The Productivity Problem of the Dutch Economy : Implications for Economic and Social Policies and Business Strategy

Transcription

1 The Productivity Problem of the Dutch Economy : Implications for Economic and Social Policies and Business Strategy Research Memorandum GD-66 Bart van Ark Groningen Growth and Development Centre September 2003

2 The Productivity Problem of the Dutch Economy: Implications for Economic and Social Policies and Business Strategy by Bart van Ark* University of Groningen and The Conference Board September 2003 Abstract This paper provides an overview of productivity issues in relation to the performance of the Dutch economy since the 1980s. It looks in particular at the reasons for the slowdown in productivity growth during the second half of the 1990s. Productivity measures are analyzed in relation to per capita income, labour market indicators and various measures of efficiency. The paper then provides a detailed sectoral perspective of productivity growth, with a focus on the role of technology (ICT) and innovation. Considerable attention is also given to the role of intangible inputs, including human capital, knowledge capital and organizational capital. The Dutch policy environment is discussed from the perspectives of macroeconomic and structural policies to support productivity growth. The paper concludes that the potential for faster productivity growth in the Netherlands is quite substantial, in particular in (service) industries that are intensive users of ICT. However, a restructuring of the economic environment is a crucial condition to realize this potentia l. The paper also stresses the need for business strategies that exploit the combined effects of innovation and investment in ICT and intangibles. * Acknowledgements: This paper makes extensive use of earlier work done for DG Enterprise at the European Commission concerning the construction of EU Sectoral Productivity Database, together the National Institute of Economic and Social Research (O Mahony et al, 2003); a project on the economics of knowledge for the Italian Communications Authority (van Ark, 2003); and a study for the Netherlands Ministry of Economic Affairs on service innovation (van Ark, Broersma and den Hertog, 2003). I am also grateful to Berenschot Groep B.V. for financial support to work on the conceptualization and measurement issues concerning intangible capital. None of the organizations mentioned above bear any responsibility for the content or viewpoints expressed in this paper. I am grateful to Robert Inklaar, Edwin Stuivenwold and Gerard Ypma for statistical assistance.

3 1. Introduction During the past decade, labour productivity growth in the Netherlands has strongly slowed down from an average annual growth rate of around 3% during the first decades since World War II to well below 1 per cent during 1990s. In recent years, partly as a result of the cyclical downturn, productivity growth has more or less come to a standstill, and in terms of output person rather than output per hour - even turned negative (see Table 1). Even though the absolute level of productivity is still hig h, even in comparison to the United States, the present slowdown seriously erodes that advantage (see Table 2). This productivity slowdown is a serious problem as, in the long run, it is the only sustainable source of economic growth. Growth of GDP is dr iven either by an increased use of inputs, such as labour, capital, intermediate inputs, energy, etc., or by an increased efficiency in applying these inputs. Labour input growth has been an important engine of the Dutch growth model during the 1980s and 1990s, making up for the low levels of labour force participation of the 1970s. Although labour force participation may still be increased to some extent, demographic changes reduce the potential for accelerated growth from that source. Physical capital input may also rise in particular when new technology (such as information and communication technology) speeds up investment in new capital vintages (capital deepening) or supports the development of new markets (capital broadening). But ultimately all these inputs are characterized by diminishing marginal returns: each additional unit of capital is likely to generate less output. The silver bullet for continued growth is in the more efficient use of the inputs. In the long term this can be achieved through technological progress. The latter requires an innovation climate that frees up resources to create knowledge that is needed to push the technology frontier ahead in the long term. In the short and medium run the focus should be on a better exploitation of the existing opportunities (the potential) for productivity growth. This requires attention for other types of innovations than just knowledge creation, in particular the support of knowledge diffusion, conditioning policy factors, such as properly working markets and sound macroeconomic policies, and organizational innovations within firms and organizations. An important argument in this paper is that these two sources of productivity growth, i.e., technological progress and a reduction in the distance between average and best practice, are not independent. A Worldwide, European or Dutch Problem? Earlier contributions by the Groningen Growth and Development Centre and The Conference Board have shown that the productivity problem partly reflects a worldwide problem, partly a European problem and partly a typical Dutch problem. 1 Worldwide the slowdown in technological advances has reduced the potential for rapid productivity since the early 1970s. Structural change towards a large share of service industries supposedly supported the slowdown further, because of the assumed inherent problems of increasing productivity growth in services (Baumol, 1967). But the increased potential for applications of ICT has turned the cards. Indeed in the industrialized world investment in ICT has rapidly increased during the 1990s. At firm level, there is substantial evidence of positive 1 See, for example, van Ark and de Haan (2000) and McGuckin and van Ark (2003). 1

