 1.5488 1.7404 1.6334 Rubber and plastics 1.4313 1.6784 1.6916 1.4575 1.6102 1.6027 1.7212 1.5210 1.5985 1.7658 1.6078 Non-metallic mineral products 1.7286 1.7665 1.8400 1.5991 1.9087 1.7703 1.8946 1.6458 1.7262 1.7885 1.7669 Basic metals 1.6475 1.5106 1.7600 1.5719 1.9760 1.8662 1.8724 1.4950 1.7810 1.9341 1.7415 Fabricated metal products 1.6112 1.7088 1.7994 1.5373 1.8992 1.7726 1.8882 1.7042 1.7180 1.8089 1.7448 Machinery n.e.c. 1.5073 1.6737 1.7588 1.5523 1.8424 1.7682 1.9140 1.6330 1.6627 1.8163 1.7129 Office machinery 1.6244 1.1942 1.5285 1.4235 1.6534 1.3928 1.3226 1.5365 1.6017 1.6404 1.4918 Electrical machinery n.e.c. 1.4353 1.4094 1.7981 1.6254 1.8424 1.5355 1.8422 1.5785 1.6339 1.7725 1.6473 Radio, television and communication equipment 1.4214 1.4069 1.6987 1.4627 1.7224 1.7573 1.8696 1.5466 1.6973 1.6846 1.6267 Scientific and other instruments 1.4174 1.5539 1.6564 1.4493 1.6299 1.4525 1.6972 1.5659 1.5789 1.6741 1.5676 Motor vehicles 1.3842 1.4578 2.1262 1.5541 1.7552 1.4933 2.1989 1.6237 1.6996 1.8731 1.7166 Other transport equipment 1.5425 1.4521 1.4980 1.6475 1.6700 1.8565 1.6882 1.6787 1.6069 1.6837 1.6324 Furniture; manufactured goods n.e.c; secondary raw materials 1.6117 1.7558 1.7686 1.6312 1.9604 1.7734 2.0051 1.4982 1.8162 1.8303 1.7651 Electricity, gas and water 1.7603 1.5354 1.7089 1.5218 1.5420 1.5681 1.5509 1.8955 1.3628 2.0632 1.6509 Construction 1.5756 2.1781 1.8207 1.7863 2.0227 1.9316 1.8662 1.9002 1.6229 2.0714 1.8776 Sale and repair of motor vehicles; wholesale and retail trade 1.4940 1.7265 1.5591 1.5985 1.5044 1.5983 1.5828 1.4703 1.5110 1.7490 1.5794

Table IV.25 (cont.) Branch AT BE DE DK ES FI IT NL SE UK Mean Hotels and catering 1.6583 1.9570 1.8353 1.6554 1.8273 1.9590 1.7793 1.6453 1.7750 1.7000 1.7792 Inland transport 1.3781 1.7344 1.7549 1.6740 1.4668 1.3364 1.5906 1.4824 1.7022 1.8207 1.5941 Water transport 1.7149 2.0530 1.3086 1.1036 1.6737 1.3507 1.7297 1.4878 1.5461 1.7278 1.5696 Air transport 1.7720 2.1492 1.5935 1.9330 1.5731 1.7053 1.8113 1.5146 1.6560 1.6737 1.7382 Supporting transport activities 1.5977 1.9907 2.3137 1.5139 1.6624 1.6311 1.8366 1.7276 1.6791 2.0297 1.7982 Communications 1.1471 1.3189 1.4976 1.7293 1.2431 1.5400 1.5045 1.4630 1.6258 1.4995 1.4569 Financial intermediation 1.2872 1.3844 1.6062 1.4864 1.3037 1.3613 1.6409 1.4652 1.4653 1.6541 1.4655 Insurance and pension funding 1.4950 1.9288 2.1436 1.7236 1.9400 1.7474 1.9064 1.7010 1.4704 1.9786 1.8035 Auxiliary to financial intermediation 1.6336 1.7760 1.7628 1.7334 1.5930 1.6136 1.4684 1.3727 1.7257 1.7845 1.6464 Real estate services 1.4971 1.2896 1.3482 1.3234 1.3703 1.5407 1.2672 1.3617 1.4708 1.4211 1.3890 Renting of machinery 1.3689 1.6710 1.4628 1.8125 1.6307 1.5922 1.5848 1.5072 1.6667 1.7350 1.6032 Computer and related activities 1.6750 1.7138 1.3119 1.7883 1.4029 1.6230 1.5254 1.5230 1.7381 1.5503 1.5852 Research and development 1.3217 1.8173 1.6420 1.5311 1.4912 1.4896 1.4539 1.5638 1.6925 1.4369 1.5440 Other business activities 1.4221 1.7161 1.4140 1.6438 1.5532 1.6094 1.6455 1.5629 1.7895 1.6850 1.6041 Non-market services 1.3660 1.3777 1.3931 1.3933 1.3660 1.4502 1.5223 1.4524 1.5265 1.6575 1.4505 EU sectoral competitiveness indicators 75 Source: Calculated from Eurostat IO tables.

EU sectoral competitiveness indicators 76 higher output multipliers, while inputs imported are leakages in the output multiplication process. a labour skills by labour skills table which provides insight into the role of human capital. Table IV.25 shows high variation across countries, particularly as regards certain branches. For example, Germany and Italy exhibit a much higher output multiplier than the average in a sector like motor vehicles which exhibits high variation across countries: the output multiplier ranges from 1.3842 in Austria to 2.1989 in Italy. Another example of a branch with high variation across countries is leather and footwear, where the output multiplier ranges from 1.4413 in Austria to 2.4377 in Spain. IV.6. Concluding remarks This section, based on standard IO techniques, has shown that it is essential to consider the interrelationships and interdependencies that characterise different branches of the economy in order to have a more accurate understanding of the competitiveness of individual industries, and of the economy at large, as well as the associated strengths ands weaknesses. The discussion has been based on three types of IO tables for Germany, all based on data for 2000: Despite the high level of aggregation, especially in the sixbranch table, the discussion has singled out some important characteristics that deserve attention in industrial policy reflections. The data show the importance of external trade not only as a vehicle to satisfy consumer demand, but also as a way to provide domestic branches with access to more and better inputs. Supplier-user links, as captured by the intermediate transaction matrix, signal carriers of forces and weaknesses and, therefore, factors or obstacles to the competitiveness of industries. Finally, the data reveal clearly the importance of market services as suppliers of inputs to manufacturing industry, and the impact of manufacturing production on the rest of the economy. The IO tables for other EU Member States and the indicators derived from the more detailed IO tables (42 branches) show in more detail the characteristics of each branch and provide a basis for further analysis in this field. a traditional aggregation to six branches, which shows, among others, the relationship between manufacturing industry and market services; an ICT by ICT table which shows the role of ICT technology in the production process; and

EU sectoral competitiveness indicators 77 IV.7. Annex Sectoral classification in Eurostat input-output tables Code Homogeneous branch 01 Products of agriculture, hunting and related services 02 Products of forestry, logging and related services 05 Fish and other fish products; services of incidental fishing 10 Coal and lignite; peat 11 Crude petroleum and natural gas; services incidental to oil and gas extraction excluding surveying 12 Uranium and thorium ores 13 Metal ores 14 Other mining and quarrying products 15 Food products and beverages 16 Tobacco products 17 Textiles 18 Wearing apparel; furs 19 Leather and leather products 20 Wood and products of wood and cork (except furniture); articles of straw and plaiting materials 21 Pulp, paper and paper products 22 Printed matter and recorded media 23 Coke, refined petroleum products and nuclear fuels 24 Chemicals and chemical products 25 Rubber and plastic products 26 Other non-metallic mineral products 27 Basic metals 28 Fabricated metal products, except machinery and equipment 29 Machinery and equipment n.e.c. 30 Office machinery and computers 31 Electrical machinery and apparatus n.e.c. 32 Radio, television and communication equipment and apparatus 33 Medical, precision and optical instruments, watches and clocks 34 Motor vehicles, trailers and semi-trailers 35 Other transport equipment 36 Furniture; other manufactured goods n.e.c. 37 Recovered secondary raw materials 40 Electrical energy, gas, steam and hot water 41 Collected and purified water, distribution services of water 45 Construction work 50 Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of automotive fuel 51 Wholesale trade and commission trade, except of motor vehicles and motorcycles 52 Retail trade services, except of motor vehicles and motorcycles; repair services of personal and household goods 55 Hotels and restaurants services 60 Land transport; transport via pipelines services 61 Water transport services 62 Air transport services 63 Supporting and auxiliary transport services; travel agency services 64 Post and telecommunications services 65 Financial intermediation services, except insurance and pension funding services 66 Insurance and pension funding services, except compulsory social security services 67 Services auxiliary to financial intermediation 70 Real estate services 71 Renting of machinery and equipment without operator and of personal and household goods 72 Computer and related services

EU sectoral competitiveness indicators 78 Sectoral classification in Eurostat input-output tables (cont.) Code Homogeneous branch 73 Research and development services 74 Other business services 75 Public administration and defence services; compulsory social security services 80 Education services 85 Health and social work services 90 Sewage and refuse disposal services, sanitation and similar services 91 Membership organisation services n.e.c. 92 Recreational, cultural and sporting services 93 Other services 95 Private households with employed persons

Chapter V: Growth and productivity EU sectoral competitiveness indicators 79 V.1. Introduction This chapter presents a set of indicators about EU-15 sectoral growth and productivity. These indicators are value added in constant prices, employment, productivity per hour worked and unit labour costs (ULCs) over the period 1979 2001, as well as an indicator of profitability for a shorter period of time. First, stylised facts are presented across seven main sectors of the economy: agriculture, mining, manufacturing, electricity and water supply, construction, market services and non-market services ( 50 ). Then results of a cluster analysis based on 48 sectors are presented. Finally, gross operating rate, as indicator of profitability, is presented and discussed ( 51 ). The information incorporated in the text is completed by a series of graphs and tables annexed to this chapter, which show EU-15 performance relative to the United States ( 52 ). year, which has resulted in this sector doubling its output in constant prices over the period. It is also evident that during the whole period, market services is the only sector whose growth rate is higher than the average. The other sectors exhibit a stronger cyclical pattern and, with the exception of electricity, gas and water supply, which tracks closely the economy as a whole, growth rates are lower than those of the total economy, particularly in mining and construction. These developments have resulted in changes in the shares of the various sectors in total value added, as shown in Graph V.2 for the years 1979 and 2001. It is evident that the increase of 8 percentage points in the share of market services has taken place against a decrease in all the other sectors shares V.2. Growth and labour productivity in EU-15 The long-term evolution (1979 2001) of value added in constant (1995) prices, indexed to 1979 = 100, is shown in Graph V.1. Market services show the most dynamic path throughout 1979 2001 with positive growth rates every ( 50 ) Market services includes from ISIC Rev 3, item No 50, Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of automotive fuel, through item No 74, Other business activities. The range of non-market services is from Public administration and defence; compulsory social security (item No 75) through Other services activities (item No 93). ( 51 ) The gross operating rate is defined as the ratio operating surplus/turnover in percentage. ( 52 ) All the indicators in this chapter are calculated from the database presented in O Mahony and van Ark (ed., 2003), op. cit., footnote 2, except operating surplus rate, which is calculated from Eurostat s NewCronos database SBS (structural business statistics) domain.

