BookPDF Available

Innovation and productivity growth in the EU service sector

European Investment Bank • European Investment Bank • European Investment Bank • European Investment Bank
Innovation and productivity
growth in the EU
services sector
by Kristian Uppenberg and Hubert Strauss
July 2010
About the authors
Kristian Uppenberg and Hubert Strauss are Senior Economists
in the Economic and Financial Studies division of the EIB.
The views expressed in this document are those of the authors and
do not necessarily reect the position of the EIB.
Innovation a nd productivit y growth in the EU ser vices sector 1
Innovation and productivity
growth in the EU
services sector
by Kristian Uppenberg and Hubert Strauss
July 2010
2 Innovatio n and productivit y growth in the EU ser vices sector
Innovation a nd productivit y growth in the EU ser vices sector 3
Innovation and productivity
growth in the EU
services sector
by Kristian Uppenberg and Hubert Strauss
Executive summary
European countries continue to pride themselves on their rich industrial
heritage and strong global position in high-end manufacturing. Yet the
underlying reality is that manufacturing is playing a steadily diminishing
role in both employment and output. In contrast, the services sector
accounts for around two-thirds of total output in the EU, and for four-
fifths of growth in recent years. In terms of employment growth, the
dominance of services is even more striking. With few exceptions,
manufacturing employment in the EU has contracted, total employment
expansion thus being accounted for either by services or by construction.
Reflecting the emphasis on the services sector in the EU2020 strategy,
this study highlights some key features of the services sector in the EU,
including productivity and innovation in market services. One important
observation is is that the services sector accounts for as much as three-
quar ters of cross-countr y differences in e conomi c growth across
individual EU countries. Relatively fast-growing countries have also
typically had above-average productivity growth. Even though
productivity growth is generally lower in the services sector than in
manufacturing, it nevertheless accounts for a large share of aggregate
growth in output per employee because of its large size. Countries with
high aggregate productivity growth also tend to have relatively higher
productivity growth in services.
4 Innovatio n and productivit y growth in the EU ser vices sector
But the services sector consists of a very disparate group of subsectors,
with varying productivity per formance and very different mechanisms
for enhancing output per employee. The study points to three key
ingredients in services sector productivity expansion.
The first is tangible fixed investment. On average, market services have
as much fixed capital per employee as manufacturing, but this capital
stock is more skewed towards buildings and information and
communications technology. These investments have been shown to
contribute substantially to productivit y growth in several key services
A second element is intangible capital. Services industries attain higher
productivity by combining investment in fixed capital, new computer
software and human capital so as to create new organisational structures
and business models, and sometimes entirely new service products. But
cross-country differences in the EU are substantial, in terms of both
tangible and intangible investment.
A third element is that services sector innovation, in contrast to that in
manufacturing, draws less on in-house knowledge creation in the form
of R&D. Services industries tend to innovate in interaction with customers,
suppliers and competitors. There is also substantial scope for productivity
improvements by adopting best practice, both within and between
certain service industries. The lower level of in-house knowledge creation
par tially reflects smaller average firm size in services industries. This
greater reliance on external sourcing of new knowledge suggests that
cluster formation fostering knowledge transfers and spillovers is an
important element in supporting services sector innovation.
Innovation a nd productivit y growth in the EU ser vices sector 5
6 Innovatio n and productivit y growth in the EU ser vices sector
The expansion of output and trade in manufactured goods constituted
the engine of prosperity in Europe for much of the past century. Even
today, European countries pride themselves on their manufacturing
heritage and retain a global technological lead in many industries. But
when we look more closely at economic growth in Europe, we see that
manufacturing has long taken the back seat to services industries, in
terms of both output and employment. Meanwhile, the manufacturing
firms themselves have become increasingly service focused, partly as a
means to remain competitive in a world economy where more and
more commoditised goods are being produced in developing countries
offering lower costs of production.
It is not unlikely that the economic crisis of recent years has speeded
up this process of deindustrialisation in Europe, as a number of
traditional sectors are confronted with overcapacity. Yet, the EU
economy must find ways to expand faster in coming years in order
both to replace the jobs lost during the crisis and to provide incomes
with which excessive debt burdens are to be reduced. Given that the
medium-term downtrend in manufacturing employment will not likely
reverse, future growth in employment and incomes is likely to centre
on services.
This study aims to explore some key features of the services sector.
Chapter 2 takes stock of the role of services in economic growth and
employment. Chapter 3 looks at fixed tangible investment in services,
relative to other sectors. Chapter 4 provides a mapping of intangible
investment across European countries. Chapter 5, finally, looks at the
process of innovation in services. Since this study focuses on longer-
term trends, and partly for reasons of data availability, the current
economic downturn will not be addressed specifically. There are also
other omitted elements, such as the functioning of labour, product
and financial markets, regulation, competition, and firm demographics.
Innovation a nd productivit y growth in the EU ser vices sector 7
“Framework policies” targeting these elements are clearly important
for innovation and growth in services, but they are not specific to
services per se.
The role of services in EU economic 2.
Total gross output in the economy (Gross Domestic Product, GDP) is the
sum of gross value added in all its sectors. These comprise
Utiliti es and other industry
This section sheds some light on the sectoral composition of economic
growth in the EU and the US using primarily OECD data on sector value
added and employment (“EU” is here represented by the EU-15 for
reasons of data availability). We look at the last 10-year period for which
disaggregated data is available for all countries, typically covering the
decade up to 2005. The sectoral decomposition and time periods are
slightly different for the EU aggregate and for the UK, for which only
European Commission data are available.
2.1 The services sector has been a key engine of
At the aggregate as well as the sectoral level, growth in output (i.e. gross
value added) is the sum of two components: growth in employment and
growth in output per employee (also referred to here as labour productivity,
although this is a slight simplification since output per employee is also
affected by the average number of hours worked by each employee).
8 Innovatio n and productivit y growth in the EU ser vices sector
The sectoral per spective allows us to addr ess several questions. Is
economic growth at the national level broad-based or propelled by just a
few sectors? Similarly, are cross-country differences in economic growth
broad-based or concentrated to differences in certain sectors? Finally,
does the composition of growth between employment and productivity
differ across sectors?
Starting with the aggregate picture, the services sector dominates the
EU economy in both level and growth terms. The services sector
accounts for around two-thirds of total value added and for four-fifths
of real value added growth in the decade to 2005. The services sector
also accounts for as much as three-quarters of cross-country differences
in economic growth across individual EU countries. With a few
exceptions, such as Sweden, Finland and Ireland, high-growth countries
have mostly expanded on account of their services sectors, not
In terms of employment growth, the dominance of services is even more
st rik ing. With fe w ex cep ti ons , man ufacturi ng em ploym ent has
contracted. It should be noted here that the EU as a whole experienced
relatively favourable conditions for employment growth during this
period, Germany being an exception caused in part by the contraction in
construction. Spain, Luxembourg and Ireland saw particularly strong
employment growth in the ser vices sector, augmented in the case of
Ireland and Spain by rising employment in the construction sector. In
retrospect, it is now clear that part of this construction-driven
employment growth was linked to unsustainable real estate booms, and
has contracted sharply during the recession.
2.2 In some sectors growth is propelled by
employment, in others by productivity
A way to better understand the drivers of growth is to decompose it by
growth in employment and growth in labour productivity (here proxied
Innovation a nd productivit y growth in the EU ser vices sector 9
by gross value added per employee)1 . On average in the EU as a whole,
economic growth has been driven in equal shares by productivity and
employment, as shown in Figure 1. While there is not a uniform pattern
across countries, those with high output growth have typically also had
above-average productivity growth. This is true for the US, and in the EU,
for the UK, Sweden, Finland, Greece and Ireland. There are two notable
exceptions: Output in Spain and Luxembourg has expanded largely due
to rising employment, not productivity. Ireland, finally, has enjoyed high
employment growth on top of its high productivity growth.
Figure 1: Sources of economic growth (contribution to annual real
value added growth, 1995-2005, percent)
Labour productivity Employment Value Added
Source: OECD and European Commission
Note: UK and EU-15 data are from the European Commission, for 1994-2004
The relative growth contributions of productivity and employment
differs markedly across different sectors of the economy. A shown in
1 Labour productivity is in turn a combination of capital deepening and total factor productivity
growth (TFP).
10 Innovatio n and productivit y growth in the EU ser vices sector
Figure 2 for the EU-15 as a whole, in agriculture and manufacturing, large
productivity gains have been accompanied by declining employment. In
construction the situation is the reverse. In services, finally, output has
been driven mostly by employment, but productivity growth has also
been positive. As we will show later on, this productivity growth is in fact
very important for aggregate growth performance.
Figure 2: Sources of sectoral growth in the EU-15 (contribution to
annual value added growth 1995-2005, %)
Total economy Agriculture Manufacturing Construction Services
Productivity Value Added
Source: European Commission Economic Forecast database (AMECO)
Zooming in on services, there are differences across countries. Sweden,
Denmark, the Netherlands, Greece, Ireland and the UK have all seen
notable gains in services sector productivity, as has the US. In a number
of other countries, however, productivity growth in services has been
negligible, and in the case of Spain negative.
While much of the public discourse on R&D has concentrated on the
resources that countries invest in R&D on an annual basis, what actually
matters for economic growth is the stock of knowledge, as represented
Innovation a nd productivit y growth in the EU ser vices sector 11
Box 1. Output, employment and productivity in services:
A closer look at selected subsectors
The services sector consists of a number of very different industries.