4 effects of ICT investment on productivity (OECD, 2003). At macroeconomic level, so far only the U.S. (and a limited number of other countries, such as Finland, and Ireland) have also clearly benefited in productivity terms. Some of this divergence in productivity due to ICT is related to a country being a producer of ICT or not, but some countries have also boosted productivity through better use of ICT (e.g., Australia). Hence Solow s quip that you can see computers everywhere, except in the statistics, which is often referred to as the productivity paradox, seems to be gradually but slowly loosing its significance (Solow, 1987). Part of the productivity problem is typically European. Although Europeans have widely adopted ICT in their production processes, at macro level productivity effects have remained largely absent. Part of the explanations are of a macroeconomic nature, and relate to changes in the ratio of capital to labour which finally began to fall from very high levels in the 1980s. This led to a rapid increase in labour participation, but without sufficient opportunities to employ this labour productively. The latter relates to lack of reforms in product, labour and capital markets to exploit the full productivity potential from ICT. Part of the slowdown is also due to a less effective national innovation systems, where, for example, links between business and private and public knowledge institutes are not as well developed. These and other reasons have led to a call by the European Commission in Spring 2002 to target the EU as the most knowledge intensive and productivity economy in the world (the so-called Lisbon Declaration). 2 Finally, there is a typical Dutch touch to the productivity problem as well. Following the recovery from the serious economic crisis during the early 1980s, economic policy in the Netherlands has been strongly focused on the creation of more employment by raising the labour force participation ratio. Although this policy has been quite successful, it may have turned attention away for too long from the question how to create productive employment. Two types of policy measures are indicative of this neglect. Firstly, the policy of wage moderation may have been pursued for too long and with too little differentiation across industries and sectors. Secondly, until recently the Dutch government has systematically spent a lower percentage of GDP on general education than elsewhere in the OECD. There has been a fairly extensive literature on the Dutch productivity problem, including a major report by the McKinsey Global Institute (1997), a range of studies at CPB (van der Wiel, 1999, 2001; Kox, 2002), the University of Groningen (van Ark and de Haan, 2000, 2000a), Tilburg University (van Schaik, 1997, 2002) and the University of Delft (Naastepad and Kleinknecht, 2002). More recently the Ministry of Economic Affairs has initiated a range of productivity projects from the perspectives of macroeconomics, market reforms and innovation (see, for example, Donselaar et al., 2003). All these studies have strongly focused on the external environment of firms, which naturally provides important incentives or disincentives for productivity-enhancing activities. 2 See 2

5 Table 1: Aggregate average annual growth rates of real GDP, total hours and labour productivity, real gdp total hours gdp/hour Austria Belgium Denmark Finland France Germany Greece Ireland Italy Netherlands Portugal Spain Sweden United Kingdom European Union United States Japan Note: Germany refers to West Germany only; EU excludes Eastern Laender of Germany Source: GGDC Total Economy Database (June 2003), University of Groningen and The Conference Board 3

6 Table 2: GDP share, employment/population ratio and GDP per hour worked as % of the USand labour productivity, GDP as % of US GDP Employment/population ratios GDP per hour worked as % of US Austria Belgium Denmark Finland France Germany Greece Ireland Italy Netherlands Portugal Spain Sweden United Kingdom European Union United States Japan Note: Germany 1980 refers to West Germany only; Germany is all Germany. EU 1980 excludes Eastern Laender of Germany Source: GGDC Total Economy Database (June 2003), University of Groningen and The Conference Board 4