EU sectoral competitiveness indicators 80 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Graph V.1: Index numbers of EU-15 value added in 1999 prices (1979 = 100) 210 TOTAL INDUSTRY 200 Mining and quarrying 190 Manufacturing 180 Electricity, gas and water supply 170 Construction 160 Market services 150 Non-market services 140 130 120 110 100 90 80 70 60 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 81 Graph V.2 EU 15 main sectors shares of total value added in 1995 prices (%) 60 1979 50 2001 40 30 20 10 0 Agriculture, forestry and fishing Mining and quarryng Manufacturing Electricity, gas and water supply Construction Market services Non-market services Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 82 (except electricity, gas and water supply). It is also interesting to note that the changes in shares calculated in constant prices are much less pronounced than those based on value added in current prices ( 53 ). Underlying this is the evolution of relative prices about which more will be said later. For purposes of comparison, Graph V.3 shows the shares of total value added in the United States. Here, the changes have been similar to those in the EU (with the exception of agriculture). The main difference is in the share of manufacturing which has not changed much between 1979 and 2001. Already in 1979 the share of this sector was 6 percentage points lower than in EU-15. As EU-15 has converged towards the United States, by 2001 the difference is only 2.9 percentage points. In fact, these are common trends to all countries, which converge (with an increasing share of market services and a diminishing share of manufacturing and, more recently, with a decreasing share of non-market services) towards profiles similar to those of the United States as the process of economic development advances. Moreover, despite declining manufacturing employment, value added in manufacturing, measured in constant prices, has been rising over time. Thus, the domestic supply of manufactured goods has been increasing, reflecting the sustained increase in productivity. This favourable performance in productivity of manufacturing relative to market services is shown in Graph V.4. Clearly, the benefits of increased productivity spread over the whole economy in different ways. For one, there is a transfer of labour to services activities, whose share in value added is increasing and where productivity growth has been substantially weaker than in manufacturing. Sustained productivity growth also makes possible a favourable evolution of unit labour costs in manufacturing, a key indicator of competitiveness ( 54 ). This evolution is shown in Graph V.5. In contrast, and partly as a result of slower productivity growth, ULCs in market services have evolved more adversely compared with ULCs in manufacturing. The stronger growth in manufacturing productivity and the weaker one in services have contributed to changing relative prices in favour of the former. Graph V.6 shows the evolution of prices in market services relative to manufacturing (= 100). The relative price is the ratio of two price indices, the value added deflator (1995 = 100) of manufacturing industry divided by the value added deflator (1995 = 100) of market services. Between 1979 and 2001 the relative price of manufactures (services) has evolved very favourably (unfavourably). In other words, the price of manufactured goods has declined relative to the price of market services. This underlies the fact noted earlier, that the share of manufactures in total value added in constant prices has decreased by three percentage points, while the decrease in current prices amounts to 8.5 percentage points. ( 53 ) In current prices the share of manufacturing has changed from 27.4 % in 1979 to 19 % in 2001 and the share of market services from 36.9 % in 1979 to 48.1 % in 2001. ( 54 ) Since data on production are not available, ULCs are labour costs per unit of value added, although, strictly speaking should be calculated per unit of final production.

EU sectoral competitiveness indicators 83 Graph V.3: US main sectors shares of total value added in 1995 prices (%) 60 50 40 30 20 1979 2001 prices. Moreover, the relative price of market services has increased significantly during this period, amounting to close to anywhere between 30 and 40 percentage points. The high rate of productivity growth experienced in the manufacturing sector has resulted in a favourable evolution of the relative price of manufacturing output via, among other channels, its impact on ULCs in manufacturing. These developments clearly suggest that the manufacturing sector has been able to provide the economy with relatively cheap (and high quality) inputs thus contributing to economic growth and competitiveness. 10 0 Agriculture, forestry and fishing Mining and quarryng Manufacturing Electricity, gas and water supply Construction Market services Non-market services Table V.1 provides a sectoral overview of value added in constant prices, employment and labour productivity per hour worked as average annual growth rates in each Member State ( 55 ). Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2. The relationship between productivity growth and changes over time in relative prices is shown in Graph V.7. The graph shows annual labour productivity growth over the period 1979 2001 on the horizontal axis. The variable on the vertical axis is the difference of the price of each sector relative to manufacturing in 1979 from its value in 2001. Thus, this difference provides a measure of how relative prices have changed over the period in question. It is clear that there is a negative relationship implying that high rates of productivity growth are negatively related to changes in relative V.3. Growth and labour productivity: a disaggregated perspective In the present section, data on growth (1979 2001) in value added, employment and productivity are discussed at a more detailed sectoral level. The approach is based on a hierarchical cluster analysis that has been carried out to identify groups of sectors that are similar in their growth profile. ( 55 ) It has to be noted that employment is measured by the number of persons employed, while productivity refers to productivity per hour worked.

EU sectoral competitiveness indicators 84 Graph V.4: EU-15 labour productivity per hour index (1979 = 100) 210 200 Manufacturing Market services 190 180 170 160 150 140 130 120 110 100 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2. 90 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

EU sectoral competitiveness indicators 85 Graph V.5: EU-15 ULCs per hour worked index numbers (1979 = 100) 260 240 Manufacturing Market services 220 200 180 160 140 120 100 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 86 Graph V.6: EU-15 relative prices (manufacturing = 100) 110 105 Market services 100 95 90 85 80 75 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2. 70

EU sectoral competitiveness indicators 87 Graph V.7: Labour productivity growth versus change in relative prices To complete this information, graphs for each of these indicators, which compare EU-15 and US respective performances, are presented in the annex. A sector s growth can be characterised by the growth in three variables, namely value added in constant prices, employment, and labour productivity. A classification of sectors, according to their growth profile, can be obtained from a cluster analysis based on the values of these three variables. The results are shown in Graph V.8 ( 56 ). The tree in this graph represents the hierarchical process of formation of sector clusters, from a situation where each sector is a cluster in itself, to the opposite extreme where one single cluster represents all sectors. The process of creation of clusters can be tracked by climbing the branches of the tree. For example, other electrical machinery and furniture; other manufacturing are the closest sectors and are joined at a distance of 0.02 to form a first two-sector cluster. Source: Calculated from O Mahony and van Ark (2003), op. cit., footnote 2. ( 56 ) Two methods have been used to create the clusters. In both cases the Euclidean distance and standardised data have been used. The first method is Ward s, a minimum variance method to form clusters. At each stage every possible combination of clusters is evaluated, and the cluster chosen is that which minimises the increase in the total error sum of squares over all clusters. For one given cluster the error sum of squares is defined as the sum of squared deviations from the cluster mean. The second method is complete linkage, according to which the distance between clusters is defined as that of the most distant pair of individuals (see Everitt, Brian S., Sabine Landau, and Morven Leese (2001), Cluster analysis, fourth edition, Arnold Publishers). The results of the two methods are robust, and only four sectors of cluster 1 obtained with the Ward method move to another cluster (cluster 2 ) when the complete linkage method is used. The rest of the clusters are equal. The results presented and discussed in this section are those obtained with the complete linkage method. This cluster analysis has been carried out with the data analysis software system Statistica Version 6, StatSoft, Inc. (2003).

EU sectoral competitiveness indicators 88 Table V.1: Average annual growth rate of value added in constant prices, employment, and labour productivity per hour (%) 1979 2001 AT BE DE DK ES FI FR EL VA L LP VA L LP VA L LP VA L LP VA L LP VA L LP VA L LP VA L LP Mining and quarrying 2.6 4.2 2.2 4.3 8.3 5.9 4.5 5.4 1.7 10.6 0.1 10.5 0.3 3.4 4.3 4.3 2.1 6.9 2.2 3.9 6.9 2.3 0.6 5.1 Manufacturing 3.2 1.2 5.0 2.7 1.6 5.1 1.4 1.0 2.7 1.6 0.7 2.7 2.9 0.4 3.7 4.2 0.8 5.3 1.1 1.4 3.1 0.9 0.3 1.5 Electricity, gas and water supply 2.9 0.2 3.6 2.2 1.0 4.0 1.3 1.2 3.1 1.7 0.3 1.7 3.4 0.1 3.8 3.0 1.8 5.4 4.4 0.5 4.4 4.4 1.7 3.4 Construction 1.5 0.1 2.3 0.9 0.6 2.1 0.2 0.4 0.0 0.4 0.7 1.2 3.2 1.4 2.3 0.4 0.2 0.7 0.1 1.1 1.4 0.8 0.1 1.0 Market services 3.2 1.5 2.4 2.4 0.9 2.2 3.6 2.1 2.4 2.0 0.8 1.5 2.6 2.1 0.9 3.3 0.9 2.5 2.9 1.5 2.0 3.3 2.3 1.3 Non-market services 1.5 1.9 0.2 1.7 1.3 1.1 1.9 1.8 0.8 1.4 1.0 0.5 3.1 3.0 0.4 1.8 1.4 0.3 2.2 1.9 0.9 1.6 3.1 1.2 IE IT NL PT SE UK LU EU-15 VA L LP VA L LP VA L LP VA L LP VA L LP VA L LP VA L LP VA L LP Mining and quarrying 2.2 2.5 6.1 0.8 1.6 2.9 0.1 0.7 0.3 5.2 0.5 6.3-0.3 3.7 3.3 1.3 7.1 10.3 5.8 1.0 8.4 0.1 5.0 5.7 Manufacturing 1.1 1.1 1.0 1.8 0.8 2.9 2.6 0.4 3.9 2.1 0.8 3.6 2.8 0.9 3.1 1.6 2.4 4.5 3.4 0.2 4.2 1.7 1.2 3.2 Electricity, gas and water supply 4.4 1.9 7.6 0.8 0.3 1.3 1.3 1.1 3.0 3.8 2.5 7.8 2.7 0.0 2.4 1.9 4.5 7.0 4.7 0.8 4.5 2.2 1.2 3.9 Construction 0.1 3.1 1.7 0.8 0.2 1.2 0.8 0.1 1.6 2.9 0.8 2.8 0.3 0.6 0.9 1.9 0.0 2.3 4.3 3.2 1.7 0.9 0.2 1.2 Market services 2.9 3.7 0.3 2.8 2.1 1.0 3.7 2.9 1.4 3.4 2.0 1.9 2.8 1.4 1.6 3.4 1.6 2.0 5.7 3.9 2.2 3.2 1.8 1.8 Non-market services 2.2 2.8 0.4 1.4 1.8 0.1 1.6 1.9 1.0 3.1 2.3 1.4 1.8 0.5 0.9 1.6 1.2 0.7 4.3 2.6 2.2 1.9 1.7 0.6 VA = value added in constant (1995) prices; L = employment; LP = productivity per hour worked. Source: Calculation based on data from O Mahony and van Ark (2003), op. cit., footnote 2. Similarly, sale and repair of motor vehicles and retail trade are very close to each other and form a two-sector cluster at a distance of 0.04. In the same way, the process continues, merging motor vehicles and aircraft and spacecraft, textiles and leather and footwear, and so on. At a given stage of the process, previously formed two-sector clusters merge with other single or two-sector clusters and form more complex upper level clusters. For example, at a distance of 0.09, sale and repair of motor vehicles-retail trade merges with insurance and pension funding, while metal products merges with other electrical machinery-furniture; manufacturing n.e.c. at a distance of 0.09. Clearly, climbing the branches implies accepting more heterogeneous clusters, in that the distance among the sectors within a cluster increases.