For simplicity we have grouped these together into four major
subsectors: Trade and tourism; Transport and communication; Finance
and business services; and Social services. Figure 3 shows their
respective contributions to total employment growth over the ten-
year period, for a selection of OECD countries. Finance and business
services have constituted a particularly strong growth engine in many
countries, on average accounting for around half of total growth in
services sector output, with a slightly smaller contribution to
employment growth. The role of this sector has been particularly
prominent in Luxembourg, France, Belgium, and in the US.
Unfortunately, this OECD data set does not include data for the UK.
Figure 3: Growth in service sector employment (sub-sectoral
contributions to average annual growth, 1995-2005,
Social services Finance and business services
Transport and communication Trade and tourism
Source: OECD
12 Innovatio n and productivit y growth in the EU ser vices sector
by the R&D capital stock. The R&D capital stock accumulates gradually as
a result of many years of investment in R&D, but it also depreciates as
older knowledge becomes obsolete. If Europe would suddenly raise its
level of R&D investment to meet the Lisbon target of 3 percent of GDP,
this a lone wou ld not have an immediate imp ac t o n i ts economic
performance. What is needed is a sustained increase in the level of
investment that would over time expand Europe’s R&D capital stock.
Figure 4 shows the decomposition of productivity growth by sector. In
three of the five economies with high productivity growth (UK, US and
the Netherlands), services have contributed substantially to high
aggregate productivity growth. The few countries that have attained
high productivity growth despite small contributions from services are
unlikely to serve as useful role models for Europe as a whole. Finland and
Austria, along with Ireland and Sweden (not included here), have
benefited from large contributions from their manufacturing sectors. But
Finland and Sweden benefited during this period from enhanced
competitiveness in the aftermath of their large devaluations in the early
There are notable differences both across sub-sectors and across
countries in terms of productivity growth in services (measured as
the ratio of real output over employment by sub-sector).
Productivity growth has typically been higher in trade and tourism
and in transport and communication. In contrast, it has been mostly
negative in social services. Finance and business services fall
in-between. Ireland and the US have both experienced positive
productivity growth in this subsector. The Netherlands, Sweden
and Greece stand out as European leaders in aggregate services
sector productivity growth, which in these cases has been propelled
largely by trade and tourism, and to some degree also by transport
and communication.
Innovation a nd productivit y growth in the EU ser vices sector 13
1990s, which provided substantial boosts to their manufacturing exports.
Ireland, similarly, benefited from massive FDI inflows, especially from the
US. These small and exceptionally open economies thus provide rather
untypical examples of manufacturing-led growth that the rest of Europe
cannot easily replicate.
Figure 4: Sector composition of labour productivity growth (annual
average growth 1995-2004, percentage points)
ICT production Goods production Market services
Reallocation Market economy
Source: van Ark et al. (2008)
Figure 5, also based on the work of van Ark et al., shows a different
decomposition of the same productivity growth. Instead of decomposing
productivity by sector, it shows the contribution from different sources:
capital deepening (i.e. equipping each worker with more productive
capital); labour composition (i.e. changes in the quality of labour); and
multifactor productivity (MFP), which is essentially efficiency gains and
technological progress.
14 Innovatio n and productivit y growth in the EU ser vices sector
Figure 5: The composition of labour productivity growth (all sectors,
annual average growth 1995-2004, percentage points)
ICT capital deepening Non-ICT capital deepeningLabour composition
Labour productivity
Source van Ark et al. (200 8)
Two conclusions emerge from this decomposition. First, the growth
contribution from fixed capital deepening is substantial, at just over
1 percentage point for the EU and more so for the US. Second, while the
growth contribution from capital deepening is relatively similar across
countries, differences in growth performance across countries are largely
driven by differences in MFP growth. Combined with the earlier
observation that services are key to cross-country growth differentials,
this suggests that efficiency gains in services may be an important driver
of aggregate productivity growth.
Innovation a nd productivit y growth in the EU ser vices sector 15
2.3 Manufacturing firms become service
Mirroring the macroeconomic shift towards services, global rankings of
leading firms, such as the Fortune 500, contain more service companies
than in previous decades. In some cases, manufacturing firms have
transformed themselves into predominantly service-providing
companies. One prominent example is IBM, which now considers itself
primarily a service business, although it still makes computers. The
production of physical goods has become secondary to firms that instead
focus on the provision of “business solutions”. This transformation of
manufacturing firms into service providers is part of a shift in the
comparative advantage of advanced economies. As China and other
lower cost producers move up the value added ladder in manufacturing,
straight goods production has fallen under intense cost pressure. Many
manufactured goods, for instance consumer electronics, have become
commoditised. High income countries have lost competitiveness in such
manufacturing. They have been able to stay competitive in part by
shifting towards business solutions rather than the sale of products, as
the price elasticity of demand for business solutions is lower than for
hardware. This shift has been accompanied by a shift towards subscription
pr icing. R ath er th an re cei ving a sin gle p ayme nt f or a pi ece o f
manufactured equipment, many manufacturers are now receiving a
revenue stream for ongoing contracts, which include a non-negligible
service component. The management literature refers to this as the
“servitisation of products”. For a discussion, see for instance Vandermerwe
and Rada (1988).
To conclude, this chapter sets the stage for the discussion that follows.
With few exceptions, high-growth OECD countries have prospered on
account of their expanding services sectors. But what are the drivers of
productivity growth in services? Tangible and intangible capital
deepening are key elements, but unlike the manufacturing sector,
innovation in services does not primarily stem from scientific R&D.
16 Innovatio n and productivit y growth in the EU ser vices sector
We need to embrace a broader definition of investment to understand
services sector innovation.
Fixed tangible investment is a key 3.
driver of productivity growth in
We saw in the previous chapter that although employment growth
was the key driver of services sector expansion, productivity growth
has also playe d a large role. Labour productivi ty in the EU services
sector has expanded by about 1 percent per year from 1995 to 2005.
Combined with their large share in aggregate output and employment,
services account for a substantial portion of aggregate productivity
growth in the EU. Those EU countries with the fastest-growing service
sectors have often had particularly high productivity performance.
This chapter sheds light on one of the key drivers of productivity
growth: fixed tangible investment. The scope is somewhat narrower
than that of the previous chapter, as it focuses on Market services,
thus excluding the social services sub-sector. In addition to
decomposing fixed investment by services sub-sector, we here also
look at the composition of investment and capital stocks across asset
types. The traditional split between non-residential construction and
machinery & equipment is augmented with a further decomposition
of the latter into ICT (information and communication technology)
equipment, transport equipment, and other equipment. This further
decomposition is important. Several studies have found that ICT-
cap it al de epen ing has be en a pa rtic ula rly im por tant d river o f
productivity gains in services. Our findings support this view, but
there are also notable differences across sub-sectors.
Innovation a nd productivit y growth in the EU ser vices sector 17
3.1 Capital deepening and productivity growth in
Market services
Tangible investment has played an important role in fostering
productivity in Market services in the EU over the past decade. Figure 6
depicts the composition of average growth of real value added in Market
services for the four largest EU countries, which represent about two
thirds of the EU economy.2 Value added is a measure of GDP at the sector
level. The pattern of growth is quite different across the various sectors
— “Trade” (Wholesale and retail trade and repair, NACE sector G),
“Tourism” (Hotels and restaurants, NACE sector H), Transport &
Communication (Transport, storage and communication, NACE sector I),
Finance (NACE sector J) and Business services (NACE sector K). Financial
and business services account for close to 60 percent of total value added
in Market services.
Economic growth can be achieved either through a larger number of
hours worked in the economy (through higher employment or an
increased number of hours worked per employee) or by making each
worker more productive. Higher labour productivity, in turn, can be
achieved by equipping each worker with more and better machinery, or
with more skills. But higher labour productivity can also be the result of
making the economy more efficient in its use of all factors of production,
i.e. both labour and capital. This is commonly known either as Total Factor
Productivity (TFP) or Multifactor productivity (MFP).
Figure 6 shows the contribution to sectoral value added growth from
these different elements. Capital deepening has in turn been
decomposed into ICT and non-ICT capital.
2 This chapter is based on data from the EUKLEMS that provides detailed growth accounting results
at the level of individual sectors for some 20 EU countries. Over and above the sector focus, it de-
livers improved growth analysis inter alia thanks to asset-specic capital inputs and by measuring
labour in hours worked by skill groups. Due to lack of data for the EU as a whole, EU aggregates are
based on own calculations.
18 Innovatio n and productivit y growth in the EU ser vices sector
Figure 6: Growth composition in market services, 1995-2005
(average growth in value added, %)
Labour quality
ICT capital Non-ICT capital
Hours worked
Value added
Trade Tourism Transport &
Finance & Business
Source: EUKLEMS; own calculations
A first insight from the figure is that Transport & Communication grew
most dynamically during this period, followed by Financial and business
services, whereas Trade and tourism recorded a more moderate speed of
growth. A second insight is that hours worked accounted for the bulk of
growth in Tourism and for a substantial part of growth in Financial and
business services. By contrast, growth in Trade as well as Transport &
Communication was to a larger extent driven by productivity
improvements. The latter fall into capital deepening, i.e. equipping each
unit of labour with more ICT and non-ICT capital, and TFP. The third
insight is that productivity growth was to a large extent propelled by
capital deepening. While there are differences across sectors as to the
relative importance of these two sources, the two largest sectors,
Financial & business services on the one hand and Trade on the other,
were characterized by capital-driven productivity advances.