7 Contribution of this Paper In this paper, my aim is to provide a broad overview of productivity issues mainly in relation to the Dutch economy, although at many places the discussion is widened to provide an international comparative perspective. This paper is set out as follows. Section 2 introduces the analytical framework, which contain the main driving forces of productivity growth. I also discuss the relationship between productiv ity and other performance measures, including income, various efficiency concepts and profitably. I will show that although labour productivity growth is a useful performance measure it does not equal efficiency. The latter requires another productivity concept, namely total factor productivity (TFP). TFP captures the combination of the average improvement of firms towards best practice in a given local situation (reduction in X- or technical inefficiencies) and the improvement in best practice (often denoted as technological progress). I will also argue that when measuring only the effects of physical capital in a production function framework, we may still find differences in productivity performance due to differential organizational practices or enterpreneurship. Section 3 reviews the latest estimates of the sector structure of the Dutch economy, and its relation to productivity growth. It looks specifically at the distribution of new technologies (in particular ICT) and skills across industries, and their relation to productivity growth. It is shown that ICT investment is an important source of productivity growth alongside with TFP improvements. Industries that make intensive use of ICT have broken the traditional trade-off between productivity and employment growth, in particular in service industries. However, the impact of ICT on capital in the Netherlands, and more generally in Europe, has been much lower than in the U.S. Section 4 discusses the various types on intangible capital that often remain hidden in macroeconomic productivity studies, including human capital, knowledge capital, organizational capital and marketing capital. I will provide evidence on their relative importance, stress the importance of intangible capital accumulation in the service sector of the economy and its relation to the accumulation of ICT. Section 5 considers the policy environment in more detail. I will focus on the role of macroeconomic, structural and innovation policies (in particular innovation in services), and discuss the literature on the effectiveness of such policies from the perspective of productivity growth. I also review the role of wage moderation and its impact on productivity growth. Finally, in the concluding section I reiterate the main priorities to support productivity growth in the Netherlands. I will argue that, rather than developing a new policy framework to support productivity growth, existing policies need to be intensified or extended. In particular I assign an important role to a broadening of innovation policies and greater attention for horizontal policies such as programmes of structural reforms, and the need for higher expenditure on education. Finally, the role of the business sector itself to improve transparency of the productivity effects of their own business processes is addressed. Although a restrictive economic environment may have withheld European business from making imminent decisions to jump on new opportunities, business itself has also rethink their strategies in how to exploit the technological opportunities most efficiently. 5

8 2. Income, Productivity and Efficiency: The Role of Business and Policies Figure 1 presents the conceptual framework to study the sources of growth and productivity differentials. This framework is rooted in a traditional growth accounting framework, highlighting the role of physical capital and total factor productivity, but with several crucial extensions. Labour productivity and per capita income Figure 1 starts from taking GDP per capita as the ultimate measure of economic performance as it is a fairly comprehensive albeit imperfect measure of living standards. GDP per capita growth is driven by an increased input of labour and/or labour productivity growth. Indeed one can simply show that the difference in the growth of average per capita income and labour productivity can be accounted for by changes in a range of labour market and population indicators (see van Ark and McGuckin, 1999; van Ark and de Haan, 2000). First, the growth in income per head of the population ( O/P) is a function of the change in labour productivity ( O/H) and labour intensity, expressed as the number of working hours per head on the population ( H/P): O/P = O/H * H/P (1) The change in working hours per person can be decomposed into the change in hours worked per person employed (H/E) and the change in the share of employment in the total population (E/P): H/P = H/E * E/P (2) The change in the employment/population ratio (E/P) can be further broken down into the number of persons employed relative to the total labour force (i.e., employed persons plus registered unemployed persons) (E/L), the ratio of the labour force to all persons aged 15 to 64 (i.e., the working age population) (L/P1564) and the share of the working age population in the total population (P1564/P): E/P = E/L * L/P1564 * P1564/P (3) In Figure 2a we show the trend in per capita income and labour productivity since We find that labour productivity has continued to grow faster than per capita income during the 1980s, which as appears from Figure 2b has been mainly due to the continuous decline in average working hours per person. However, since the late 1980s, per capita income began to accelerate due to a rapid increase in labour force participation. This was mainly due to a strong increase in participation of women in the labour market and an increase in participation of low-skilled labour in particular during the 1990s. Although declining working hours due to a rise in part-time work and shortening of the standard working week and a lower share of the working age population in the total population offset some of the per capita income gains, the latter continued to accelerate until In contrast labour productivity growth has slowed down. 6

9 Figure 1: Analytical Scheme on Productivity GDP per capita Labour productivity Real Output Labour supply Sectoral shifts Within-industry labour productivity growth Hours worked per person employed Share of employment in working age population Efficiency of Investment in Investment in Share of working age population factor use (TFP) physical capital intangible capital in total population Non-ICT Capital ICT Capital Human capital Knowledge capital Short and medium term shocks Active demand side policies Active supply side policies Process capital Customer capital Macroeconomic Manageme nt Structural reforms Product markets Capital markets Labour markets Internal business environment; External policy environment 7