EU sectoral competitiveness indicators 89 Mining and quarrying Textiles Leather and footwear Clothing Building and repairing of ships Basic metal Food, drink and tobacco Fabricated metal products Other electrical machinery n.e.c. Furniture; manufacturing n.e.c. Motor vehicles Aircraft and spacecraft Wood and products of wood Mechanical engineering Non-metallic mineral products Printing and publishing Inland transport Construction Pulp, paper and paper products Electricity, gas and water supply Insulated wire Chemicals Radio and television receivers Water transport Other instruments Railroad and transport equipment n.e.c. Mineral oil refining and nuclear fuel Scientific instruments Rubber and plastics Sale and repair of motor vehicles Retail trade Insurance and pension funding Wholesale trade Financial intermediation Supporting transport activities Research and development Air transport Communications Telecommunication equipment Hotels and catering Auxiliary to financial intermediation Real estate activities Renting of machinery Legal, technical and advertising Other business activities n.e.c. Computer and related activities Office machinery Electronic valves and tubes Graph V.8: EU-15 sector growth clusters 9 8 7 6 Linkage distance 5 4 3 2 1 0 Source: Own calculations, based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 90 At a distance of 2.5 the clusters mining through basic metals and food and drinks through scientific instruments merge into a more heterogeneous cluster. Also, at certain distances the presence of outliers can be identified. For example, telecommunications equipment remains as a single-sector cluster until, at a distance of 2.3, it becomes a member of a larger cluster, along with the cluster rubber and plastics through communications. The cluster formation process ends when, at a distance of 8.1, one 48-sector cluster is formed. In Graph V.8 five large clusters are clearly identified ( 57 ). The first cluster groups sectors from mining and quarrying to basic metals. The second embraces sectors from food, drink and tobacco to scientific instruments, the third from rubber and plastic to telecommunications equipment, the fourth from hotels and catering to computer and related activities. Finally, office machinery and electronic valves and tubes are grouped in the fifth cluster. These clusters are formed by sectors that are close to each other in their performance in value added, employment and productivity growth, but to interpret the clusters it is necessary to see how these are characterised in terms of the values of these variables. This is done in Graph V.9 ( 58 ), which summarises the basic numerical information on the distribution of the scores of the sectors included in each of the clusters. This is a box-and-whisker graph, which shows the median, the quartiles, and the maximum and minimum value of the distribution of the three variables used. A point inside the box represents the median value for each factor. The upper and lower boundaries of the boxes represent respectively the upper and lower quartiles of the distribution. The whiskers (lines extending from the box) represent the non-outlier maximum and minimum values of the distribution. Hence, 50 % of the observations are within the range indicated by the box, and 25 % of the observations are respectively between the upper and lower borders of the box and the extreme point of the corresponding whisker. Furthermore, seven sectors appear as outliers and two as extreme values, which implies that these sectors are far from the upper and lower boundaries of the box ( 59 ). In Graph V.9 the first four growth sector clusters are clearly outlined. Cluster 1 (from mining and quarrying and textiles, through building and repairing of ships) is characterised by the poorest performance in terms of both output and employment growth. The median of its growth rate in value added is slightly below zero, and its performance ( 57 ) The number of clusters retained depends upon the distance chosen to cut the branches of the tree. To a large extent this is an arbitrary decision, which depends on the objective of the analysis and the interpretability of the results. An alternative would be to use information on the number of clusters that is known in advance, information not necessarily contained in the sample studied. ( 58 ) Cluster 5, which is characterised by growth rates of value added (29.9 and 33.3 %) and productivity (30.5 and 33.7 %) much higher than those in the other four clusters, is not represented in Graph V.9. For details on the deflators applied to ICT industries see O Mahony and van Ark (2003), op. cit. footnote 2, Chapter VII. ( 59 ) Strictly speaking in this graph a sector is characterised as outlier if the value in one variable is greater or lower than 1.5 (upper value of the box lower value of the box). Extreme values are those that are greater or less than 2 (upper value of the box lower value of the box).

EU sectoral competitiveness indicators 91 Graph V.9: EU-15 sector growth clusters Source: Own calculations, based on data from O Mahony and van Ark (2003), op. cit., footnote 2. in terms of employment is even worse ( 60 ). It is therefore formed by industries that have stagnated, or that exhibit very low growth rates, but which have undergone a process of adjustment resulting in high increase in productivity. The outlier in employment is mining and quarrying (5.2 % employment decline). Cluster 2, which encompasses a high number of manufacturing industries, exhibits, on average, relatively low, though positive, growth rates in value added, and poor performance in employment. Productivity growth is high, although on average inferior to that of Cluster 1. Clusters 3 and 4 are, with two exceptions ( rubber and plastics and telecommunications equipment in Cluster 3), formed by services sectors. Cluster 3 exhibits high growth rates in value added, positive, though relatively low, growth in employment, and consequently high increases in productivity. In this cluster it is worth mentioning the performance of telecommunications equipment, with high growth rates in value added (9.6 %) and productivity (11 %). Nevertheless, it must be noted that this is a cluster characterised by high variations across its member sectors, particularly in terms of value added growth. Finally, Cluster 4, from hotels and catering to computer and related activities, exhibits high rates of growth in output and employment, and the poorest performance in productivity ( 61 ). As indicated ( 60 ) It is important to underline that the point inside the boxes is the median of the distribution of values of the variable: half of the industries fall, respectively, above and below this value. ( 61 ) A formal non-parametric test (Mann-Whitney U test) to analyse whether the various pairs of clusters are statistically different has been run on the three variables. The conclusion is that all pairs of clusters are different, at least in two of the varia-

EU sectoral competitiveness indicators 92 above, Cluster 5 is not represented in Graph V.9. This cluster encompasses two sectors ( office machinery and electronic valves and tubes ), which exhibit very high growth rates in value added and productivity, and negative growth rates in employment. The complete list of sectors, grouped by cluster, is presented in Table V.2, along with their average annual growth rates in value added in constant (1995) prices, number of persons employed, and labour productivity per hour worked. Graph V.10 represents, for the first four clusters, the position of each industry in the space of the three variables used for creating the clusters. The two lines on the plane VA growth L growth sub-divide this into four regions, corresponding to combinations of positive and negative growth rates in value added and employment. The vertical axis measures labour productivity growth. V.4. Profitability Although profitability is a key indicator of competitiveness and success measurement issues make difficult the construction of appropriate indicators ( 62 ). The one presented in this section is gross operating rate, defined as gross operating surplus divided by turnover ( 63 ). Two remarks are worth noting here. First, it is an accounting rather than economic measure of profit; and, second, it does not take into consideration the stock of capital, which would be a more appropriate denominator in the expression of profit rate. In this sense it can be considered as an intermediate measure of profitability, which should ideally be adjusted for the ratio turnover/capital stock. The available data ( 64 ) cover the period 1995 2001, although country and industry coverage is uneven. The choice made here is to present EU-15 data for 1999 2001 and to calculate this indicator for a more reduced number of countries (EU- 12 from now on) for which information is available over 1996 2001 ( 65 ). The fact that Germany (data available only bles. More precisely, the similarities between pairs of clusters are as follows: in value added growth clusters 3 and 4; in employment: growth clusters 2 and 5, and 3 and 5; in labour productivity: clusters 1 and 2, 1 and 3, and 2 and 3. See: Hollander, Myles and Douglas A. Wolfe (1999), Nonparametric statistical methods, second edition, Wiley Interscience. ( 62 ) Indicators of profitability relevant for sustained economic growth should relate economic profit to the resources engaged in the production process (e.g. stock of capital). In any case, as regards the numerator, the appropriate figure should measure economic profit (where the relevant concept of cost is opportunity cost), as opposed to accounting benefit. The denominator chosen varies, in some cases under the constraint imposed by the information available. Including capital and reserves leads to a measure of the efficiency in the use of the funds invested by shareholders. Total assets is difficult to use, particularly at industry level, due to lack of appropriate measures of capital stock data. The use of turnover is an alternative frequently used at industry level. ( 63 ) Gross operating surplus is obtained by deducting intermediate inputs and labour costs from the value of turnover. This indicator is a price-cost margin, which has the advantage that it can be calculated from existing industrial statistics, and that it is a proxy for the Lerner index of market power, defined as (price marginal cost)/price. See, for example, Scherer and Ross (1990), Industrial market structure and economic performance, Houghton Mifflin, Boston. ( 64 ) The source used is Eurostat s NewCronos database (SBS domain). The data have been aggregated to make them correspond with the sectoral classification presented in Table III.A.2. ( 65 ) The basic set of 12 countries is: Belgium, Denmark, Spain, France, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Finland, Sweden, and the United Kingdom. However, the information is not available for all them. Table V.A.1 presents the countries actually included for each sector. The United Kingdom and Finland

EU sectoral competitiveness indicators 93 Table V.2: EU-15 industry growth clusters (average annual growth rates (%) 1979 2001) Sector Value added Employment Productivity Mining and quarrying 0.2 5.2 5.4 Electricity, gas and water supply 2.1 1.3 3.7 Textiles 0.8 3.2 2.6 Construction 0.8 0.2 1.2 Cluster 1 Clothing 0.2 3.5 3.4 Leather and footwear 1.1 3.3 2.4 Inland transport 2.3 0.2 2.6 Water transport 0.7 2.5 3.6 Cluster 2 Basic metals 0.7 3.1 4.1 Building and repairing of ships 0.1 3.3 3.6 Food, drink and tobacco 1.1 0.6 2.1 Wood and products of wood 1.1 1.0 2.4 Pulp, paper and paper products 2.0 1.0 3.3 Printing and publishing 1.6 0.1 2.1 Mineral oil refining and nuclear fuel 3.7 2.0 1.6 Chemicals 3.3 1.3 4.9 Non-metallic mineral products 1.0 1.3 2.7 Fabricated metal products 0.8 0.8 1.9 Mechanical engineering 0.6 1.1 2.0 Insulated wire 2.8 1.0 4.1 Other electrical machinery n.e.c. 0.5 0.7 1.5 Radio and television receivers 0.2 2.4 2.9 Scientific instruments 2.6 0.2 2.1 Other instruments 1.6 1.9 3.8 Motor vehicles 1.6 0.7 2.9 Aircraft and spacecraft 1.7 0.6 2.8 Cluster 3 Cluster 4 Rubber and plastics 2.4 0.6 2.1 Telecommunication equipment 9.6 1.3 11.0 Sale and repair of motor vehicles 1.9 0.9 1.4 Wholesale trade 2.7 1.1 2.2 Retail trade 2.1 1.0 1.6 Air transport 6.0 1.4 4.9 Supporting transport activities 3.7 1.3 2.9 Communications 6.3 0.3 6.5 Financial intermediation 3.2 1.1 2.6 Insurance and pension funding 2.2 1.1 1.7 Research and development 2.4 1.7 1.2 Hotels and catering 1.0 2.4 0.9 Auxiliary to financial intermediation 3.1 2.7 0.8 Real estate activities 2.5 3.4 0.5 Renting of machinery 5.3 3.4 2.2 Computer and related activities 7.6 6.5 1.5 Legal, technical and advertising 4.3 4.2 0.6 Other business activities n.e.c. 4.0 4.7 0.2 Railroad and transport equipment n.e.c. 1.0 2.1 3.4 Furniture; manufacturing n.e.c. 0.4 0.7 1.6 Cluster 5 Office machinery 29.9 0.6 30.5 Electronic valves and tubes 33.3 0.1 33.7 Source: Own calculations, based on data from O Mahony and van Ark (2003).