Innovation a nd productivit y growth in the EU ser vices sector 19
Last but not least, the contributions from ICT capital deepening are
impressive, especially in Financial & business services considering that
back in 1995, the total stock of computers, communication equipment
and software (ICT capital) represented only a small share in the total
tangible capital stock. The other aspect that makes the growth
contribution from ICT capital deepening peculiar is the large cross-
country variation of this contribution. Among the four largest EU
countries, the UK clearly stands out for having enjoyed the largest
contribution across all sectors of Market services.
3.2 Productive investment in Market services
While employment has played an important role in propelling growth in
Market services, at least in some sub-sectors, capital deepening has also
been very influential. As Figure 7 below illustrates, investment in
productive fixed capital is as high relative to value added in Market
services as in Manufacturing. 3, 4
Productive investment totalled 18 percent of value added for the
economy as a whole. At close to 19 percent of value added, both Market
services and Manufacturing were close to the whole-economy aggregate.
In contrast, only 15 percent of output was invested in “Social services”
(not shown).
3 For the remainder of this chapter, EU refers to those 11 EU countries for which EUKLEMS provides
detailed sector-asset breakdowns for investment and capital stocks. These are Austria, Czech Re -
public, Denmark, Finland, Germany, Italy, Netherlands, Portugal, Slovenia, Sweden and the UK.
4 Tangible investment is known to be more pro-cyclical than output. Thus the share of investment
in value added tends to be lower in recessions and higher in booms. In 2005, however, the output
gap in the EU was closed according to the latest estimates by the EU Commission (AMECO) and,
hence, overall capacity utilisation was normal. Therefore, the investment shares presented in the
following are, by and large, representative.
20 Innovatio n and productivit y growth in the EU ser vices sector
Figure 7: Productive investment in the EU by sector and asset, % of
value added, 2005
FinanceTransport &
TourismTradeAll Market
Industries within market services
Non-residential construction
ICT Transport equipment Other equipment
Source: EUKLEMS; own calculations
While the overall investment intensities of Manufacturing and Market
services are very similar, the composition of investment is not. Some two-
thirds of productive investment in manufacturing consists of “other
equipment”, while it is the smallest component in Market services.
Instead, productive investment in Market services is dominated by non-
residential construction, followed by ICT and Transport equipment.
Figure 7 also shows that both the level and the composition of investment
differs notably across the different sub-sectors of Market services. This
reflects the different characteristics of individual service industries. In
terms of the asset composition of investment in individual Market
services sectors, the example of the Transport and Communication sector
is particularly intuitive. Half of the investment in this sector is devoted
to non-residential construction (e.g. street, rail, port and airport
infrastructure, warehouses, offices). Another quarter is used for transport
equipment to renew fleets of trucks, plains, ships, rolling stock etc.
Innovation a nd productivit y growth in the EU ser vices sector 21
Moreover, at 6 percent the sector comes second only to Finance in the
share of value added that is invested in ICT equipment even though ICT
is allocated only a small fraction of the sector’s large overall investment
budget. By contrast, in Finance, two thirds of investment was devoted to
ICT equipment.
Turning now to the geographic dimension, there are notable differences
in the level of investment in Market services across countries. As shown
in Figure 8, the US and Japan invested considerably less in Market services
(11 percent and 12½ percent, respectively) than the EU. But also the
variation across EU countries was large, with the productive-investment
share ranging from 11½ percent in the Netherlands to some 25 percent in
the economies in transition (Czech Republic and Slovenia). Italy, Austria
and Portugal had above-average investment, too, mostly due to very
high investment in non-residential construction.
Figure 8: Productive investment by asset, Market services (percent
of value added, 2005)
Non-residential constructionICT Transport equipment Other equipment
Source: EUKLEMS; own calculations
22 Innovatio n and productivit y growth in the EU ser vices sector
There are also interesting differences across countries in terms of the
composition of investment by asset type. The well-known “ICT spenders”
such as Denmark, Sweden, the UK and the US, devoted some
30-40 percent of fixed investment in Market services to ICT equipment,
compared with just 20 percent for the EU as a whole. This is noteworthy,
as these countries have also registered the largest growth contributions
from ICT capital deepening for the economy as a whole, as discussed in
the previous chapter. Moreover, in the UK and the US in particular, labour
productivity in the service sector has grown substantially faster than in
other countries. It is also worth noting that in all four countries overall
investment relative to value added in Market services is well below the
EU average.
The Czech Republic and Germany, in turn, may be characterized as
“Transport equipment spenders”. Other equipment tends to make for a
relatively large share of investment in the ICT-intensive market sectors of
Denmark, Sweden and the UK. Finally, non-residential constructions were
particularly dominant in Italy and Portugal (see above) but also in
3.3 Capital intensity in the service sector
Different types of capital assets have very different lifespans. High
investment in short-lived asset types, such as ICT, translates into a smaller
capital stock than would a corresponding level of investment in long-
lived assets such as non-residential buildings. Because of the large
differences in asset composition across sectors, we therefore need to
look also at the stock of capital that each worker is equipped with, before
deciding on whether a sector is fixed capital intensive or not.
Innovation a nd productivit y growth in the EU ser vices sector 23
Figure 9: Productive capital per person employed in the EU, by
sector (1000s of EUR, 2005)
FinanceTransport &
TourismTradeAll Market
Industries within market services
Non-residential construction
ICT Transport equipment Other equipment
Source: EUKLEMS; own calculations
While broadly corresponding to the investment levels seen earlier, the
capital stocks per employee shown in Figure 9 display some notable
differences. First, as expected, the share of non-residential construction
in the total capital stock is higher than its share in investment, as a
result of its higher longevity relative to other assets. Second, the
amount of capital per employee is higher in Market services than in
Manufacturing, despite similar levels of total investment. This result
follows directly from the higher share of construction in Market ser vices
investment. Among the sub-sectors within Market services, Transport &
Communication stands out as the most capital-intensive sector,
mirroring both its higher total level of investment and its large
component of construction. To illustrate, each person working in that
sector is equipped with approximately EUR 210,000 of productive
tangible capital, compared with less than EUR 40,000 in Trade and
24 Innovatio n and productivit y growth in the EU ser vices sector
Mirroring differences in investment intensity, the capital intensity of
Market services differs markedly across countries. However, capital stocks
per worker vary even more strongly across countries than investment. At
close to EUR 180,000 per worker, Denmark’s Market services are twice as
capital intensive as the EU average and 4½ times as capital intensive as
Market services in Slovenia. Second, unlike for investment, Japan is more
capital intensive than the EU, and there is now only a small difference
between the EU and the US. Third, there are striking cross-country
differences in per-worker endowment with machinery and (transport)
equipment, suggesting that within Market services, countries are
specialised on different sectors requiring different asset types. Last but
not least, endowment with ICT equipment greatly differs from one
country to the next.
Figure 10: Productive capital in EU Market services per person
employed (1000s of EUR, 2005)
Non-residential constructionICT Transport equipment Other equipment
Source: EUKLEMS; own calculations
Innovation a nd productivit y growth in the EU ser vices sector 25
3.4 Concluding remarks
Starting from the observation that tangible investment has made a
substantial contribution to labour productivity in Market services since
1995, this chapter has analysed patterns of tangible investment and
capital intensity in Market services. Among the main insights are that
Market services are as capital intensive as Manufacturing and that Market
services devote a larger share of resources to ICT capital than other
segments of the economy. Business services, in particular, have seen a
productivity-enhancing shift in capital structure towards more ICT and
less “brick and mortar” without increasing the overall capital stock per
worker. Those countries that have experienced rapid increases in labour
productivity in Market services are characterized by a particularly large
share of ICT equipment in overall tangible investment. But we also need
to caution against overgeneralisations, since Market services include a
rather heterogeneous set of activities. Transport & Communication, for
example, is capital intensive, while Trade and Tourism is labour intensive.
Intangible capital and economic 4.
The traditional concept of productive fixed capital includes tangible
assets such as non-residential buildings and machinery and equipment.
But from an economic point of view, this is a rather too narrow definition
of productive fixed capital. In principle, capital expenditure should
include any outlay that increases future output and income at the
expense of current consumption. Investment in R&D for example gives
rise to a productive capital stock similar to tangible fixed capital. The
same argument can be made for investment in human capital, in the
form of education and training. Human capital and R&D capital are key
components of the economy’s “intangible capital”, but this concept can
be broadened even further.
26 Innovatio n and productivit y growth in the EU ser vices sector
The exclusion of intangible capital from traditional measures of the fixed
capital stock was to a large extent caused by a lack of reliable data.
Intangible investment and capital tend to be more difficult to measure
than tangible fi xed capital. For much of t he pos t-war period, thi s
exclusion was not a great concern. Most advanced economies were
manufacturing-based and tangible capital accounted for the bulk of the
total productive capital stock. Over time, however, the exclusion of
intangible capital from official statistics has led to a growing
misrepresentation of the economic growth process. The reason is that
many advanced economies have shifted away from traditional
manufacturing towards services and towards economic activity that is
increasingly knowledge-based. Growth in modern post-industrial
countries has become increasingly dependent on investment in human
capital, knowledge and other forms of intangible capital. It is estimated
that intangible assets now account for between one third to half the
market value of the US corporate sector. In Europe the share of intangible
assets in the total assets of publicly-listed firms has more than tripled
since the early 1990s, to around 30 percent. Even this figure understates
the true share of intangible assets, however, because accounting
standards do not allow for treating R&D as capital, and because only
intangible assets which are actually on the balance sheet are measured.