10 150 Figure 2a: Labour Productivity and Average Income, Netherlands, , 1980= Output per hour Output per person employed Income per capita 30 Figure 2b: Effects of Lower Hours and Higher Participation on GDP per Capita Trend, Hours per person-effect Unemployment-effect Labour force participation-effect Working age-effect Source: Per capita income and labour productivity from GGDC Total Economy Database, University of Groningen and The Conference Board; unemployment, labour force participation rates, and share of working age population from CBS Statline. 8

11 The myth of slowing productivity growth due to declining working hours. Despite the usefulness of the labour productivity measure in relation to the change in average income and trends in labour market indicators, it is a measure that easily gives rise to confusion. One source of confusion is the popular notion that slow labour productivity growth means that people do not work hard enough. The latter is often translated into people not working sufficiently long hours. This explanation for slowing productivity growth is simply refuted by the facts. The relationship between labour productivity growth rates and the change in working hours per person has been negative during the whole of the 1980s and 1990s (compare Figures 2a and 2b). Moreover, despite a slowdown in labour productivity growth, the number of total hours worked has contin ued to increase rapidly during the 1990s. It is also clear from international comparisons of productivity levels that some countries with relatively high productivity levels, such as Belgium, France, Norway and the Netherlands, are characterized by relatively low working hours (see, for example, Table 2 and McGuckin and van Ark, 2003). The confusion on the relationship between productivity and working hours arises from the fact that more working hours may imply more output in total (and even higher income per capita), but not necessarily more output per hour. For example, during the 1970s and 1980s, when labour force participation rates were much lower than today, productivity levels were in fact quite high. Those who were still in the labour force were the most productive, as relatively high skilled, full-time employed men accounted for a greater share of total employment. Even so, there is little evidence that the increased participation of low-skilled labour or more part-time labour has contributed much to the productivity slowdown (see, for example, CPB, 1997, 1998). The role of sectoral shifts Labour productivity growth is essentially driven by two mechanisms. The first is productivity growth within individual industries (i.e., manufacturing industries or service industries), and the second involves shifts of resources from industries with either low productivity levels and/or low productivity growth rates to industries with high productivity levels and/or high productivity growth rates. There is indeed some evidence that the increased share of service industries in the economies of advanced countries may be partly responsible for the productivity slowdown, but the effect is not very large for at least two reasons. 3 First, slow productivity growth in services is partly offset by relatively high productivity levels (euros per working hour) in several service industries compared to manufacturing industries. Secondly, many service industries are particularly large users of ICT capital, which (at least potentially) has a positive impact on productivity growth, offsetting the slow natural productivity growth rate in services. 4 The role of ICT and its impact on industry productivity is discussed in more detail in Section 3 of this paper. 3 See, for example, van Ark (2001) for a shift-share analysis of productivity growth in the Netherlands from See also Naastepad and Kleinknecht (2002). 4 See, for example, Triplett and Bosworth (2002) on the productivity revival in U.S. service industries. 9

12 The sources of within-sector productivity growth As within-industry productivity growth dominates the shifts between industries, the focus of the analysis needs to be on productivity growth by industry. There are essentially three sources of growth which drive industry productivity: 1) The first and most obvious source is investment in physical capital goods (or tangible capital), including machinery and equipment and structures. In particular the distinction between capital goods that embody information and communication technology (ICT) versus non-ict capital is important for our analysis here (see Section 3). 2) A second source of industry productivity growth is investments in intangible capital. There is abundant evidence that intangible capital, which includes investment in education and other human capital, knowledge, organizational changes and relationships with customers, is an important source of wealth creation. Because of its importance for the study of productivity, the intangible capital concept is discussed in more detail in Section 4. In traditional macroeconomic productivity studies, there is only limited attention for intangible capital, mostly restricted to the role of human capital, which is measured as skills of the labour force, and knowledge capital, which is measured as the contribution of R&D to productivity growth. 3) Labour productivity growth is not only the result of a rise in the amount of tangible and intangible inputs per working hour, but also of the efficiency with which these resources are transformed into output, which may be defined as total factor productivity (TFP) growth. From a macroeconomic viewpoint, TFP growth refers to the increase in output relative to the rise in the combination of joint inputs. In more practical terms one may also interpret TFP growth as real cost reductions of the inputs, where real refers to the fact that the quality of the inputs is assumed to remain constant (Harberger, 1998). 5 The latter source of growth, which is the only sustainable source of productivity growth in the long run, is discussed in some more detail below, as there is much confusion on the actual meaning of TFP growth. Total factor productivity growth and efficiency Although total factor productivity growth may be interpreted as the rise in efficiency or technological change, one has to be cautious with such interpretations for various reasons. Firstly, although a greater amount of capital input raises output per working hour, it mostly goes together with a good deal of technical change. Hence capital accumulation and technological change are mostly not independent sources of growth but strongly complementary. In the framework of a traditional Solow production function, relating capital to output growth, TFP growth refers to the outward shift of the production function. But Figure 3 shows how the rise in labour productivity is often related to a combination of technological change (measured as a shift of the production function) and a rise in capital per worker (measured as a shift along the production function), which may be induced by the change in technology in the first place. 6 5 Alternatively TFP growth may also be interpreted as the investment returns that are not internalised by the investor. 6 For a review of the literature on embodied technical change see, for example, Hercowitz (1998). 10