EU sectoral competitiveness indicators 94 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Graph V.10: EU-15 sector growth clusters VA : negative/employment: negative Productivity: high VA: positive-low/employment: negative Productivity: high VA: high/employment: positive-low Productivity: high VA: high/employment: high Productivity: positive-low Source: Own calculations, based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 95 for 1999 2001) is not included in EU-12 limits considerably the significance of the indicator, but it is important to track a longer period of time to show the fluctuations of this indicator ( 66 ). However, given the weight of Germany in manufacturing industry it is interesting to see Germany s performance relative to EU-12. Graph V.11 shows the average value of the gross operating rate for the period 1999 2001 in Germany and EU-12. Although strongly correlated, the gross operating rate is systematically lower in Germany, with the exception of office machinery. sectors, on the contrary, there is significant fluctuation: telecommunications equipment, aircraft and spacecraft, and railroad and other transport equipment are examples of this. The nature of the goods, their cyclical pattern and possible sector-specific shocks are, among others, factors that affect their profitability performance over time. The results are presented in Tables V.3 (EU-15) and V.4 (EU- 12). The short period used in Table V.3 makes it difficult to asses the evolution of profitability over time. Some sectors are worth mentioning since they exhibit substantial changes even within this short period of time. This is the case of electronic valves and tubes, telecommunications equipment, and radio and television receivers, and computer and related activities. A second aspect is the variation across sectors. The gross operating rate indicator varies markedly across sectors, indicating the influence of industry-specific factors ( 67 ). Table V.4 shows data for EU-12 and 1996 2001 for only manufacturing sectors. It is clear that for some sectors profitability does not change significantly over the period covered. This is the case of some consumption goods such as food, drink and tobacco, and clothing, but not only, since some capital goods producing sectors (e.g. mechanical engineering) also exhibit quite stable profitability ratios. In other 2000 data for food, drink and tobacco have been estimated on the basis of their share in the total aggregate in 2001. The same criterion (using 2000 shares) has been used to estimate Sweden 2001 data for electronic valves and tubes and telecommunication equipment. ( 66 ) Nevertheless, there is a high degree of correlation in levels between EU-15 and EU-12. The results for EU-12 for 1999 2001 have been compared, year by year, with those available for EU-15. The coefficient of correlation between EU-15 and EU-12 for the sample of manufacturing industries is 0.97, 0.98, and 0.95 respectively. This coefficient of correlation has been calculated in level terms, and indicates that the relative profitability of sectors in the two areas is similar, but does not capture properly the similarity (or absence of) over time. ( 67 ) Since the 1950s there has been extensive research on the factors determining the profitability rate, both at firm and industry level. This research has focused on the influence of factors such as concentration, risk, and barriers to entry. See, for example, Scherer and Ross: op. cit., footnote 63. The definition of gross operating rate makes this indicator sensitive to differences in capital intensity (see Section III.4). More precisely, high capital-intensive sectors will tend to display higher levels in the value of this indicator, which can explain, at least partially, the variation of profitability, as measured here, across sectors. In any case, the level of aggregation of the industry classification used matters in the analysis of profitability variation across sectors, since broadly defined industries do not conform to the definition of economically meaningful markets.

EU sectoral competitiveness indicators 96 Table V.3: EU-15 gross operating rate (%) Sector 1999 2000 2001 Mining and quarrying na 41.0 37.9 Food, drink and tobacco 9.3 9.4 9.2 Textiles 10.0 10.2 9.5 Clothing 8.3 9.3 9.8 Leather and footwear 9.7 9.2 10.0 Wood and products of wood 9.9 10.3 10.3 Pulp, paper and paper products 12.5 14.0 13.4 Printing and publishing 15.2 14.9 13.6 Mineral oil refining and nuclear fuel 4.9 6.2 5.0 Chemicals 12.9 13.0 12.4 Rubber and plastics 11.4 10.6 10.0 Non-metallic mineral products 14.3 14.1 13.4 Basic metals 7.8 9.2 7.0 Fabricated metal products 12.0 11.9 11.8 Mechanical engineering 8.3 8.8 8.7 Office machinery 7.3 6.0 4.6 Insulated wire 6.7 8.9 7.1 Other electrical machinery n.e.c. 8.3 9.7 6.7 Electronic valves and tubes 13.8 15.5 8.7 Telecommunication equipment 10.5 9.2 0.6 Radio and television receivers 5.4 6.3 2.6 Source: Eurostat NewCronos database (SBS domain). na: not available. Scientific instruments 10.7 12.6 12.5 Other instruments 11.7 13.6 14.7 Motor vehicles 4.6 4.0 4.9 Building and repairing of ships 7.8 6.6 7.5 Aircraft and spacecraft 12.8 11.2 11.2 Railroad and transport equipment n.e.c. 6.5 4.0 3.9 Furniture; manufacturing n.e.c. 10.1 10.7 10.4 Electricity, gas and water supply 22.1 18.4 18.5 Construction 10.4 na na Sale and repair of motor vehicles na na 5.8 Wholesale trade na na 5.0 Retail trade na na 7.8 Hotels and catering 17.5 na 17.1 Inland transport 12.6 na 14.9 Water transport 16.0 na 17.3 Air transport na na 3.3 Supporting transport activities na na 11.1 Communications 27.1 na 21.7 Real estate activities 81.9 na 39.7 Renting of machinery 55.0 na 40.3 Computer and related activities 22.4 na 12.6 Research and development 7.1 na na Legal, technical and advertising na na 22.0 Other business activities n.e.c. na na 14.5

Sector 1996 1997 1998 1999 2000 2001 Food, drink and tobacco 10.3 10.4 10.7 11.0 11.0 10.6 Textiles 10.1 10.6 10.6 10.4 10.6 9.9 Clothing 8.4 10.3 9.6 8.9 9.7 10.5 Leather and footwear 9.5 8.4 9.0 10.0 9.5 10.4 Wood and products of wood 9.1 11.4 11.2 11.0 11.2 10.7 Pulp, paper and paper products 12.4 13.5 13.3 13.2 15.1 14.2 Printing and publishing 12.7 14.4 14.5 15.8 15.3 14.4 Mineral oil refining and nuclear fuel 4.8 5.0 5.5 5.6 6.3 4.6 Chemicals 13.9 14.2 13.9 14.5 14.5 13.5 Rubber and plastics 12.1 12.1 12.3 11.8 11.3 10.7 Non-metallic mineral products 14.0 14.3 14.8 15.4 15.1 14.3 Basic metals 9.1 9.4 8.7 7.8 9.6 6.6 Fabricated metal products 12.1 13.1 13.6 13.2 12.7 12.5 Mechanical engineering 10.6 10.6 10.3 9.8 10.1 9.5 Office machinery 9.4 7.4 7.4 6.7 5.5 4.7 Insulated wire 11.5 10.5 8.8 8.1 10.0 5.9 Other electrical machinery n.e.c. 10.5 11.8 11.0 10.0 10.9 9.4 Electronic valves and tubes 10.5 14.3 11.1 13.9 15.8 11.5 Telecommunication equipment 9.7 15.2 11.3 12.4 10.7 3.4 Radio and television receivers 5.9 7.5 5.5 6.1 6.2 6.6 Scientific instruments 12.0 12.8 12.0 12.3 13.5 13.1 Other instruments 13.9 15.5 13.5 12.9 13.4 13.5 Motor vehicles 6.6 7.5 7.6 5.5 5.7 5.3 Building and repairing of ships 6.0 5.1 6.0 8.2 7.5 8.1 Aircraft and spacecraft 3.3 7.5 na 13.1 11.3 11.0 Railroad and transport equipment n.e.c. 6.0 8.7 na 8.6 4.8 4.1 Furniture; manufacturing n.e.c. 10.0 10.7 11.3 10.9 11.4 11.1 EU sectoral competitiveness indicators 97 Table V.4: EU-12 gross operating rate in manufacturing (%) Source: Calculated from Eurostat NewCronos database (SBS domain).

EU sectoral competitiveness indicators 98 Graph V.11: Gross operating rate in EU-12 and Germany (average 1999 2001) Source: Calculated from Eurostat NewCronos database (SBS domain).

EU sectoral competitiveness indicators 99 V.5. Concluding remarks Although competitiveness is a multidimensional concept, productivity exerts a crucial influence in determining growth and performance of an industry. Broadly speaking, favourable developments in manufacturing productivity relative to market services have resulted in favourable developments in unit labour costs and ultimately in relative prices. Productivity growth has made it possible for manufacturing industries to supply high quality intermediate inputs and capital goods to other manufacturing industries and to services activities, and goods for final demand, and at decreasing relative (to service industries) prices. Data for seven main sectors (from agriculture to non-market services), encompassing all economic activities, have been used but the discussion has focused on manufacturing and market services. Cluster analysis has identified five main growth clusters of industries characterised according to their performance in value added, employment and productivity growth.

EU sectoral competitiveness indicators 100 V.6. Annexes Graph V.A.1: EU-15 and US value added average annual growth rate (%) 1979 2001 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 101 Graph V.A.2: EU-15 and US employment average annual growth rate (%) 1979 2001 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 102 Graph V.A.3: EU-15 and US labour productivity per hour worked average annual growth rate (%) 1979 2001 Source: Based on data from O Mahony and van Ark (2003), op. cit., footnote 2.

EU sectoral competitiveness indicators 103 Table V.A.1: Countries included from Table V.4 Sector Countries included Comments Food, drink and tobacco BE, DK, ES, IE, IT, PT, FI, UK Textiles BE, DK, ES, FR, IE, IT, LU, NL, AT, PT, FI, SE, UK Clothing BE, DK, ES, FR, IE, IT, LU, NL, AT, PT, FI, SE, UK Leather and footwear BE, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Wood and products of wood BE, DK, ES, FR, IE, IT, LU, NL, AT, PT, FI, SE, UK Pulp, paper and paper products BE, DK, ES, FR, IE, IT, NL, AT, PT, FI, SE, UK Printing and publishing BE, DK, ES, FR, IE, IT, NL, AT, PT, FI, SE, UK Mineral oil refining and nuclear fuel BE, ES, FR, IT, LU, NL, PT, FI, SE, UK Chemicals BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Rubber and plastics BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Non-metallic mineral products BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Basic metals BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Fabricated metal products BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Mechanical engineering BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Office machinery BE, DK, ES, FR, IE, IT, NL, PT, FI, SE, UK Insulated wire BE, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Other electrical machinery n.e.c. BE, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Electronic valves and tubes BE, DK, ES, FR, IE, IT, NL, PT, FI, SE, UK Telecommunication equipment BE, DK, ES, FR, IE, IT, PT, FI, SE, UK Radio and television receivers BE, DK, ES, FR, IE, IT, PT, FI, SE, UK Scientific instruments BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK NL excludes Manufacturing of medical and surgical equipment DK excludes Manufacturing of industrial process control equipment Other instruments BE, ES, FR, IT, NL, PT, FI, SE, UK Motor vehicles BE, DK, ES, FR, IE, IT, NL, PT, FI, SE, UK Building and repairing of ships BE, DK, ES, FR, IE, IT, LU, NL, PT, FI, SE, UK Aircraft and spacecraft BE, ES, FR, IT, PT, FI, UK Railroad and transport equipment n.e.c. BE, ES, FR, IT, PT, FI, UK Furniture; manufacturing n.e.c. BE, ES, FR, IT, LU, NL, AT, PT, FI, SE, UK AT and FR exclude Recycling