Hall et al. (2007) show, on the basis of just over 1000 publicly-listed
European firms, that investment in R&D is a fundamental determinant of
corporate financial value and competitive advantage. These findings are
in line with other studies on US firms showing that investors view R&D as
an asset rather than as an expense.
The growing role for intangibles is visible also at the macroeconomic
level, which suggests that their exclusion from national accounts entails a
growing misrepresentation of economic activity. Neither the system of
national accounts (SNA) nor the financial accounting of firms have
traditionally allowed for the capitalisation of intangibles, for both
measurement and methodological reasons. Intangible capital such as
Innovation a nd productivit y growth in the EU ser vices sector 27
the stock of R&D or human capital is often tacit, i.e. embedded in the
skilled staff and researchers of firms. Also, such expenditures often
contain a mix of genuine capital investment (which should be capitalised)
and intermediate consumption (which should not be). Some fear that
companies might be tempted to label almost any kind of expenditure a
“capital expenditure” in order to improve their standing with investors. In
contrast, conventional fixed investment and the capital stock it generates
is relatively easy to distinguish.
Some steps have been taken towards the capitalisation of intangible
investment in the SNA. Expenditures on computer software, for example,
have already been counted as capital expenditure for a decade. Software
benefits from relatively easy measurement and is relatively distinguishable
as pure capital expenditure. It was also decided in 2008 to start counting
R&D as investment, to be implemented in a few years time.
Given the limited coverage of intangibles in official SNA statistics,
economic researchers have relied on a combination of private and public
information sources to estimate such investment. Most have chosen the
template created by Corrado, Hulten, and Sichel (2005, 2009), henceforth
referred to as CHS. They include three types of intangible assets for the
US economy:
Computerised information
(software and databases);
Scientific and creative property
(R&D, mineral exploration, copyright
and license costs, other product development, design, and other research
Economic competencies
(brand equity, firm-specific human capital
and organisational structure).
On this basis, they estimate total annual investment in intangible assets
by US businesses in the late 1990s to have amounted to some USD 1.1
trillion, or 12 percent of GDP. This is a substantial figure, a similar order of
magnitude as tangible investment. This is perhaps the single most
28 Innovatio n and productivit y growth in the EU ser vices sector
impor tant result of the ir exercise: Once the definition of capital is
broadened to include all forms of expenditure that raise the future
output potential of the economy, business sector investment is actually
twice as large as that traditionally reported.
The data collected by CHS also suggest that US investment in intangibles
has risen markedly over time. This gradual rise in intangible investment
has been of the same order of magnitude as the decline in tangible
investment, thus keeping the ratio of total investment to GDP relatively
stable over time. Not all segments of intangible investment have
contributed equally to this expansion however. Comparing the time
period 1973–1995 with 1995–2003, CHS find that overall intangible
investment grew from 9.4 percent of total national income to 13.9 percent.
Computerised information rose the most, from 0.8 to 2.3 percent.
Interestingly, while traditional scientific R&D remained flat at around 2½
percent, “non-scientific R&D” rose from 1 to 2.2 percent. Non-scientific
R&D includes innovative and artistic content in the form of commercial
copyrights, licenses, and designs, which are not counted in traditional
R&D statistics. Investment in brand equity rose from 1.7 to 2 percent,
while that in firm-specific resources increased from 3.5 to 5 percent. In
other words, while scientific R&D is traditionally seen as the key element
in knowledge creation, it has made a negligible contribution to the
ascent of US intangible capital investment in recent decades.
Innovation a nd productivit y growth in the EU ser vices sector 29
Box 2: The neo-classical growth model and growth accounting
The most common method used to empirically investigate the
composition of economic growth is called growth accounting,
drawing on the neo-classical model of the economy developed
simultaneously by Solow (1956) and Swan (1956). In the neoclassical
production function gross output is a simple function of only two
factors of production: capital and labour. These two are smoothly
but imperfectly substitutable, as can be exemplified by the
standard Cobb-Douglas production function:
(1) Y=AKαL1- α
What this function says is that aggregate output can be expanded
either by increasing the amount of labour (L) or fixed capital (K)
used in production, or thro ugh an e xpans ion of the stock of
knowledge (A). The function above has constant returns to scale.
This means that a doubling of both capital and labour also leads to
a doubling of output. At the same time there are diminishing
returns to individual inputs (i.e. α<1). Because of diminishing
marginal returns to capital, the marginal contribution to growth
from steadily increasing the capital stock for each worker will be
smaller and smaller. Consequently, the only way for the neoclassical
economy to keep growing on a per capita basis is by continuously
expanding the stock of knowledge.
The seminal contribution of Solow was his pioneering empirical
work on growth accounting. Applying his model to US data from
the first half of the 20th century, Solow (1957) could calculate the
shares of growth that s temmed directly from the expansion of
labour and fixed capital#. Whatever portion of growth that cannot
be directly explained as the result of increased factor inputs must,
according to the neo-classical model, be the result of an expanding
30 Innovatio n and productivit y growth in the EU ser vices sector
stock of knowledge. Solow’s startling discovery was that, indeed,
some nine-tenths of US growth could not be explained by the
expansion of labour and capital, but was captured by the residual
A. While knowledge is certainly one key element of this residual,
this interpretation may in fact be a bit too narrow, since empirically
the residual captures all efficiency gains in the use of factors of
production. The residual captures all increases in output for a given
combination of factor inputs. Hence it is nowadays often referred
to simply as “total factor productivity”, or TFP.
Modern growth research has found that one reason the TFP residual
accounted for such a large portion of growth in Solow’s calculations
was that early measures of fixed capital were rather too narrow. By
broadening the concept and measurement of capital, the
unexplained TFP residual can be reduced*.
# In order to do this using the relatively simple neo-classical production function and the
limited set of data at his disposal, Solow had to make a few simplifying assumptions. First,
he assumed that the US economy was on its equilibrium growth path, not unreasonably
given its long history of having a relatively free market economy. This allowed him to draw
on some generalised properties of the production function that are only true in equilibr i-
um and under the additional assumption of perfect competition. Under these circum-
stances, the wage rate equals the marginal productivity of labour and the rate of return on
capital equals the marginal productivity of capital. The income shares reflect the output
elasticity of each input. Assuming constant returns to scale, they add up to one. These are
the α and 1-α shown in equation (1). Consequently, while the output elasticities are not
directly observable, one can simply calculate the contribution of an input to output
growth as the growth rate of each input (capital and labour) multiplied by its own income
share, which is observable.
* A more comprehensive review of the modern growth literature is provided in Uppenberg
Based on their estimates of intangible investment, CHS estimate the size
of the intangible capital stock, which is then incorporated into the
standard growth accounting framework first developed by Solow (see
Box 2). As illustrated by Figure 11, productivity growth is higher in the
presence of intangible capital. The reason is that spending on intangibles,
Innovation a nd productivit y growth in the EU ser vices sector 31
which grew faster than other segments of the economy, is now included
in measured output. It was not when viewed merely as intermediate
consumption. Another consequence of treating intangibles as capital
expenditure is that it dramatically changes the observed sources of
economic growth. Capital deepening – increases in the stock of capital
per hour worked – now becomes the dominant source of growth. For the
period 1995-2003, intangible and tangible capital investment account for
broadly equal shares of growth in US output per worker.
Figure 11: Contributions to US output growth per hour worked
(percentage points)
1973-1995 1995-2003
* Capital deepening
1973-1995 1995-2003
TFP Labour composition Intangibles excl. software Software
Tangible capital excl. IT equipment
Excluding intangibles Including intangibles
IT equipment
Source: Corrado et al. (20 09)
With capital deepening explaining a larger share of growth, the
contribution from the TFP residual becomes correspondingly smaller,
falling from around half to one-third for the post-1995 period when
intangibles are included. The Solow residual also accounts for a smaller
portion of the post-1995 acceleration in US growth. When intangibles are
excluded, some two-thirds of the increase in growth is accounted for by
32 Innovatio n and productivit y growth in the EU ser vices sector
TFP. Its share drops to just over one-third when intangibles are included.
On balance, this research is suggestive of the very substantial role that
investment in intangibles has played in US economic growth.
The CHS methodology was consequently applied by Giorgio Marrano
and Haskel (2007) for the UK, by Fukao et al. (2009) for Japan, by Jalava et
al. (2007) for Finland and by Edquist (2009) for Sweden. In all of these
cases, total investment in intangible capital stood at around 10 percent
of GDP, i.e. a similar order of magnitude as in the US. However, when this
methodology has been applied to a larger number of continental
European countries, a wider range of results has emerged.
Figure 12: Intangible investment in the market sector (percent of
GDP, 2006)
Czech Rep.
Economic competencies Innovative property Computerized information
Source: van Ark et al. (2009); Edquist (2009); Fukao et al. (2009); Jalava et al. (2007); Van Rooijen-
Horsten e t al. (2008)
In the EU, with the exception of the countries mentioned above, both the
resources devoted to intangible investment and their contribution to
productivity growth have typically been of a smaller magnitude. This is
Innovation a nd productivit y growth in the EU ser vices sector 33
one of the key findings of van Ark et al. (2009). Building on existing
estimates of intangible capital for the US and several European countries,
van Ark and his co-authors extend the estimates of intangible investment
and capital to five additional European countries: Austria, the Czech
Republic, Denmark, Greece and Slovakia. The concept of intangible
capital follows the template of CHS for the US. Figure 12 provides a
comparison of intangible investment in the US, Japan and a number of
European countries, drawing on the results of van Ark et al. and other
studies using the CHS methodology.