13 Figure 3: Combined impact of capital intensity and technological progress on labour productivity Labour Productivity Growth "Induced" Capital Intensity X Technological Progress X Change in Capital-Labour Ratio Secondly, apart from the fact that TFP growth and a rise in inputs are not fully independent, total factor productivity is in practice measured as a residual measure that is obtained from the growth output minus the growth rates of the input weighted at their compensation share in total output. This is done on the assumption that each input gets paid its marginal product. In the likely case that that assumption does not hold, for example, because labour markets do not exactly pay a wage according to the productivity of the last worker added to the labour force, the identity of TFP, efficiency and technical change breaks down. In fact, measured TFP includes everything that is not otherwise measured, including the growth in unmeasured intangible inputs (which turns up as higher TFP growth) and the effects of imperfect market competition that create mark-ups on prices beyond the normal returns to inputs (and therefore reduce TFP growth). There is a substantial literature that aims to interpret the reasons for differences in TFP residuals across countries, which may be due to market imperfections (Hall, 1988; Roeger, 1995) but also because of differences in historical, institutional or policy related factors (Maddison, 1989; Easterly and Levine, 2002). Thirdly, one should also be careful on how to interpret total factor productivity growth in relation to a rise in efficiency. Figure 4 distinguishes three different concepts of efficiency. The two production functions in this figure represent all the combinations of capital and labour input that together make 11

14 up the technically efficient methods of production. Firms that are on the production function get the most production from the available resources, and are in principle equally productive in real terms. 7 Figure 4: Various efficiency concepts and their relation to the production function Capital X X X X X X X X Technological frontier Best local practice Relative price of labour and capital Labour Reduction of X-inefficiency Improvement in allocative efficiency Technological progress However, in practice there are many firms that are not on the production function. These firms may spend more resources than the best practice firms to achieve the same (or lower) productivity. They are technically inefficient for a host of different reasons. For example, they have not adequately adapted the organization of work to the new technologies they have adopted, or to the new products or services they have begun to produce, or to the new markets they face. They may still have unneeded employees on the payroll, or failed to hire new ones. They may have been unsuccessful in overcoming disturbances to the production process or work with inappropriate management structures. It are these differences between actual practic e and best practice (or actual productivity and norm productivity) that are the topic of much of the (human resource) management literature (see, for example, Jongkind, Vaas and Oeij, 2003). There may be many internal reasons why firms do not reach best practice. External factors, such as inadequately functioning labour or capital markets may also be a cause. Whatever the reasons, from an economist point of view the gap between actual and best practice, which may also be called X-inefficiency (Leibenstein, 1976), means that a surviving firm can extracts a higher price than a competitive market would dictate to cover its higher cost. 7 In practice firms on the production function may still differ in productivity because of differences in unmeasured intangible inputs that impact productivity (see Section 4). 12