EU sectoral competitiveness indicators 105 Chapter VI: External trade VI.1. Introduction The present section analyses EU-15 industries performance in external trade ( 68 ). The importance of the analysis of external trade is twofold. First, while other forms of internationalisation of economic activities (e.g. foreign direct investment) are important, exports account, on average, for 17 % of total manufacturing production, and this percentage is substantially higher for some industries ( 69 ). This underscores the importance of external markets as a destination of domestic production. Second, performance in external trade provides insight into various factors determining trade patterns, and reveals EU-15 industries competitiveness. This chapter is organised as follows. Section VI.2 provides an overview of world trade using a trade matrix, where the world is divided into 10 geographical regions. Section VI.3 analyses EU-15 external trade performance on the basis of various indicators including an index of revealed comparative advantage (RCA). Section VI.4 reviews the nature of EU-15 external trade flows by distinguishing between intraindustry trade (IIT) and inter-industry trade. A world trade matrix, which shows trade between four groups of countries clustered according to their income per capita ( 70 ) is presented and EU-15 IIT is measured and discussed. This provides insight into the factors that play a role in external trade and the nature of threats and challenges that EU-15 could be facing. Section VI.5 looks into the composition of EU-15 trade by labour skill and technology categories and presents the RCA index for these categories of products. Finally, Section VI.6 concludes. The annexes present a series of tables and graphs that complement this information focusing mainly on trade by groups of products. VI.2. World trade structure EU-15 s place in world trade of manufactured goods is presented in Table VI.1 ( 71 ). The data show that EU-15 is a major ( 68 ) The section focuses on trade in manufactured goods. With some exceptions the importance of external markets for services is much lower, as shown in Section IV.5. ( 69 ) See the ratio exports/production in Graph VI.A.1. The numerator of the ratio (exports) is calculated from data on products while the denominator production is calculated from data on economic activities. Therefore, strictly speaking, they are not fully comparable and the results have to be taken as an indication of the importance of exports by sector. ( 70 ) The matrices presented in this section refer to total manufacturing products trade. ( 71 ) The matrix does not include crude oil and other products from mining and quarrying. The matrix has been calculated from export data. Exporting regions are presented in rows and importing regions are presented in columns. The values on each cell are percentages on total world trade: the intercept of row i and column j measures exports from region i to region j. The main diagonal of the matrix (shaded cells) represents intra-region trade (e.g. exports from EU countries to EU countries). The list of countries included in each region is in Annex VI.7.1.

EU sectoral competitiveness indicators 106 Table VI.1: Manufactured products world trade matrix (%) 2001 EU-15 Other EU-25 Other western Europe Central and eastern Europe North America Latin America Middle East Asia Oceania Africa Total EU-15 28.7 2.2 1.8 1.3 5.0 1.1 1.1 2.8 0.4 1.2 45.6 Other EU-25 2.0 0.4 0.1 0.2 0.1 0.0 0.0 0.1 0.0 0.0 2.8 Other western Europe 1.4 0.1 0.0 0.1 0.3 0.1 0.1 0.3 0.0 0.0 2.3 Central and eastern Europe 0.9 0.1 0.0 0.4 0.2 0.0 0.1 0.2 0.0 0.1 2.1 North America 3.3 0.1 0.2 0.1 7.2 3.0 0.4 2.8 0.3 0.2 17.6 Latin America 0.6 0.0 0.0 0.1 3.7 1.0 0.0 0.2 0.0 0.1 5.8 Middle East 0.2 0.0 0.0 0.0 0.3 0.0 0.1 0.2 0.0 0.0 0.9 Asia 3.9 0.2 0.1 0.2 6.2 0.7 0.7 8.7 0.5 0.3 21.4 Oceania 0.1 0.0 0.0 0.0 0.2 0.0 0.0 0.4 0.1 0.0 0.8 Africa 0.4 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.0 0.1 0.7 Total 41.5 3.1 2.4 2.4 23.2 5.9 2.5 15.7 1.3 2.0 100 Source: Calculated from the Comtrade database. player: exports originating in EU-15 countries, including intra-eu-15 trade, account for 45.6 % of total world exports. Trade within the EU-15 internal market is also important since 28.7 % of total world trade takes place between EU-15 countries. Asia and North America are the two other main players. Altogether EU-15, North America and Asia account for 85 % of total world trade flows. Furthermore, trade between contiguous regions is also important, and reflects factors such as distance between trading partners, transport costs, and the existence of common borders. The North America-Latin America block s share in total world trade is 15 % while Europe (the four regions into which the continent is divided) accounts for 39.7 % of total world trade flows. Export destination and import origin, excluding intraregion trade, are presented in Tables VI.2 and VI.3. The main destination of EU-15 exports is North America (29.4 %) and Asia (16.8 %). Moreover, exports to the three European regions other than EU-15 shown in the table account for the major part (32.2 %) of EU-15 exports. Similar patterns characterise the origin of imports. The main origin of EU-15 imports is Asia (30.5 %) and North America (25.9 %) while imports from the rest of Europe as a whole account for 33.5 %.

EU sectoral competitiveness indicators 107 Table VI.2: Manufactured products world trade matrix Export destination 2001 EU-15 Other EU-25 North America Latin America Other western Europe Central and eastern Europe Middle East Asia Oceania Africa Total EU-15 13.3 10.9 8.0 29.4 6.5 6.2 16.8 2.1 6.9 100 Other EU-25 81.3 2.2 7.3 4.5 0.7 0.9 2.2 0.1 0.7 100 Other western Europe 63.7 2.9 2.2 12.4 2.9 2.5 11.1 0.9 1.4 100 Central and eastern Europe 52.8 9.0 2.0 10.3 2.0 6.6 13.0 0.1 4.2 100 North America 31.9 0.6 2.3 1.4 28.7 3.4 26.9 2.7 2.1 100 Latin America 12.5 0.2 0.7 1.1 78.0 1.0 4.9 0.2 1.3 100 Middle East 25.3 1.7 1.5 2.9 36.9 3.1 23.4 1.6 3.8 100 Asia 30.7 1.3 1.0 1.5 48.8 5.2 5.1 3.8 2.6 100 Oceania 17.1 0.3 0.6 0.5 22.0 2.9 6.6 48.3 1.9 100 Africa 63.6 0.4 1.9 1.4 10.0 2.4 3.9 14.2 2.0 100 Source: Calculated from the Comtrade database. In addition to Tables VI.1, VI.2 and VI.3, the pattern of trade can be categorised according to regions comprising countries of similar levels of development. These trade matrices are presented in Section VI.4 below. VI.3. EU-15 sectoral performance and revealed comparative advantage This section discusses the EU performance in external trade using an index of revealed comparative advantage (RCA) and an index of relative trade balance (RTB). The RCA index compares EU-15 exports, both total and for a specific industry, with those of a reference area. Values higher (lower) than 1 imply that EU-15 (or a given industry) performs better (worse) than the reference area, and are interpreted as a signal of comparative advantage. The RCA indicator is used to rank EU-15 products according to their comparative advantage. The RTB is used to measure performance developments over time. The RTB index compares the trade balance (exports minus imports) for a group of products to the total trade (exports plus imports) of that group of products. These two indicators are used to describe EU competitiveness in external trade in goods.

EU sectoral competitiveness indicators 108 Table VI.3: Manufactured products world trade matrix Import origin 2001 EU-15 Other EU-25 Other western Europe Central and eastern Europe North America Latin America VI.3. EU-15 sectoral performance and revealed com This Middle section East discusses Asia the Oceania EU performance Africa in external tr comparative advantage (RCA) and an index of relative trade EU-15 EU, i (2 XW, i These two indicators are i i = (3 82.5 78.1 67.5 31.0 22.3 The RCA index compares EU-15 exports, both total and for 44.5 40.4 29.8 60.1 a reference area. Values higher (lower) than 1 imply tha Other EU-25 15.6 2.3 9.0 0.7 0.4 performs 1.0 better (worse) 0.8 than the reference 0.2 area, 0.9and are inter Other western Europe 11.2 2.4 2.5 1.7 advantage. The RCA indicator is used to rank EU-15 produc 1.3 2.4 3.6 1.6 1.6 advantage. The RTB is used to measure performance dev Central and eastern Europe 6.7 5.4 1.4 1.0 0.7 index compares 4.5 the trade 3.0 balance 0.2 (exports minus 3.5 imports) fo North America 25.9 2.5 10.1 7.1 60.6 trade (exports 15.0 plus 40.0 imports) of 24.0 that group of 11.3products. Th VI.3. EU-15 sectoral performance and revealed comparative advantage describe EU competitiveness in external trade in goods. Latin America 4.7 0.4 1.5 2.7 23.5 2.1 3.3 1.0 3.3 Middle East This section discusses 1.5 the EU 0.5 performance 0.5in external 1.1 trade using 1.8 an index of 0.5 The RCA indicator for revealed 2.6product i 1.0 is defined as 1.5 follows: Asia comparative advantage 30.5 (RCA) and 6.2 an index of 5.4relative trade 9.5 balance (RTB). 38.9 13.5 27.5 X 41.0 17.0 Oceania The RCA index compares 1.0 EU-15 0.1exports, both 0.2 total and for 0.2 a specific 1.0 industry, with 0.4those of 2.0 X EU, i 5.0 0.7 i Africa a reference area. Values 3.0 higher 0.1(lower) than 0.5 1 imply 0.4 that EU-15 0.4 (or a given 0.3industry) RCAi = 1.0X 1.2 1.0 W, i Total performs better (worse) than the reference area, and are interpreted as a signal of comparative 100 100 100 100 100 100 100 advantage. The RCA indicator is used to rank EU-15 products according to their comparative i 100 100 100 Source: Calculated from the Comtrade advantage. database. The RTB is used to measure performance developments over time. The RTB index compares the trade balance (exports minus imports) for a group of products to the total trade (exports plus imports) of that group of products. describe EU competitiveness in external trade in goods. used to where X = value of exports; the reference area (world) is EU the list in the annex); the source used is the UN Comtrade dat The RCA indicator for product The RCA indicator i is defined for product as follows: i is defined as follows: The RTB indicator for product i is defined as follows: The RTB indicator for product i is defined as follows: X EU, i ( X M ) X EU, i RTBi i RCAi = X W, i (2) ( X i + M i ) XW, i i where X = value of exports and M = value of imports where X = value of exports and M = value of imports where X = value of exports; the reference area ( world ) is This indicator is based This on indicator EU-15 is trade based with on EU-15 the trade rest with of the rest of the EU-15 plus 93 other countries (see the list in the annex); the world. The source of the Eurostats data Comext is Eurostat s database. Comext database. database. EU-15 products are ranked according to RCA in Graph VI.1 where X = value of exports; the reference area (world) is EU-15 plus 93 other countries (see source used is the UN Comtrade the list in the database. annex); the source used is the UN Comtrade The RTB indicator for product i is defined as follows: the average of years 2000, 2001 and 2002. Information is al the name of each industry), about the share, in percentage