We see h ere that the ratio of intangible investment to GDP varie s
markedly across countries, not least within the EU. Also the composition
of intangible investment varies across countries. Economic competencies
account for as much as half of total intangible investment in the US, UK
and the Netherlands, while innovative property such as copyrights and
licenses tend to dominate in Japan and a large number of continental EU
Figure 13: Intangible and tangible investment in the market sector
(percent of GDP, 2006)
Czech Rep.
Tangible investmentIntangible investment
Source: van Ark et al. (2009)
34 Innovatio n and productivit y growth in the EU ser vices sector
Figure 13 above compares the size of intangible investment with tangible
investment across a selection of countries. As seen earlier for the US,
intangible investment is of a similar order of magnitude as tangible
investment in the Nordic countries and in the three biggest EU economies.
In many other EU economies, however, investment in intangibles remains
far below tangible investment.
Figure 14: Contribution of inputs to labour productivity growth
(annual average in percent, 1995-2006)
TFP NonICTIntangiblesLabour Quality ICT
Czech Rep.
Source: van Ark et al. (2009)
Just as the level of intangible investment varies across countries, so does
its impact on economic growth. As shown in Figure 14, intangible capital
deepening (i.e. more intangible capital per unit of labour) contributed
0.7-0.8 percentage points to labour productivity growth in the US, UK,
Denmark and the Czech Republic in 1995-2006. In Germany, France and
Austria the growth contribution was slightly smaller, ranging between
0.4 and 0.6 percentage points. The smallest contributions to productivity
growth were found in Italy, Spain and Greece, where it averaged only
Innovation a nd productivit y growth in the EU ser vices sector 35
0.1-0.2 percentage points during this period. The f igure also illustrates
how non-ICT capital deepening has been delegated to a minor role in
growth during this period, with the notable exceptions of the Czech
Republic and Greece.
To sum up, this literature shows that the exclusion of intangible
investment generates a growing misrepresentation of growth in
economies specialising in knowledge-intensive production. The more
complete accounting of intangibles undertaken in recent research has
demonstrated that the business sector sets aside a much larger share of
their total resources to investment than conventional capital measures
would have us believe. This modification, in turn, has substantially
affected our perception of the drivers of economic growth. It makes both
the accumulation of knowledge and its contribution to economic growth
more explicit. Indeed, the inclusion of intangibles in aggregate
investment shows that a substantial portion of growth can be accounted
for by such investment.
But the diversity of intangible investment levels across countries is also
indicative of the highly varying speeds at which different countries are
making the transition to knowledge-based economies. Although a
sectoral breakdown is not available for these data, intangible investment
has tended to be particularly high in those countries where the services
sector has made a large contribution to productivity growth. Notable
examples are the UK , the US, the Netherlands and some of the Nordic
countries. The positive correlation between the level of intangible
investment and the role of services as a growth engine suggests that
high aggregate productivity growth will be difficult to achieve in
countries with low intangible investment and stagnant productivity in
the services sector. This is an important observation to consider if Europe
as a whole is to succeed in its ambition to catch up with US productivity
growth in coming years. The next chapter will take a closer look at the
nature of innovation in the business services sector, and how public
policy can be tailored to support innovation in services specifically.
36 Innovatio n and productivit y growth in the EU ser vices sector
Innovation in the services sector5.
We have earlier presented evidence that the services sector is becoming
increasingly important for economic growth, in terms of both
employment and productivity. It also accounts for a substantial portion
of the outperformance of fast-growing advanced countries in recent
years, d isregardi ng for now any rep osit io ning that the e conomi c
do wnt ur n may cause. A be tter un de rstand ing of th e dr ivers of
productivity growth in services is therefore important if Europe as a
whole is to improve its productivity performance. We have seen above
that investment in both tangible and intangible capital plays a role.
Investment in ICT, in particular, is instrumental in facilitating productivity
enhancing innovation in services. But there is also strong evidence in the
economics literature that these productivity gains arise only when the
new ICT hardware and software is accompanied by organisational
changes. In a recent study of the US economy, Oliner et al. (2007) observe
that ICT and intangible capital deepening accounted for a large share of
US productivity growth in the second half of the 1990s. But they also
show that this influence diminished in the first half of the 2000s in favour
of total factor productivity (TFP), i.e. the increased efficiency with which
factor inputs are used. This shift is consistent with the view that
productivity enhancing organisational changes may lag the investments
that enable them. Hence there is more to innovation -- not least in
services -- than installing more and better machinery. This chapter
therefore takes a closer look at how the services sector innovates.
5.1 Innovation has recently been redefined to
better fit its role in services
Analysis on innovation has always tended to centre on manufacturing.
Both statistical services and economic research have historically
underplayed the role of innovation in services. The realisation that services
play a substantial role in growth makes this stance untenable, however.
Efforts have recently been made to better account for innovation in services.
Innovation a nd productivit y growth in the EU ser vices sector 37
One prominent example of this is the third edition of the “Oslo Manual”
(OECD, 2005) which provides a revised definition of innovation which is
better tailored to its role in service industries. Specifically, it has been
obvious for some time that innovation in services is more geared towards
organisational changes than towards the development of new products
and processes. Indeed, it is an inherent feature of services that the final
product is difficult to distinguish from the organisation that provides it,
or from the manner in which it is provided.
To account for this, the revised Oslo Manual broadens the definition of
innovation to mean “the implementation of a new or significantly
improved product (good or service), or process, a new marketing method,
or a new organisational method in business practices, workplace
organisation or external relations.“
This implicitly identifies the following four types:
Product innovation
: the introduction of a good or service that is
new or significantly improved with respect to its characteristics or
intended uses.
Process innovation
: the implementation of a new or significantly
improved production or delivery method.
Marketing innovation
: the implementation of a new marketing
method involving significant changes in product design or packaging,
product placement, product promotion or pricing.
Organisational innovation
: the implementation of a new
organisational method in the firm’s business practices, workplace
organisation or external relations.
The first two are traditionally more closely related to technological
innovation. The last two are non-technological in nature. These are new
additions to the third edition of the Oslo Manual.
38 Innovatio n and productivit y growth in the EU ser vices sector
5.2 Manufacturing and services focus on different
types of innovation
The revised definition of innovation has been applied in recent surveys,
providing improved measurement of innovation in services. The latest
Community Innovation Survey (CIS-2006, conducted by Eurostat on
behalf of the European Commission) shows clearly that a too narrow
definition of innovation (limited to technological innovation) would
underestimate the occurrence of innovation in services.
The survey identifies “in-house” innovation as that which is mainly
developed within the firm. On this score, the number of firms engaged in
in-house product innovation (products that are new to both the firm
and the market) is on average around one-third lower in services than in
manufacturing, as shown in Figure 15.
Figure 15: In-house product innovators by sector (as a percentage of
all firms, 2004-06)
Czech Rep.
Manufacturing Services
Source: OECD STI Scoreboard 2009
Innovation a nd productivit y growth in the EU ser vices sector 39
The gap between services and manufacturing is somewhat smaller (one-
quarter) as regards the percentage of firms engaged in process
innovation (Figure 16).
Figure 16: In-house process innovators by sector (as a percentage of
all firms, 2004-06)
Czech Rep.
Manufacturing Services
Source: OECD STI Scoreboard 2009
The gap between manufacturing and services virtually disappears,
finally, in the percentage of firms that engage in non-technological
innovation such as a marketing or organisational innovation (chart 17
below). Note that the percentage of firms involved in such innovation is
also much higher across the board than in the case of product or process
40 Innovatio n and productivit y growth in the EU ser vices sector
Figure 17: Non-technological innovators (as a percentage of all
firms, 2004-06)
Czech Rep.
Manufacturing Services
Source: OECD STI Scoreboard 2009
5.3 Average firm size in services is smaller, and
they benefit from clustering
The CIS-2006 also shows that a lower percentage of SMEs engage in
innovation than do large firms. This should be born in mind when
assessing the lower incidence of innovation in services. Most firms in the
services sector are relatively small. On average in the EU-27, around three-
quarters of service sector value added are generated by firms with less
than 250 employees (i.e. SMEs and micro-sized firms). In manufacturing,
the SME/micro share of total value added is only around one-half.
Smaller firms tend to devote less resources to in-house innovation,
whether in the form of scientific R&D or other types of intangible
investment. Typically lacking the resources for substantial internal
innovation, they are more dependent on externally generated innovation
Innovation a nd productivit y growth in the EU ser vices sector 41
and technology, for example off-the-shelf software and IT hardware.
They also benefit from sharing the costs of innovation and infrastructure
with other similar firms, which suggests that they are prone to
The European Cluster Observatory (financed by the Commission in the
framework of its Europe INNOVA initiative) has shown that clustering in
services is highly correlated with GDP per capita. This is most evident for
clusters in business services, financial services and information
technology. Evidence for positive effects from clustering in services is
indicative of what “eco-systems” allow innovative services to flourish.
Figure 18 illustrates this point. The 2006 Innobarometer survey showed
that a larger portion of services sector firms gave their cluster credit for
their own innovation (dark blue) than did industrial firms.