15 In addition to X-inefficiency, the efficiency of the best practice firm can also improve due to technological progress. For example, the most efficient firm in the Netherlands can adopt a new technology already in existence in the United States; or it can itself be at the technological frontier and successfully introduce a new technique that shifts the frontier. This source of technological progress is at the basis of most of the economics literature on productivity. In practice the TFP measure introduced above does not distinguish between a reduction in X-inefficiency and technological progress but includes both. The productivity measures discussed so far are in fact quantity relationships between the quantity of output and the quantities of one or more input, which are in practice measured as the value of output relative to inputs deflated by an appropriate price index. In addition, there is another improvement in productivity possible that comes from an improvement in allocative efficiency. This implies that a firm which is technically efficient reshuffles its resources is such a way that it is using these resources most efficiently given the relative prices of the inputs. A rise in allocative efficiency does not change the productivity in terms of the output quantity measure relative to combined quantity measure of input, but it does raise the output value relative to the input values at one point in time. Hence real productivity (in growth terms) is not affected but nominal productivity (in level terms at current prices) rises and therefore positively impacts on, for example, income and profits. The latter implies that firms that are technically efficient are not necessarily profit maximizing. In fact in particular during times of rapid changes in relative prices (such as during recent time of rapidly declining prices of ICT capital goods relative to non-ict capital) firms may make substantial losses if their combination of factor inputs is not in line with relative prices of factor inputs. In summary, productivity measures, such as labour productivity and total factor productivity, measure the average change in the quantity of output (real output) of all firms in an industry or the whole economy relative to the average change in their quantities of one or more inputs (real inputs). Productivity is not equal to efficiency, but combines the effect of a reduction in technical ineffic iency (or X-inefficiency) and technological progress. The regular measures of productivity growth or comparisons of productivity levels across countries do not take account of possible changes in allocative efficiency, although these do change the productivity value and affect income and profit rates. Finally, traditional measures of productivity, such as those used in the following section do not separately distinguish other sources of differences in productivity beyond differences in physical and human capital intensity. The impact of other sources is therefore reflected in differences in the TFP residual. The external policy environment The investment decisions concerning tangible and intangible capital, and the (re)allocations of these inputs to industries and firms, are taken in an environment, governed by markets in which supply and demand for factor inputs (labour and capital markets) and product and services (product markets) are matched. Governments play an important role in setting the rules of the game (or institutions) of these markets. Firstly, macroeconomic conditions influence the relative prices of capital and labour inputs, which determine the choice of technology. Secondly, the intensity of competition at those markets determines the threat of potential entries and is therefore an important source of the drive for both incumbents and newcomers to innovate. Thirdly, governments also need to create the rules of 13

16 the game concerning technology creation and diffusion, including an effective patenting and licensing system that meets the demands of a world in which innovation spread at in increasing pace. Finally, governments are key to developing appropriate supply side policies in the areas of education, research and physical infrastructure to provide a breeding ground for business to generate investment and productive use of resources. The role of the policy environment in relation to productivity growth is discussed in more detail in Section 5 of the paper. In conclusion, productivity is partly driven by internal business processes and partly by the external environment of firms (and organizations in general). The internal environment refers to the domain of business itself. It focuses on the internal process within firms to make investments in capital and optimize the return of these investments. Capital here refers to a broad concept, and includes machinery and equipment (including ICT capital), but also human capital, knowledge capital and organization capital. The external environment deals with macroeconomic and industrial organization issues, which include the functioning of markets that are key in allocating resources (such as ICT and ICT-related inputs) to their most productive uses, and the role of government to create an optimal environment for innovation. In the remainder these concepts will be crucial to understanding the role of capital and TFP at industry level (Section 3), intangible capital (Section 4) and policies that support productivity growth (Section 5). 14

17 3. A Sector-Specific Perspective on Productivity Growth Why adopt a sector perspective? In this section we look at the productivity performance of the Dutch economy from a sector perspective. Although many of the policy issues related to the slowdown of the Dutch economy are more of a generic rather than of an industry specific nature, the sector perspective is useful for several reasons. Firstly, it is important to pinpoint where the slowdown occurs and to ask the question if the Dutch productivity slowdown is just confined to a few sectors or whether it is more widespread. Secondly, under the influence from both intra-eu economic integration and the on-going globalization of product markets and factor markets, the industry structure is under continuous pressure from competitive forces. It is important to establish how these changes affect the overall performance of the Dutch economy. Finally, the opportunities for new technological applications may have very different implications for industries. Indeed the absorptive capacity for ICT differs highly across industries, and has very different impacts on output, employment and productivity performance. Sector Structure of the Dutch Economy In this section we make use of a new database, the EU Sectoral Database, which was developed by the Groningen Growth and Development Centre and the National Institute of Economic and Social Research on behalf of the European Commission (DG Enterprise). 8 It provides information on output, labour and capital inputs and productivity at the level of 56 industries from 1979 to When focusing on the structure of the Dutch industry, there are of course several ways to look at a sector distribution. Table 3 shows the labour input and value added share in the total economy of the Netherlands in comparison with that of the EU-15 and the United States for a range of different taxonomies. 9 In terms of broad sector shares, there are no large differences between the various regions, except for the somewhat higher employment share of the U.S. in distributive trade, and the relatively high share of business services in employment in the Netherlands. 10 Concerning the latter it is striking that the differences in value added share is much lower than that of total hours share, suggesting a concentration of business services at low productivity level. The taxonomy based on whether industries are producers of ICT goods or services, large users of ICT in terms of investment, or less intensive users, shows a striking advantage for the U.S. in the share of ICT-using services (see also van Ark et al., 2002). In contrast EU shares are relatively large in manufacturing (ICT-using and non-ict). The Dutch distribution is in between the EU and the U.S. with a larger share for ICT-using services and lower share for manufacturing than the EU See O Mahony et al. (2003, forthcoming). The database, including the details, will be made available to the public at the end of 2003 on the GGDC website: industry.shtml#top. Presently a previous version of the database is available on that site with series up to 2000, based on van Ark, Inklaar and McGuckin (2002). 9 See Appendix A for a precise description of the allocation of industries according to each taxonomy. 10 The value added and employment share of non-market services (including health, education and government) is surprisingly large in the U.S. 15