EU sectoral competitiveness indicators 109 EU-15 products are ranked according to RCA in Graph VI.1. The RCA values correspond to the average of years 2000, 2001 and 2002. Information is also provided (in parentheses after the name of each industry), about the share, in percentage, of the industry in EU-15 total manufacturing exports in 2002, and the category in the labour skill taxonomy to which each product belongs ( 72 ). Products ( 73 ) in the top of the ranking are characterised by a high RCA. Although the intervals for classifying sectors are arbitrary, the following six are top products in EU-15 performance: mechanical engineering, chemicals, non-metallic mineral products, aircraft and spacecraft, printing and publishing, and scientific instruments. All together, these account for 42 % of total manufacturing exports, although mechanical engineering and chemicals alone account for 31 %. Eight products find themselves at the bottom of the graph: radio and television receivers, clothing, electronic valves and tubes, office machinery, wood and products of wood, railroad and other transport equipment, basic metals, and other instruments. Yet, it should be stressed that some of these products have recorded steady and significant improvement in performance, as will be shown below. Finally, the value of the index for some products is close to 1, showing neither comparative advantage nor disadvantage. Examples of these products are: pulp, paper and paper products, rubber and plastics, motor vehicles, and telecommunications equipment. The relative trade balance (RTB) indicator, shown in Graph VI.2, presents the evolution of industry performance between 1989 and 2002 ( 74 ). The strong competitiveness performance of chemicals is confirmed by the positive, although modest, evolution of its RTB index. The same applies to scientific instruments and aircraft and spacecraft. Nonmetallic mineral products have followed the opposite direction with a steady deterioration of RTB between 1989 and 2002. The position of mechanical engineering has not changed substantially. As for the products performing less well, the RTB indicator confirms the poor performance of clothing. However, others have improved their position, particularly wood and products of wood, electronic valves and tubes, but also, although to a lesser extent, office machines and radio and television receivers. ( 72 ) HS = high labour skills; HIS = high-intermediate labour skills; LIS = low-intermediate labour skills; LS = low labour skills. ( 73 ) Products and groups of products are indistinctively used throughout the text, although the second expression ( group of products ) would be more appropriate given the high level of aggregation used in presenting these results. The data, originally presented according to the SITC (Standard International Trade Classification) or CPA (Statistical Classification of Products by Activity in the European Economic Community), have been converted to ISIC Rev. 3. Furthermore, the headings used for products in the graphs of this chapter are those of the ISIC Rev. 3 category (used in Chapters III and V) to which they are linked. Nevertheless, it has to be underlined that these data are on products and, strictly speaking, do not correspond to trade by economic activities. ( 74 ) RCA and RTB are positively correlated. The coefficient of correlation is 0.78, and highly significant. Due to a lack of data, RCA cannot be calculated for the same reference area for 1989. The evolution of products performance over time is therefore based on RTB. In this respect, it is worth mentioning that the weak performance of radio and television receivers in RCA (Graph VI.1) is confirmed by the RTB indicator (Graph VI.2).

EU sectoral competitiveness indicators 110 Graph VI.1: EU-15 trade in manufactured products Revealed comparative advantage index (average 2000 02) Source: Calculated from the Comtrade database.

EU sectoral competitiveness indicators 111 Graph VI.2: EU-15 external trade of manufactured goods (X M)/(X + M) Source: Calculated from Eurostat data: European business facts and figures (2003 edition) and Comext database.

EU sectoral competitiveness indicators 112 VI.4. Intra-industry trade (IIT) Traditionally the analysis of external trade has focused on countries exchanging products of different industries (interindustry trade) reflecting different factor (labour and capital) endowments and technology. On this basis different countries export different goods: for example, chemicals for textiles or motor cars for food. In Section VI.2 the international trade network has been presented as being composed of trade flows between geographical regions. However, income per capita of countries plays an important role to determine trade patterns, and in fact an important part of trade takes place between similar countries of comparable levels of development which exchange similar products (intra-industry trade). This section reviews EU-15 trade with groups of countries of comparable income per capita, highlights the role of this variable, and explores the dichotomy intra-industry trade/inter-industry trade. IIT has implications for understanding a nation s trade and for developing appropriate policies. Table VI.4 shows data on EU trade based on the per capita income level of partner countries ( 75 ). This world trade matrix shows trade flows between five groups of countries (EU-15 and the rest of the world divided into four income per capita groups). differences in technology and factor endowments lead countries to specialise in activities in which they have comparative advantage and explains inter-industry trade (e.g. cars for clothing). While trade between different countries (e.g. high and upper-medium-income countries on one hand, and low and low-medium-income countries on the other) can be expected to consist, to a large extent, of exchange of different goods, the intense exchange of goods between high-income countries suggests a different pattern of trade. IIT also involves trade between high-income and lower-income countries, as well as between lower-income countries themselves. Some relevant data are presented below. Some remarks are necessary when intra-eu trade is excluded from the data. While the largest share of EU-15 trade (both exports and imports) concerns trade with high and uppermedium-income countries, low-medium-income countries take a significant place among EU-15 trade origin and destination (Tables VI.5 and VI.6). Some 56.6 % of extra-eu exports go to other high-income countries, and 55.5 % of imports originate from these. However, 21 % of extra-eu exports are destined to low-medium-income countries, and 22 % of imports originate from these too. The data suggest a mix of trade consisting of exchange of similar and different goods between similar and different countries in terms of income level (see the discussion below). Table VI.4 shows that 61.7 % of total world trade takes place among EU-15 and high-income countries. If upper-medium countries are included, this percentage rises to 76.7 %. The ( 75 ) The classification used is from the World Bank. The list of countries is presented in the annex.

EU-15 28.7 9.5 3.1 3.6 0.6 45.6 High non-eu-15 7.1 16.4 4.1 3.8 0.7 32.1 Upper medium 2.4 4.8 0.6 0.9 0.1 8.9 Low medium 2.8 5.9 1.0 1.4 0.5 11.6 Low 0.5 1.0 0.1 0.2 0.1 1.9 Total 41.5 37.7 8.9 9.9 2.0 100 EU-15 56.6 18.6 21.2 3.6 100 High non-eu-15 45.5 25.9 24.5 4.2 100 Upper-medium 29.5 58.5 10.4 1.6 100 Low-medium 27.8 58.1 9.5 4.6 100 Low 25.6 55.1 7.4 11.9 100 EU sectoral competitiveness indicators 113 Table VI.4: World trade matrix Income level 2001 EU-15 High non-eu-15 Upper-medium Low-medium Low Total Source: Calculated from the Comtrade database. Table VI.5: World trade matrix Income level: destination of exports 2001 EU-15 High non-eu-15 Upper-medium Low-medium Low Total Source: Calculated from the Comtrade database.

EU-15 High Uppermedium non-eu-15 EU-15 44.9 37.9 EU sectoral competitiveness different indicators goods between similar and different countries in terms of income level High (see the non-eu-15 55.5 114 48.9 discussion below). Upper-medium 19.0 22.7 Low-medium 21.9 27.7 11.6 Table VI.5: World trade matrix Income level: destination of exports 2001 Low 3.6 4.6 1.6 Table VI.6: World trade matrix Income level: origin of imports 2001 Total 100 100 100 EU-15 High Uppermediumedium Low Low- EU-15 High Low Upper-medium Source: Total Calculated from Low-medium the Comtrade database. non-eu-15 EU-15 56.6 18.6 non-eu-15 21.2 3.6 The most 100 widely used measure of IIT is the Grubel-Lloyd (G EU-15 High non-eu-15 45.5 25.9 24.5 44.9 4.2 product 100 i 37.9(where X and M stand 42.2 for exports and 32.4 imports, respe Upper-medium 29.5 58.5 10.4 1.6 100 High non-eu-15 55.5 48.9 45.2 35.4 Low-medium 27.8 58.1 9.5 4.6 100 Upper-medium Low 25.6 55.1 7.4 19.0 11.9 22.7 100 10.1 7.2 X i M i Low-medium Source: Calculated from the Comtrade database. 21.9 27.7 GLi = 1 11.6 25.1 (4) X i + M i Low 3.6 4.6 1.6 2.5 Total Table VI.6: World trade matrix Income level: 100 origin of imports 100 2001 100 100 100 Source: Calculated from the Comtrade database. EU-15 High Uppermedium sensitive to the level of product aggregation: it increases w Low-medium Low The values of the index range from 0 (no IIT) to 1 (all trade i non-eu-15 EU-15 44.9 37.9 42.2 without 32.4 necessarily implying trade in similar products. The in High non-eu-15 55.5 48.9 45.2 across 35.4 products and over time, but it can overstate the size of IIT Upper-medium 19.0 22.7 10.1 7.2 levels of IIT trade within a given group of products. Low-medium 21.9 27.7 11.6 25.1 Low 3.6 4.6 1.6 2.5 The GL index can be defined across products as follows: The most widely used Total measure of IIT is the 100 Grubel-Lloyd 100 The 100 GL index 100 can be defined 100 across products as follows: Source: Calculated from the Comtrade database. (GL) index. The GL index for product i (where X and M stand for exports and imports, The most widely respectively) used measure is defined of IIT is as the follows: GL = 1 (5) Grubel-Lloyd (GL) index. The GL index for ( X i M i ) product i (where X and M stand for exports and imports, respectively) is defined as follows: i ( X + M ) i i X i M i GLi = 1 (4) X i + M i In this section IIT is studied on the basis of EU-15 trade broken down into a total of 262 products. These are products The values of the index range from 0 (no IIT) to 1 (all trade is defined in terms of CPA (classification of products by activity) with nomenclature the level of aggregation, at four-digit level. The values of the index range from 0 (no IIT) to 1 (all trade is intra-industry). The index is intra-industry). The index is sensitive to the level of product sensitive to the level of product aggregation: it increases aggregation: it increases without with necessarily the level implying of aggregation, trade in similar without necessarily implying across trade products in similar and over products. time, but it The can overstate index the size The of IIT GL trade for and EU-15 can mask trade different with the four groups of countries in products. The index is useful for comparisons is useful for comparisons levels across of IIT trade products within and a given over group time, of products. but 2002 is presented in Graph VI.3, while Graph VI.4 shows it can overstate the size The of GL IIT index trade can be and defined can across mask products different as follows: the GL index for EU-15 trade with the four groups of countries and by the 27 groups of goods. levels of IIT trade within a given group of products. (X i M i ) i i

EU sectoral competitiveness indicators 115 Graph VI.3: GL index by income level of EU-15 trade partners 2002 in trade with high-income countries, although there are some exceptions concerning products such as leather and footwear and food, drinks and tobacco, which exhibit the lowest values in the GL index. Also, with low-income countries there are exceptions, but this group of countries accounts for a very low part of EU-15 trade. Source: Calculated from Eurostat s Comext database. As expected, the value of the GL index increases with the level of income of trade partners: 0.32 for trade with lowincome countries, 0.46 for trade with low-medium-income countries, 0.67 for trade with upper-medium-income countries, and 0.74 for trade with high-income countries. In other words, trade with industrialised countries is basically IIT, and inter-industry trade increases as the level of development of trade partners diminishes. The results of the cross-country grouping presented in Graph VI.4 confirm the prevalence of IIT across all products To the extent that inter-industry trade is determined by comparative advantage, it is the segment of products characterised by the lowest GL index values with low-intermediate-income countries that are exposed to the strongest threat. Examples are food, drink and tobacco, clothing and mechanical engineering. Nevertheless, in some products (e.g. insulated wire and electronic valves and tubes) the GL index with low-intermediate-income countries is nearly as high as with high-income countries. This suggests that IIT does not concern exclusively trade between high-income countries, and that low-intermediate-income countries play in some cases a dual role, competing with high-income countries in certain segments of the market. A more aggregated view of the nature of EU-15 trade with the four groups of countries is obtained by dividing the GL index into four intervals and distributing the total EU-15 trade (exports + imports vis-à-vis the rest of the world) over these intervals. This is shown, in percentages, in Graph VI.5. With high-income countries EU-15 trade is mostly IIT and with upper-medium-income countries follows the same pattern but with increasing participation of inter-industry trade. With low-income countries trade is basically inter-

EU sectoral competitiveness indicators 116 Graph VI.4: EU-15 IIT with partners by income level (GL index) 2002 Source: Calculated from Eurostat s Comext database.