Figure 18: Clustering helps services innovate
Yes, and being in a cluster region facilitated it Don't know
Yes, but being in a cluster region had no bearing on this No
High & medium
high tech industries
Low & medium
low tech industries
Knowledge intensive
Less knowledge
intensive services
Source: European Commission (200 6), Innobarometer
42 Innovatio n and productivit y growth in the EU ser vices sector
5.4 Some services are more innovative than
One problem with assessing innovation in services is that it includes a
very heterogeneous group of activities. Some types of services are
particularly uninnovative, which pulls down the average. Services with
high levels of technological opportunity, such as computer services,
telecommunications, transport and R&D and engineering services stand
at the core of what Eurostat calls “Knowledge Intensive Services” (KIS).
Eurostat’s definition of KIS is relatively broad, which has the effect that it
covers around half of total service sector employment and one-third of
total employment in the EU (Figure 19).
Figure 19: Employment in knowledge-intensive service sectors
(share of total employment, percent)
1995 2005
US EU-25 Japan
Source: PRO INNO Europe paper No. 12, 2009
Unlike the services sector as a whole, the KIS segment is not that different
from manufacturing in terms of R&D intensity or the share of output that
comes from new products. The KIS segment is important for aggregate
productivity growth, and there is a strong positive correlation between
Innovation a nd productivit y growth in the EU ser vices sector 43
the employment share of the KIS and GDP per capita, as shown in Figure
20. The causality here likely goes in both directions, i.e. rich countries
may have higher aggregate demand for KIS services. However, we have
seen earlier that services contribute very differently to aggregate
productivity growth across countries, and the employment share of KIS is
also strongly correlated with overall innovation scores. This suggests that
knowledge intensive services do play a non-negligible part in overall
services sector innovation, and in its contribution to aggregate
productivity growth.
Figure 20: Employment share in knowledge-intensive services vs.
GDP per capita
10 15 20 25 30 35 40 45 50
GDP per capita 2007
Employment share of KIS, 2007 (%)
Source: Eurostat and European Commission (AMECO database)
5.5 How do service sector firms innovate? Results
from the NESTA innovation survey
Because of the heterogeneity of service industries, it is difficult to
generalise too much about their innovative process. We therefore now
turn to take a closer look at how a sample of individual service industries
44 Innovatio n and productivit y growth in the EU ser vices sector
conduct their innovation. This section draws on a UK survey, which
usefully distinguishes between different stages of the “innovation value
chain”, from the formation of knowledge all the way through to commercial
applications and value creation, which in turn is the basis for measuring
productivity. This is helpful, as different industries with similar overall levels
of innovation may focus on different stages of the value chain.
That innovation should be reflected in value creation was first suggested
by Joseph Schumpeter, who argued that innovation is not just a new idea
or invention, but the in cr ea se d produc tivit y that stems fro m its
application. Innovation is thus inseparable from the economic value that
it generates. This is a very serviceable definition of innovation, since it
makes it measurable in quantitative/monetary terms. By any other
measure, how could one possibly compare two different inventions?
The study, by the UK National Endowment for Science, Technology and
the Arts (NESTA, 2009), draws on a survey of 1500 UK companies. It covers
nine sectors, selected to provide a representative cross-section of the
economy. These include both industries that are believed ex ante to be
knowledge-intensive and those that are not.
The nine sectors included in the survey are:
Automotive sector
Specialist design
Energy production
Accountancy services
Architectural services
Consultancy services
Legal services
Software & IT services
Of these, the last five are in services (shown in blue in the list).
Innovation a nd productivit y growth in the EU ser vices sector 45
Sectors innovate differently, emphasising different stages of the
innovation value chain. The NESTA survey identifies three distinct
Accessing knowledge
(through in-house investment in knowledge,
collaboration with other organisations, or acquisition of external
Building innovation capacity
(as firms translate their knowledge
investments into innovation outputs);
Commercialisation/value creation
(as firms seek to exploit their
innovations in the market place).
In order to measure the innovative capabilities of each sector, in each of
the three stages, the survey identifies a number of metrics assessed at
firm level. In order to measure each sector’s innovativeness through the
innovation value chain, the survey covers the 16 firm-level metrics. Many
of these elements are particular to each of the three stages. For example,
the Accessing Knowledge stage includes metrics reflecting the firm’s
internal R&D and design expenditure. Building Innovation inclu des
spending on process change and the extent of new products and services
in total sales. Commercialising Innovation includes metrics relevant to
successfully taking an innovati on to market, such as the nature of
involvement with customers and the use of IP protection. Then there are
also metrics that are common across all three stages. For example, the
use of different internal skill groups and the use of external partners are
not limited to a specific stage.
In a second step, the firm-level metrics are weighed and translated into
sectoral innovation indices, as shown in Figure 21. These are constructed
with the aim of allowing for a comparison of the level and variability of
innovativeness across sectors, and across the three stages of the
innovation value chain. In addition, the variation of firms in each sector is
used as a measure of the scope for knowledge transfer within sectors.
46 Innovatio n and productivit y growth in the EU ser vices sector
These results are then used as an indication of the potential for
productivity gains through the adoption of best practice, either within or
across sectors.
While some sectors have an evenly high level of innovative capacity
across all three stages (most notably IT and Consultancy services), others
are more uneven (Automotive and Specialist design, along with several
service industries).
Figure 21: Sectoral innovation indices
Software and
IT services
Accessing knowledge Building innovation Commercialising innovation
Source: NESTA (2009)
5.6 Improving innovative capabilities by learning
from best practice
The guiding principle of the NESTA survey was that the innovation
capability of individual sectors can be enhanced by learning from best
Innovation a nd productivit y growth in the EU ser vices sector 47
practice, whether residing inside the sector or in other sectors. If such
learning does not occur spontaneously, there may be a role for the
government to serve as a facilitator. The approach taken by NESTA is
consistent with the view that technological innovation plays a secondary
role in services sector innovation, as implied by the CIS results discussed
earlier. If true, the allocation of resources (whether public or private) to
the creation of new scientific knowledge is likely less effective in the
context of fostering services sector innovation than the dissemination of
best practice and knowledge spillovers, for instance through cluster
In the NESTA framework, the scope for intersectoral learning is proxied by
the gap of each sector and stage relative to that with the highest score,
which is assumed to represent economy-wide best practice for each
stage of the innovation value chain. The scope for learning from best
practice within each sector is represented by the standard deviation of
firm scores within each sector. is mapping provides a guide to sector-
specific strategies for lifting innovative capacity through the adoption of
best practice.
On this basis, four sectors stand out as having rather extreme profiles.
Accountancy and construction display very large inter-sectoral gaps for
each stage of the innovation value chain, suggesting greater scope for
inter-sectoral learning of innovation best practice. At the same time,
however, accountancy and construction firms have relatively low intra-
sector variability, which implies limited scope for learning from other
firms in their own sectors. At the other extreme, consultancy and
software/IT services have small or non-existent gaps to best practice for
each element of the value chain. Consultancy firms also have relatively
low intra-sector variability, which implies limited scope also for intra-
sector learning. Firms in the software and IT services sector, on the other
hand, display a greater degree of intra-sector variability in their
innovation capability. Here there is greater scope for learning from best
practice within the sof tware and IT services sector itself. Other sectors
48 Innovatio n and productivit y growth in the EU ser vices sector
fall in between these extremes. Architectural services display low
variability within the sector but a relatively large inter-sectoral gap. If this
sector is to improve its innovative capabilities, it would have to draw on
best practice in other sectors, for instance consultancy and specialist
design. The latter stands to gain relatively more from intra-sector
learning, on account of its greater intra-sector variation.
One key observation made in the NESTA study is that the need to learn
from and adopt best innovation practice is not always equal across all
three stages of the innovation value chain. Relatively few sectors have
large gaps to best practice in the first and third stages of the innovative
value chain. In the second stage, however (“Building Innovation
Capacity”), only t wo sectors have sma ll gaps to best prac tice. This
suggests that particular policy attention is needed in improving the
ability of firms to build on their knowledge investments to generate
more commercially viable innovative products and services.
5.7 Innovative firms grow faster
One final finding of the NESTA survey is that firms with high innovative
capacity expanded substantially faster on average than non-innovative
firms (Figure 22). The gap is also visible in services (except in architecture,
where the innovative lead is relatively small). To the extent that the UK
can serve as a role model for the rest of Europe, this suggests that
broadening the innovative capability of firms in the services sector holds
the key to faster service sector-led growth.
Possible methodological shortcomings notwithstanding, the NESTA
study does provide a telling illustration of how individual service
industries differ, not only in their overall innovative capacity, but also in
their focus on the different stages of the innovation value chain. One
lesson here is for instance that sectors suffering from structural
weaknesses in the commercialisation of knowledge would enjoy limited
benefits from increased investment in the creation of new knowledge.
Innovation a nd productivit y growth in the EU ser vices sector 49
These results point to an alternative role for public policy in the context
of service sector innovation, as a facilitator of learning from best practice,
as opposed to supporting investment in R&D and in-house generation of
new knowledge.