18 Table 3: Distribution of Value Added and Employment Shares by Industry on the basis of various taxonomies, 1999 Industry Share in Value Added Industry Share in Total Hours at current prices, 1999 Worked, 1999 Neth EU US Neth EU US Broad Sectors Agriculture, Forestry and Fishing Mining and quarrying Manufacturing Electricity, gas and water supply Construction Distributive trades Transport Communications Financial Services Real Estate Business Services Other community, Social & Personal Services Public Administration, Education and Health ICT production or use intensity (a) ICT Producing Manufacturing ICT Producing Services ICT Using Manufacturing ICT Using Services Non-ICT Manufacturing Non-ICT Services Non-ICT Other Skill intensity (b) High Skill High-Intermediate Skill Low-Intermediate Skill Low Skill Technology/innovation intensity (c) Supplier dominated Scale intensive industry Specialized suppliers Science based and/or organizational innovation Client led services Non-market services (a) based on share of ICT capital services in total capital in United States (b) based on detailed US and UK matching of skills complemented with more aggregate EU skills from EU LFS; see O'Mahony et al. (2003, forthcoming) (c) based on A22taxonomy of supplier-dominated, scale-intensive, specialized supplier and science-based, complemented with services innovation taxonomy on innovation in services (included with science based), innovation through services (included with specialized suppliers), supplier dominated services, client led services and non-market services from van Ark, Broersma and den Hertog (2003). Source: O'Mahony et al. (2003, forthcoming) 16

19 The third taxonomy looks at the distribution of industries according to their main skills characteristics. One is struck by the relatively high value added share of industries with high skills in the U.S., including ICT-producing industries and financial services. The EU dominates in the lower skill categories, and the Netherlands is characterized by a relatively la rge share in lower-intermediate skill industries, including low-medium tech industries in manufacturing (e.g. miscellaneous electrical goods), distributive and transport services. Finally, we developed a somewhat hybrid taxonomy that aims to take on board various characteristics of the technological and innovation process in various industries, in particular by looking at the source of the innovation (science-based, supplier-based, client-led, etc.). According to this taxonomy, clientled services which include wholesale trade, financial intermediation services, and various business services, have a relatively large share in value added and employment in the Netherlands. In summary, the industry structure of the Dutch economy seems somewhat biased towards services, in particular transport, wholesale trade and lower end of business services. Within manufacturing, which is characterized by a relatively small output and employment share, medium and low skill industries, including miscellaneous electrical goods and food processing dominate. On skills the Dutch situation is quite similar to that in the European Union as a whole, but with a somewhat stronger concentration in lower-intermediate skills. A Trade-Off between Employment and Productivity Growth? There has been a traditional concern in the economics literature that productivity growth goes at the cost of job creation. More efficiency would mean less jobs and rapid technological change would ultimately lead to a world without work (Rifkin, 1995). There is no evidence, however, at the level of the whole economy that this is the case. Since World War II, the number of jobs has increased enormously and on the whole labour intensity (in terms of actual hours to potential hours) has increased, although a slight decline can be observed for Europe but not for the U.S. (van Ark, Duteweerd and Frankema, 2003). At the industry level, however, tradeoffs between employment and productivity growth occur more frequently. In particular technological progress in manufacturing has been strongly labour-saving. In services, however, productivity growth has gone together with a substantial creation of new jobs. Still this raises the question whether the slower productivity growth in services is not at least partly related to the creation of new relatively low-skilled jobs. Table 4 shows growth rates of labour productivity, measured as value added per hour worked, and total working hours by industry group. 11 Table 5 shows the regression results of relating productivity and labour input growth rates for each subperiod. 11 It should be stressed that the productivity growth rates in the EU Sectoral Database are not fully compatible with the official estimates on real GDP and labour input by Statistics Netherlands as shown in Table 1. The estimates have been made more consistent for international comparison by, among other things, adopting an internationally harmonized price deflator for ICT goods. Moreover, as countries use different aggregation methods in their national accounts, the industry results in the sectoral database were aggregated according to the Törnquist index method for all countries. See also appendix B on measurement issues. 17