EU sectoral competitiveness indicators 117 industry. The distinctive feature with low-intermediateincome countries is that the distribution is more uniform. Finally, the trade data in Graph VI.6 provide a measure of the main challenges and opportunities for EU-15 in international trade. The largest share of EU-15 total trade is with high-income countries exchanging similar goods. At the other end is trade with low-income countries which is basically inter-industry; it consists of the exchange of goods of different industries in which the level of wages plays an important role ( 76 ). However, the volume of trade with these countries, especially with low-medium-income ones, is, as expected, very low. Since trade with these countries is a mixture of intra-industry and inter-industry, it suggests a wide range of possibilities for both areas to gain from trade. As for the threat posed by low wage countries, it ought to be stressed that inter-industry trade accounts for only a low share of total EU-15 trade with the rest of the world. As trade in goods between industrialised countries is predominantly IIT and, thus, not uniquely caused by traditional comparative advantage, there is room for intervention to improve a nation s trade performance. IIT reflects economies of scale and differentiated products. Thus, it is possible that use of policies such as increasing the human capital, fostering product innovation to meet increasingly sophisticated demand, and facilitating the creation of industrial clusters (source of external economies of scale) should make it possible for EU-15 industries to take advantage of the possibilities opened by IIT trade, particularly with other developed countries and regions. An important implication of IIT relates to its effect on the allocation of resources in the economy. If trade is predominantly inter-industry then the reallocation of resources between industries in the event of a shock is more costly than when trade is predominantly intra-industry because resources would need to be reallocated within industries. One recent concern has been competition for EU-15 industries from low-intermediate-income countries. As noted previously, EU-15 trade with these countries has a dual nature in that it consists of both intra-industry and interindustry trade. This reflects the dual structure of some countries (China is a representative example) which are able to produce and export products based on low-wage comparative advantage and on standardised technology that permits product imitation ( 77 ). Section VI.5 shows that this dual structure is also reflected in the product mix that characterises EU-15 trade with these countries. VI.5. Labour skills and technology The ranking of products in Graph VI.1 is based on the comparative advantage as revealed by their performance in external trade. But this does not provide an explanation of the ( 76 ) A discussion of trade by labour skills categories is in Section VI.5. ( 77 ) In Gregory Chow s words, China exports shoes, clothing, sports equipment, toys and other goods that require inexpensive labour, which is plentiful in China. It needs to import computers, automobiles, and other capital-intensive products in exchange. China will soon export computers. See Gregory Chow (2002), China s economic transformation, Blackwell Publishers, Oxford. In his stylised discussion of the external trade factors that drive economic change shoes stands for any labour-intensive product and computers for any capitalintensive product.

EU sectoral competitiveness indicators 118 Source: Calculated from Eurostat s Comext database. Source: Calculated from Eurostat s Comext database. Graph VI.5: Distribution (%) of EU total trade (exports + imports) by GL index and income level of partners 2002 Graph VI.6: EU total trade (exports + imports) by GL index, and income level of partners (in 1 000 EUR) causes of this performance. The present section complements the discussion on intra-industry trade with evidence on the labour skills use of European industries. EU-15 exports and imports according to labour skills categories are presented in Graphs VI.7 and VI.8 ( 78 ). By considering the level of income of trading partners this approach can help identify segments of EU-15 trade that are most sensitive to threats from low-income countries. In all cases the largest share in EU-15 exports is based on low and intermediate-low labour skills products, although this share varies with the income level of the countries. Exports to low-income countries are concentrated (75 %) in low and low-intermediate labour skills products; with low-medium and upper-medium-income countries the share of high labour skills is higher, although the partici- ( 78 ) As in the rest of this chapter this refers to EU-15 trade with the rest of the world.

EU sectoral competitiveness indicators 119 pation of the two lowest categories of labour skills is still high (about 68 %). Finally, with high-income countries, the weight of higher labour skills is greater, and the distribution more balanced. For imports, the prevalence of low and intermediate-low labour skills dominates the data and the share of these categories of products is much higher for imports than for exports. The exception is imports from high-income countries from which the largest is imports of high-skill goods. These data raise the question as to what does the high share of products of low and low-intermediate skills in EU-15 exports suggest and what does it tell us about EU-15 comparative advantage against other groups of countries. To a considerable extent, the EU s export structure mirrors the production structure (see Table VI.7) of the EU manufacturing industry. Products of low and low-intermediate labour skills are a significant part of exports of manufactures because they are also a significant part of value added in manufacturing. Products of high labour skills account for 16 % of value added in manufacturing and for 27 % of exports of manufactures. But products of low and intermediate-low labour skills account for 77.8 % of value added and for 61.1 % of total exports. Hence, relative to the production structure, exports show a bias towards a greater content of labour skills. trade balance for all combinations of income levels and labour skills. The data show that as the income level of trade partners increases, the share of trade in products embodying higher levels of labour skills increases. This contributes to making the distribution of trade by labour skills more uniform. More than half of trade with lowincome countries is in products of low levels of labour skills and the distribution is notably skewed. With lowmedium and upper-medium-income countries the share of products of high labour skills is higher, although the participation of the two lowest categories of labour skills is still high (about 68 %). Finally, with high-income countries the largest share corresponds to products of high labour skills and the distribution is more uniform. This explains the sign of the relative trade balance (RTB) index. The trade balance of the EU with low and lowmedium-income level countries is clearly negative for products embodying low labour skills but notably positive for the other product categories with one exception: the trade balance for products of high skills against low-medium-income countries ( 79 ). Trade with high-income countries is evenly distributed between the two highest and the two lowest categories of labour skills and the trade balance is strongly positive for low labour skills products (0.302), and, to a lesser extent, lowintermediate labour skills. Table VI.8 summarises the composition of EU trade with the four groups of countries, and provides the relative ( 79 ) Although in relative terms the balance ( 0.055) is the smallest of all categories of products with these two types of countries.

EU sectoral competitiveness indicators 120 Low-intermediate skills Low skills Graph VI.7: EU-15 exports by income level of partners and labour skills category (1 000 EUR) 2002 Graph VI.8: EU-15 imports by income level of partners and labour skills category (1 000 EUR) 2002 160 000 000 140 000 000 High skills High-intermediate skills 120 000 000 100 000 000 80 000 000 60 000 000 40 000 000 20 000 000 0 High Upper-medium Low-medium Low Source: Calculated from Eurostat s Comext database. Source: Calculated from the Comext database. Table VI.7: Distribution of manufacturing industry value added by labour skills categories EU-15 United States Labour skills 1989 2001 1989 2001 High 15.2 15.9 22.4 25.4 High-intermediate 5.8 6.3 10 9.5 Low-intermediate 35.3 35.8 34.5 31 Low 43.7 42 33.1 34 Source: Calculated using data from O Mahony and van Ark (2003), op. cit., footnote 2.

Table VI.8: EU-15 trade by labour skills category and relative trade balance (%) 2002 Income level of EU-15 trade partner countries High Upper-medium Low-medium Low Labour skills Total trade (X M)/(X + M) Total trade (X M)/(X + M) Total trade (X M)/(X + M) Total trade (X M)/(X + M) High 31.4 0.011 26.1 0.062 25.5 0.055 20.2 0.395 High-intermediate 17.2 0.076 5.1 0.293 5.9 0.301 5.7 0.494 Low-intermediate 21.3 0.166 27.3 0.228 24.6 0.337 21.6 0.458 Low 30.1 0.302 41.6 0.005 44.0 0.259 52.5 0.418 Total 100 0.117 100 0.096 100 0.027 100 0.012 EU sectoral competitiveness indicators 121 Source: Calculated from Eurostat s Comext database. Table VI.9: RCA index in products by labour skills category (2002) Region by income level Products by labour skills category High High-intermediate Low-intermediate Low EU-15 0.920 1.144 1.209 0.907 High non-eu-15 1.051 1.331 0.984 0.899 Upper-medium 1.114 0.468 0.980 1.048 Low-medium 0.961 0.465 0.791 1.264 Low 0.678 0.252 0.620 1.610 Source: Calculated from the Comtrade database. The bilateral trade pattern vis-à-vis the four groups of countries can be better understood by looking at the RCA of each region for each of the four categories of products. This is shown in Table VI.9. The most significant cases can be mentioned here. Low-income countries exhibit high RCA in low skills (index value of 1.610) which corresponds to the negative trade balance of EU-15 with them. The same applies to low-medium-income countries (index value of 1.264). The best performance of EU-15 is in products of low-intermediate and high-intermediate labour skills. For the low and low-intermediate categories of products the RCA in EU-15 is higher than in other high-income countries, although the difference is negligible for low labour skills. Therefore, the strongest comparative advantage of EU-15 appears to be in

EU sectoral competitiveness indicators 122 products of high-intermediate and low-intermediate labour skills. It is important to note that the share of imports from low and low-intermediate-income countries in total EU-15 imports is low in percentage and therefore its impact on EU-15 labour markets (employment and wages), on average, may not be significant. It can nevertheless be more important in some specific industries characterised by inter-industry trade based on low labour skills products. Graph VI.9 shows developments in the relative trade balance (RTB) index over the period 1989 2002. Leaving aside the cyclical behaviour of the index, the improvement in the trade balance in product of high labour skills is evident. The deficits of the late 1980s and early 1990s have been reduced and since 1993 trade is balanced. It might be said that the EU is strengthening its position in international trade in these products. The prevalence of products of low and intermediate-low labour skills in EU-15 exports (they represent up to 61 % of total exports) raises the issue of the technology nature of the goods traded. Graphs VI.10 and VI.11, similar to those for labour skills, represent this situation. But, in contrast, the distribution of EU-15 exports is different from the one for labour skills. In this case it is skewed towards the highest levels of technology, and the largest share corresponds to medium-high technology products. As in the case of labour skills, a summary is provided in Table VI.10. The best EU-15 performance, across the four groups of countries, is achieved in medium-high technology products. It is clear that the EU-15 performance against each of the four trade partner regions shown in Table VI.10 is broadly consistent with the RCA index of the EU against these regions, as shown in Table VI.11. For example, the poor relative trade balance (RTB) of the EU against low-income, lowtechnology nations ( 0.6 in Table VI.10) is a reflection of the corresponding strong RCA index these nations exhibit (2.67 in Table VI.11). Note, however, that this correspondence does not always hold in the data under review. Finally, Graph VI.12 shows that since 1988, and as in the case of trade by products embodying various levels of labour skills, performance in high-technology products has been improving and the trade balance, though in deficit, has improved especially since 1992. About 67 % of EU-15 exports are of high and medium-hightechnology products, which may be inconsistent with the composition of EU trade by labour skills (of which the largest share corresponds to low and low-intermediate labour skills products). Two remarks can explain this apparently contradictory result. First, there is a correspondence between the two taxonomies for the highest (high technology = high and

EU sectoral competitiveness indicators 123 High Low Graph VI.9: EU-15 trade by labour skills categories (X M)/(X + M) 0.4 0.3 0.2 0.1 High-intermediate Low-intermediate 0 0.1 0.2 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source: Calculated from Eurostat data: European business facts and figures (2003 edition) and Comext database.