Figure 22: Sales growth for UK innovators and non-innovators,
by sector (annual percent growth, 2006-2009)
-5 0 5 10 15 20 25 30 35 40
Energy production
Specialist design
Software & IT services
Legal services
Source: NESTA (2009)
The various sections of this survey paper have individually made some
striking observations. Services account for a non-negligible portion of
the productivity lead of highly innovative economies, most notably the
US (Chapter 2). While Europe on average does not lag behind in terms of
fixed tangible investment in the services sector, the shift towards ICT
equipment has been even more pronounced in the US than in Europe
(Chapter 3). Europe does lag the US with respect to intangible investment,
and especially in economic competencies (Chapter 4). Given the large
role that intangible investment has played in US productivity growth in
the past decade-and-a-half, this imbalance needs to be addressed if the
50 Innovatio n and productivit y growth in the EU ser vices sector
transatlantic productivity gap is to be narrowed. The academic literature
points to strong synergies between tangible fixed capital, investment in
knowledge and in human and organisational capital. An imbalance in the
resources allocated to tangible vs. intangible capital may therefore
hamper the final productivity-payoff. But innovation in services is not
just about the resources allocated to ICT and intangible investment. In
order to boost productivity, service industries must draw on these
investments to reshape the way they conduct business, and to invent
entirely new services. For such innovation to occur, appropriate
framework conditions must be in place, including product and labour
market flexibility, competition, and free trade of services across borders.
In services as in other industries, survival and the ambition to outrun the
competition is the most powerful incentive to innovate.
A final conclusion that emerges from the literature and data surveyed
above is that the nature of knowledge formation itself is different in
services. Although some service industries do invest substantial amounts
in scientific R&D, many do not. Average firm size in most service industries
is small and the resources devoted to in-house knowledge creation are
limited. Instead, surveys show that services rely extensively on external
sources for new knowledge, most notably through their ties with
customers and other firms. Yet the widespread lack of patenting of non-
technological innovations tends to limit the dissemination of such
knowledge. As discussed in Chapter 5, many service industries would
stand to gain substantially from learning from best practice in other firms
and even in other sectors, yet many are relatively closed to information
sharing and cooperation, partly for competitive reasons. The lack of
effective IP protection for non-technological innovation raises the risk of
suboptimal levels of knowledge transfers and wasteful duplication of
innovative efforts, protected by secrecy. In light of these observations,
public support for the dissemination of best practice and the formation
of knowledge intensive service clusters are attractive complements to
traditional R&D subsidies in fostering more innovation in the ser vices
Innovation a nd productivit y growth in the EU ser vices sector 51
Corrado, C.A., Hulten, C.R. and Sichel, D.E. (2005). “Measuring capital and
technology: An expanded framework, in Corrado, C.A., Haltiwanger, J.
and Sichel, D.E. (eds.), Measuring capital in the new economy. NBER
Studies in Income and Wealth, (65), University of Chicago Press, Chicago,
Corrado, C.A., Hulten, C.R. and Sichel, D.E. (2009). “Intangible capital and
US economic growth”. The Review of Income and Wealth, (55:3), pp. 661-685.
Edquist, H. (2009). “How much does Sweden invest in intangible assets?”
Research Institute of Industrial Economics Working Paper No. 785.
Fukao, K., Hamagata, S., Miyagawa, T. and Tonogi, K. (2009). “Intangible
investment in Japan: Measurement and contributio n to eco nomic
growth”. The Review of Income and Wealth, (55:3), pp. 717-736.
Giorgio Marrano, M. and Haskel, J. (2007). “How much does the UK invest
in intangible assets?”. CEPR Discussion Paper No. 6287.
Hall, B.H., Thoma, G. and Torrisi, S. (2007). “The market value of patents
and R&D: Evidence from European firms”. NBER Working Paper No. 13426.
Jalava, J., Aulin-Ahmavaara, P. and Alanen, A. (2007). “Intangible capital in
the Finnish business sector 1975-2005”. Discussion Papers 1103, The
Research Institute of the Finnish Economy.
OECD (2005). “The measurement of scientific and technological activities:
Proposed guidelines for collecting and interpreting technological
innovation data”, OECD, Paris.
Oliner, S., Sichel, D.E., Stiroh, K.J. (2007). “Explaining a productive decade”.
Brookings Papers on Economic Activity, 2007/1.
52 Innovatio n and productivit y growth in the EU ser vices sector
NESTA (2009). Measuring sectoral innovation capability in nine areas of the
UK economy. Report for NESTA Innovation Index project. November
Solow, R.M. (1956). “A contribution to the theory of economic growth”.
Quarterly Journal of Economics, (70), pp. 65-94.
Solow, R.M. (1957). “Technical change and the aggregate production
function”. Review of Economics and Statistics, (39), pp. 312-320.
Swan, T.W. (1956). “Economic growth and capital accumulation”. Economic
Record, (32:2), p.334-61.
Uppenberg, K. (2009). “Innovation and economic growth”. EIB Papers,
(14:1), pp. 10-35.
van Ark, B., O’Mahony, M. and Timmer, M. (2008). “The productivity gap
between Europe and the U.S.: Trends and causes”, Journal of Economic
Perspectives, 22 (1), pp. 25-44.
van Ark, B., Hao, J.X., Corrado, C., and Hulten, C. (2009). “Measuring
intangible capital and its contribution to economic growth in Europe”.
EIB Papers, (14:1), pp. 62-93.
Vandermerwe, S. and Rada, J. (1988) “Servitization of business: Adding
value by adding services”, European Management Journal, vol. 6, no. 4,
198 8.
van Rooijen-Horsten, M., van den Bergen, D., de Haan, M., Klinkers, A. and
Tanriseven, M. (2008). “Intangible capital in the Netherlands: Measurement
and contribution to economic growth”, Discussion Paper No. 08016,
Statistics Netherlands, The Hague.
European Investment Bank • European Investment Bank • European Investment Bank • European Investment Bank
European Investment Bank
Economic and Financial Studies
98-100, boulevard Konrad Adenauer
L-2950 Luxembourg
3 (+352) 43
8215 4
5 (+352) 43
© EIB – 07/2010 QH-31-10-501-EN-C © EIB GraphicTeam
... In some economies, such as Vietnam, there is a noticeable "shift" of labour from the agricultural sector to the manufacturing sector (McCaig and Pavcnik 2013). On the other hand, a trend of increasing employment in the service sector has been observed in Europe, at the expense of the manufacturing sector, which is a reason why service industries are the main driver of technological development in Europe (Uppenberg and Strauss 2010). Namely, the reallocation of human resources from one sector to another changes the potentials of technological growth, as the human capital itself is an important determinant of technological development (Baltagi et al. 2016;Seyoum et al. 2015). ...
Full-text available
Technological efficiency is one of the main factors of economic growth in modern history. Technologies have traditionally been important for manufacturing sector, but the age of digitalization has also made service sector increasingly rely on modern technologies. There are not many studies measuring the technological trends of these two sectors. This study uses the micro approach of the dynamic panel to measure productivity of the manufacturing and service sectors in Montenegro during 2010 to 2019, between the two global economic crises, using firm level data. The results indicate a clear upward technological trend in manufacturing but not in the service sector. Divergent technological trends are found amongst the manufacturing and service industries that require different level of technologies and knowledge in their production processes. The study concludes that there is a room for further technological improvements in both sectors and proposes concrete policy measures for further development.
... Although jobs in manufacturing may require more physical strength, dexterity, and agility, which tend to decline with age, the manufacturing sector has become less relevant, especially in countries with the most severe demographic aging. By contrast, the service-industry Börsch-Supan, Hunkler, Weiss 8 sector is expanding not only in economic importance and share of the labor force, but also in terms of the diversity of tasks performed by different teams (Uppenberg and Strauss 2010). This diversity of tasks performed is of importance because we can expect systematic differences in the age composition between different types of teams. ...
Full-text available
Does productivity decline with age? Does population aging harm economic growth? We exploit process-generated data from a large and typical service-sector company. We find no decline in average productivity in the age range of 20-60. This result is precisely measured. Our innovative identification strategy corrects for sample selection, endogeneity of age composition and age-cohort confounding. Our big data are essential to extract the signal from the noise that has marred many previous studies. While average productivity stays flat, we find variation according to task complexity. Productivity increases with age in teams with more demanding tasks and decreases in routine tasks.
... The main hypothesis can be, however, described by two auxiliary hypotheses (H1a and H1b). In the long run, regions can compete on the global market only by technological progress and increasing productivity (Solow 1988) since expansion of the population and workforce and exploiting natural resources has its limits (Uppenberg -Strauß 2010). Therefore, successful transition has to be based on knowledge resources that need to be present and achievable in a transition region before changes. ...
Full-text available
The aim of this paper is to identify the differences in the determinants of successful transition (understood as the creation of a new development path) between the eastern and the western EU Member States between 1994 and 2014 and elaborate assumptions for a strategy of constructing regional advantage for them at the NUTS2 level. We find that the regional transition requires individual approaches to using comparative advantage at the beginning of the process and then competing with specific advantages that can be consciously constructed throughout the process. Therefore, we hypothesise that a successful transition requires constructing regional advantages based on the knowledge-related factors, leading to specialisation in the knowledge-intensive industries. Furthermore, we state that the way of constructing such advantages differs across the regions. All of our hypotheses were confirmed. Both groups of regions had different comparative advantages at the beginning of the period and constructed competitive advantage based on related knowledge-intensive industries, leading to their specialisation. Interestingly, although the process of building regional advantage was similar, the factors used to create it were different, had a different impact on GDP growth and led to a different specialisation.
... This revised definition of innovation has been applied in composing the Community Innovation Survey, the European Commission's official instrument for measuring the innovation performance of its member states. The latest survey (CIS 6) reveals that marketing or organizational innovation prevailed over product or process innovation (Uppenberg and Strauss, 2010)". ...