20 Table 4: Growth Rates of Labour Productivity and Total Hours in the Netherlands, , annual averages Labour Productivity Growth, Growth of Total Hours, annual average growth rates annual average growth rates Total Economy Broad Sectors Agriculture, Forestry and Fishing Mining and quarrying Manufacturing Electricity, gas and water supply Construction Distributive trades Transport Communications Financial Services Real Estate Business Services Other community, Social & Personal Services Public Administration, Education and Health ICT production or use intensity (a) ICT Producing Manufacturing ICT Producing Services ICT Using Manufacturing ICT Using Services Non-ICT Manufacturing Non-ICT Services Non-ICT Other Skill intensity (b) High Skill High-Intermediate Skill Low-Intermediate Skill Low Skill Technology/innovation intensity (c) Supplier dominated Scale intensive industry Specialized suppliers Science based and/or organizational innovation Client led services Non-market services (a) based on share of ICT capital services in total capital in United States (b) based on detailed US and UK matching of skills complemented with more aggregate EU skills from EU LFS; see O'Mahony et al. (2003, forthcoming) (c) based on Pavitt (1984) taxonomy of supplier-dominated, scale-intensive, specialized supplier and science-based, complemented with services innovation taxonomy on innovation in services (included with science based), innovation through services (included with specialized suppliers), supplier dominated services, client led services and non-market services from van Ark, Broersma and den Hertog (2003). Source: O'Mahony et al. (2003, forthcoming) 18

21 Table 4 shows that the slowdown in productivity growth between relative to the period has been largely across the board. Between these two periods, a productivity improvement was recorded only for agriculture, mining, financial services and other community, social and personal services. Moreover the relationship between productivity and labour input growth became more strongly negative during the period Although this may be partly related to cyclical factors, as productivity recovery at the bottom of the cycle usually goes at the cost of employment reduction, the change during the period is very striking. Despite a continued aggregate productivity slowdown for the whole economy from , Table 4 shows that the slowdown was more strongly concentrated in a limited number of industries, namely agriculture, manufacturing, financial services and other community, social and personal services. In contrast productivity growth strongly accelerated in distributive trades, communication and also in business services, although the productivity growth in the latter industry remained relatively low at 1 per cent per year on average. The recovery of productivity growth can also be traced to industries in the ICT-using services parts of the economy, with a relatively strong emphasis on industries that are characterized by low-intermediate skills (including trade and transport), and in industries that are either supplier dominated (in particular supplier dominated services (e.g, retail trade, communication and water transport) and client-led services (e.g., wholesale trade, supporting transport activities, etc.). The slowdown is to a large extent accounted for by the electrical goods sector, including radio and TV equipment in particular after taking account of the rapid decline in intermediate input prices and the banking and insurance sector. Table 5: Interaction between annual growth rates of labour productivity and labour input for 55 industries, The Netherlands, correlation coefficient regression coefficient (standard error) Note: labour productivity is value added hours worked Labour input is total hours worked Table 5 shows that the trade-off between productivity and employment growth has become much less severe during the second half of the 1990s. This is strongly related to the rise of ICT-using industries, where employment increased relatively rapidly and productivity growth accelerated. Table 6 compares the percentage of output by industry group with a positive relation between labour productivity and labour input growth, which has significantly increased since The improvement is particularly striking in ICT-using services. For the Netherlands, it is quite weak in 12 See also van Ark, Inklaar and Timmer (2003), with data only running up to The inclusion of 2001 in Table 6 has somewhat reduced the change in particular in the U.S. due to the recession. 19