EU sectoral competitiveness indicators 124 Medium-low-tech Low-tech Source: Calculated from Eurostat s Comext database. Source: Calculated from Eurostat s Comext database. Graph VI.10: EU-15 exports by income level of partners and technology category (1 000 EUR) 2002 Graph VI.11: EU-15 imports by income level of partners and technology category (1 000 EUR) 2002 250 000 000 High-tech Medium-high-tech Medium-low-tech Low-tech 180 000 000 160 000 000 High-tech Medium-high-tech 200 000 000 140 000 000 120 000 000 150 000 000 100 000 000 100 000 000 80 000 000 60 000 000 50 000 000 40 000 000 20 000 000 0 High Upper-medium Low-medium Low 0 High Upper-medium Low-medium Low intermediate-high labour skills) categories and lowest (low technology = low and low-intermediate skills) categories. However, medium-high and medium-low technology is spread over the four categories of labour skills. Particularly, the largest part of medium-hightechnology products corresponds to low and lowintermediate labour skills products. Equally, the largest part of medium-low-technology products is mostly low labour skills. Table VI.12 shows the joint distribution of EU-15 exports on technology and labour skills categories. Secondly, as suggested in Chapter III, low labour skills products incorporate, both directly and indirectly, intermediate inputs from higher labour skills branches. This process of assembling high-technology intermediate in-

EU sectoral competitiveness indicators 125 Table VI.10: EU-15 trade by technology category and relative trade balance (%) 2002 Income level of EU-15 trade partner countries High Upper-medium Low-medium Low Technology level Total trade (X M)/(X+M) Total trade (X M)/(X+M) Total trade (X M)/(X+M) Total trade (X M)/(X+M) High-tech 35.7 0.081 20.5 0.079 20.6 0.005 15.5 0.431 Medium-high-tech 36.6 0.207 40.5 0.205 32.3 0.434 26.2 0.631 Medium-low-tech 12.2 0.157 18.1 0.044 17.5 0.288 13.3 0.196 Low-tech 15.5 0.326 20.9 0.056 29.6 0.393 45.0 0.600 Total 100 0.117 100 0.096 100 0.027 100 0.012 Source: Calculated from Eurostat s Comext database. Table VI.11: RCA index in products by technology category (2002) Region by income level Products by technology category High Medium-high Medium-low Low EU-15 0.861 1.174 0.950 0.878 High non-eu-15 1.117 1.134 0.929 0.682 Upper-medium 1.119 0.923 1.057 0.970 Low-medium 0.922 0.565 1.210 1.716 Low 0.467 0.364 1.030 2.665 Source: Calculated from the Comtrade database. puts by low skilled labour contributes to explain, at least partially, the apparent contradiction in question. VI.6. Concluding remarks EU-15 industry performance in external trade and competitiveness must be considered in the light of the pattern, characteristics and nature of trade with different partners.

EU sectoral competitiveness indicators 126 Graph VI.12: EU-15 trade by technology category (X M)/(X + M) 0.4 0.3 0.2 0.1 High Medium-high Medium-low Low 0.0 0.1 0.2 0.3 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source: Calculated from Eurostat data: European business facts and figures (2003 edition) and Comext database.

EU sectoral competitiveness indicators 127 Table VI.12: Distribution of EU-15 exports by labour skills and technology category (1 000 EUR) 2002 Skills Technology High High-intermediate Low-intermediate Low Total High 133 220 483 86 373 711 219 594 195 Medium-high 84 302 650 3 727 831 170 498 233 104 018 319 362 547 032 Medium-low 14 204 453 5 393 325 25 406 771 71 256 632 116 261 181 Low 31 609 615 125 111 458 156 721 073 Total 231 727 586 95 494 867 227 514 619 300 386 409 855 123 481 Source: Calculated from Eurostat s Comext database. A key characteristic is intra-industry trade (IIT). This is particularly important in trade between high-income countries, but it is also important for trade flows among countries of different levels of development. The determinants of IIT are different from those of inter-industry trade and, consequently, the policy conclusions also differ. Inter-industry trade with low-intermediate-income countries can be seen as the segment of trade, and of the industry, for which the threat from international competition is highest. These flows correspond to trade explained by comparative advantage, such as low wage levels, which are clearly a characteristic of low-intermediate-income countries. to the level of income of the trade partners, the distinctive feature with low-intermediate countries is the co-existence of IIT and inter-industry trade. In other words, these countries play a dual role: their trade is based on low labour skills products but they also exchange with EU-15 other categories of more sophisticated products and technologies. These are undoubtedly based on standardised technology that permits product imitation and, hence, can be produced easily in these nations. These data suggest that EU-15 trade takes place mostly with high-income countries and is mostly IIT. Trade with lowintermediate-income countries accounts for a relatively small share of total trade. While EU-15 trade with high, upper-medium, and low-income countries corresponds to the general pattern, according to which IIT is inversely related

EU sectoral competitiveness indicators 128 Source: Calculated from Eurostat data: NewCronos (SBS domain) and Comext databases and European business: Facts and figures (2003 edition). VI.7. Annexes 60 50 40 30 20 10 0 Food, drink and tobacco Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Non-metallic mineral products Basic metals Fabricated metal products Mechanical engineering Office machinery Insulated wire Other electrical machinery n.e.c. Electronic valves and tubes Telecommunication equipment Radio and television receivers Scientific instruments Other instruments Motor vehicles Building and repairing of ships Aircraft and spacecraft Railroad and transport equipment n.e.c. Furniture; manufacturing n.e.c. Graph VI.A.1: EU-15 exports/production (%) average 2000 02

EU sectoral competitiveness indicators 129 20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 Food, drink and tobacco Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Non-metallic mineral products Basic metals Fabricated metal products Mechanical engineering Office machinery Insulated wire Other electrical machinery n.e.c. Electronic valves and tubes Telecommunication equipment Radio and television receivers Scientific instruments Other instruments Motor vehicles Building and repairing of ships Aircraft and spacecraft Railroad and transport equipment n.e.c. Furniture; manufacturing n.e.c. Graph VI.A.2: EU exports of goods Share of total manufacturing exports (%) 1989 2002 Source: Calculated from Eurostat data: European business: Facts and figures (2003 edition).

EU sectoral competitiveness indicators 130 12.0 10.0 8.0 4.0 2.0 0.0 Food, drink and tobacco Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Non-metallic mineral products Basic metals Fabricated metal products Mechanical engineering Office machinery Insulated wire Other electrical machinery n.e.c. Electronic valves and tubes Telecommunication equipment Radio and television receivers Scientific instruments Other instruments Motor vehicles Building and repairing of ships Aircraft and spacecraft Railroad and transport equipment n.e.c. Furniture; manufacturing n.e.c. Graph VI.A.3: EU imports of goods Share of total manufacturing imports (%) 1989 2002 6.0 Source: Calculated from Eurostat data: European business: Facts and figures (2003 edition).

EU sectoral competitiveness indicators 131 100 000 80 000 60 000 40 000 20 000 0 20 000 40 000 Food, drink and tobacco Textiles Clothing Leather and footwear Wood and products of wood Pulp, paper and paper products Printing and publishing Mineral oil refining and nuclear fuel Chemicals Rubber and plastics Non-metallic mineral products Basic metals Fabricated metal products Mechanical engineering Office machinery Insulated wire Other electrical machinery n.e.c. Electronic valves and tubes Telecommunication equipment Radio and television receivers Scientific instruments Other instruments Motor vehicles Building and repairing of ships Aircraft and spacecraft Railroad and transport equipment n.e.c. Furniture; manufacturing n.e.c. Graph VI.A.4: EU-15 external trade of goods Trade balance (million EUR) 1989 2002 Source: Calculated from Eurostat data: European business: Facts and figures (2003 edition).

EU sectoral competitiveness indicators 132 Graph VI.A.5: EU-15 exports Top six sectors shares in total manufacturing exports (%) 20 18 16 14 12 10 8 Food, drink and tobacco Chemicals Basic metals Mechanical engineering Motor vehicles Aircraft and spacecraft 6 4 2 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source: Calculated from Eurostat data: European business: Facts and figures (2003 edition).

EU sectoral competitiveness indicators 133 Clothing Basic metals Motor vehicles Aircraft and spacecraft Graph VI.A.6: EU-15 imports Top six sectors shares in total manufacturing imports (%) 11 10 9 8 7 Mechanical engineering Office machinery 6 5 4 3 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source: Calculated from Eurostat data: European business: Facts and figures (2003 edition).

EU sectoral competitiveness indicators 134 Malaysia Pakistan Philippines Singapore Thailand Vietnam VI.7.1. List of countries by region Other EU-25 Cyprus Czech Republic Estonia Hungary Latvia Lithuania Malta Poland Slovakia Slovenia Asia China Hong Kong India Indonesia Japan South Korea Other western Europe Norway Switzerland Central and eastern Europe Belarus Bulgaria Kazakhstan Romania Russia Ukraine Turkey North America Canada United States Latin America Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela Costa Rica El Salvador Guatemala Honduras Nicaragua Cuba Dominican Republic Panama Oceania Australia New Zealand Africa Algeria Angola Benin Burkina Faso Burundi Cameroon Central African Republic Congo Côte d Ivoire Egypt Ethiopia Gabon Guinea Guinea-Bissau Kenya Libya Mali Morocco Mozambique Niger Nigeria Rwanda Senegal South Africa Togo Tunisia Uganda Tanzania Congo, Democratic Republic of the Zimbabwe Middle East Kuwait Iran Israel Jordan Lebanon Oman Qatar Saudi Arabia United Arab Emirates

Low-income India Pakistan Vietnam Nicaragua Angola Benin Burkina Faso Burundi Cameroon Central African Republic Congo Côte d Ivoire Ethiopia Guinea Guinea-Bissau Kenya Mali Mozambique Niger Nigeria Rwanda Senegal Togo Uganda Tanzania Congo, Democratic Republic of the Zimbabwe Indonesia EU sectoral competitiveness indicators 135 VI.7.2. List of countries by income level High-income Cyprus Malta Slovenia Israel Kuwait Qatar United Arab Emirates Hong Kong Japan South Korea Singapore Norway Switzerland Canada United States Australia New Zealand Upper-medium-income Czech Republic Estonia Hungary Latvia Lithuania Poland Slovakia Lebanon Oman Saudi Arabia Malaysia Argentina Chile Mexico Uruguay Venezuela Costa Rica Panama Gabon Libya Low-medium-income Iran Jordan China Philippines Thailand Belarus Bulgaria Kazakhstan Romania Russia Ukraine Bolivia Brazil Colombia Ecuador Paraguay Peru El Salvador Guatemala Honduras Cuba Dominican Republic Algeria Egypt Morocco South Africa Tunisia Turkey

EU sectoral competitiveness indicators 136 VI.7.3. Goods classified by technology category The OECD four technology categories used in this chapter are as follows. High-technology manufactures Pharmaceuticals Office, accounting and computing machinery Radio, television and communication equipment Medical, precision and optical instruments Aircraft and spacecraft Medium-high-technology manufactures Chemicals excluding pharmaceuticals Machinery and equipment n.e.c. Electrical machinery and apparatus n.e.c. Motor vehicles, trailers and semi-trailers Railroad equipment and transport equipment n.e.c. Medium-low-technology manufactures Coke, refined petroleum products and nuclear fuel Rubber and plastic products Other non-metallic mineral products Basic metals Fabricated metal products Building and repairing of ships and boats Low-technology manufactures Food products, beverages and tobacco Textiles, textile products, leather and footwear Wood and products of wood and cork Pulp, paper, paper products, printing and publishing Manufacturing n.e.c.; recycling

European Commission EU sectoral competitiveness indicators Luxembourg: Office for Official Publications of the European Communities 2005 136 pp. 14.8 x 21 cm ISBN 92-894-6418-6

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