Full-text available
This book explores the innovation culture in Croatia from a theoretical and empirical point of view. The initial assumption is that national/regional culture, innovation and entrepreneurship interact in a way that affects economic innovation and social progress. The book consists of three parts. The first part seeks to clarify the theoretical framework and concept of innovation and innovation culture and consists of five subchapters that discuss the concept of innovation, and cultural theories that link cultural factors and economic growth. Hofstede's model is presented in detail since empirical research is based on it. The second part of the book presents an empirical study of inter-regional cultural differences in Croatia using the Hofstede model with the aim of identifying possible implications of cultural differences on regional innovation capacities and overall development. The basic conclusion is Hofstede's approach has not proved to be a productive theoretical and analytical framework for researching the impact of regional innovation culture on innovation within a country in this case Croatia. Hofstede’s approach, which is methodologically quite simple and prone to hyper empiricism, has proven far more fruitful in exploring intercultural differences globally between multiple countries. Thus, the third part of the book suggests that due to the limited application of Hofstede’s model, an alternative approach is found to study the “hidden” social factors that influence the weak dynamics of innovation and entrepreneurship. Fertile ground for such an alternative approach was found in the relatively rich literature of Croatian authors who analyzed various socio-cultural and political factors of Croatia's weak economic growth during the transition. These studies were divided into two main groups. One, developed by sociologists who see the causes of backwardness in the "crossed path", the cultural heritage of socialism and cultural inertia, and the other, developed by political economists who see the reasons for backwardness in a special form of capitalism developed in the post-socialist period. the clientelist variant of capitalism and the corruption closely connected with it. Finally, the epilogue gives a brief overview of the recent political circumstances that led to the collapse of the Croatian government only 6 months after the December 2015 general elections as confirmation of the main conclusion that corruption is the wrong political discourse that divides Croatian society according to outdated ideologies, political views, ethical values, worldviews and behaviors, the biggest barrier to innovation and entrepreneurship. In this way, cultural and social factors and the “state of mind” prove to be decisive in the development of innovation but analyzed from the aspect of socio-economic reality. Such an approach allows, unlike relatively abstract global cultural theories, mobilization activities to overcome the existing state.
... Nowadays, the services sector is developing rapidly and even dominates modern economies, in comparison with other productive sectors (Uppenberg and Strauss, 2010). Unlike other productive sectors, the services sector has relatively low productivity and innovation, and its technical progress is dependent on other sectors. ...
Full-text available
Purpose Although recent studies have increased attention on the effects of related and unrelated variety on innovation, a Chinese test has until now been missing from the literature. This paper aims to investigate how related and unrelated variety affect regional innovation in Chinese provinces. In particular, emphasis was placed on differentiating the analysis for the industry and services sectors at a detailed sectoral level. Design/methodology/approach This paper’s sample is composed of 30 provinces in China from 2003 to 2016. Feasible generalized least squares was used to estimate the effects of related and unrelated variety on regional innovation. Findings The results show that related variety in all sectors promotes regional innovation, whereas unrelated variety in all sectors does not play a role. In-depth analyses were performed by comparing the industry and services sectors. Only related variety in the industry sector and unrelated variety in the services sector promote regional innovation, whereas unrelated variety in the industry sector exerts a negative effect. After dividing the country into eastern, central and western regions, different findings appear in the sub-samples. Originality/value This study contributes to the literature on evolutionary economic geography and innovation by exploring how related and unrelated variety promote regional innovation in a developing country context (China). It also sheds light on the sectoral and regional differences in the influence of related and unrelated variety on regional innovation.
Technical Report
Full-text available
Welche Relevanz besitzt Wirtschaftswachstum für das Erreichen umweltpolitischer Ziele? Der Bericht analysiert die Argumente verschiedener Positionen in diesem Diskurs und formuliert eine idealtypische „vorsorgeorientierte Postwachstumsposition“. Er präsentiert zudem Ursachen von Wirtschaftswachstum und identifiziert gesellschaftliche Bereiche, deren Funktion vom Wirtschaftswachstum abhängen könnte. Darüber hinaus werden Reformvorschläge diskutiert, um diese Wachstumsabhängigkeit zu verringern. Der Bericht zeigt die Vielschichtigkeit der Wachstumsdebatte auf und setzt Impulse für die öffentliche Auseinandersetzung, wie gesellschaftliches Wohlergehen innerhalb planetarer Grenzen verwirklicht werden kann.
This article emphasizes the fact that the implementation of the recommendations of the International Labor Organization to increase efficient and productive employment in the country, its calculation and analysis based on national labor market indicators is one of the important tasks in the fight against poverty in many countries. The presence of a employed population among those suffering from poverty in the global labor market underscores the need to calculate productive employment. The article describes in detail the indicators of efficient and productive employment, their analysis and calculation. The article also concludes with recommendations for increasing efficient and productive employment.
Using the 2018 World Bank enterprise data, this study sought to establish whether the determinants of labor productivity in the Kenyan private service sector varied with the size of the firm. Unlike previous studies that just focus on the determinants of labor productivity among manufacturing firms; this study employed the two‐stage switching regressions model to correct for the firm‐size effect. The findings revealed that capital intensity, employee wage, high school education, and managers' experience impacted positively and significantly on labor productivity while tax burden and power outages significantly decreased labor productivity across all firms. The differences in the determinants of labor productivity across both firms were, however, found to be negligible and insignificant. With the political uncertainty and tax burden constraints perennially defining the Kenyan economy, the study recommended the provision of a favorable business environment and investment in human capital as key channels of optimizing service sector productivity. The selectivity variable was also significant across both firms, hence supporting the role of self‐selection in labor productivity studies. Correcting for the firm‐size effect was very crucial; something that has been largely ignored in previous studies on labor productivity.
Full-text available
Australian and New Zealand environmental economists have played a significant role in the development of concepts and their application across three fields within their subdiscipline: non-market valuation, institutional economics and bioeconomic modelling. These contributions have been spurred on by debates within and outside the discipline. Much of the controversy has centred on the validity of valuations generated through the application of stated preference methods such as contingent valuation. Suggestions to overcome some shortcomings in the work of environmental economists include the commissioning of a sequence of non-market valuation studies to fill existing gaps to improve the potential for benefit transfer. Copyright 2005 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd..
Full-text available
ABSTRACT : This paper is the first effort to analyze the intangible investments of the Finnish non-financial business sector in 1975–2005 with a heretofore unseen scope of intangible investments in line with the definition of Corrado, Hulten and Sichel (2005, 2006). Not only GDP but also investments have become more weightless as the importance of scientific innovative property and economic competencies has increased. In 2005 Finnish business intangible investments amounted to 14.2 billion euro, which was 9 per cent in relation to (unrevised) GDP. Our results imply higher investments rates and lower labor shares than traditionally thought. Comparing our new results with SNA93-type growth decompositions we found that our revision increased the average growth rate of labor productivity by 0.48 percentage points in 1995–2000 and 0.06 percentage points in 2000–2005. Capitalizing intangible investments decreased the measure of our ignorance by 0.12 percentage points in 1995–2000 and 0.45 in 2000–2005. A shift to new, intangible, investments with higher marginal products than traditional capital has taken place. It is not any longer solely a matter of how much is invested, but what it is firms invest in.
Full-text available
This paper constructs a data set to document firms' expenditures on an identifiable list of intangible items and examines the implications of treating intangible spending as an acquisition of final (investment) goods on GDP growth for Canada. It finds that investment in intangible capital by 2002 is almost as large as the investment in physical capital. This result is in line with similar findings for the U.S. and the U.K. Furthermore, the growth in GDP and labor productivity may be underestimated by as much as 0.1 percentage point per year during this same period.
I. Introduction, 65. — II. A model of long-run growth, 66. — III. Possible growth patterns, 68. — IV. Examples, 73. — V. Behavior of interest and wage rates, 78. — VI. Extensions, 85. — VII. Qualifications, 91.
В статье производится анализ агрегированной производственной функции, вводится аппарат, позволяющий различать движение вдоль такой функции от ее сдвигов. На основании сделанных в статье предположений делаются выводы о характере технического прогресса и технологических изменений. Существенное внимание уделяется вариантам применения концепции агрегированной производственной функции.
Published macroeconomic data traditionally exclude most intangible investment from measured GDP. This situation is beginning to change, but our estimates suggest that as much as $800 billion is still excluded from U.S. published data (as of 2003), and that this leads to the exclusion of more than $3 trillion of business intangible capital stock. To assess the importance of this omission, we add intangible capital to the standard sources-of-growth framework used by the BLS, and find that the inclusion of our list of intangible assets makes a significant difference in the observed patterns of U.S. economic growth. The rate of change of output per worker increases more rapidly when intangibles are counted as capital, and capital deepening becomes the unambiguously dominant source of growth in labor productivity. The role of multifactor productivity is correspondingly diminished, and labor's income share is found to have decreased significantly over the last 50 years. Copyright 2009 The Authors. Journal compilation International Association for Research in Income and Wealth 2009.
Australian and New Zealand environmental economists have played a significant role in the development of concepts and their application across three fields within their subdiscipline: non-market valuation, institutional economics and bioeconomic modelling. These contributions have been spurred on by debates within and outside the discipline. Much of the controversy has centred on the validity of valuations generated through the application of stated preference methods such as contingent valuation. Suggestions to overcome some shortcomings in the work of environmental economists include the commissioning of a sequence of non-market valuation studies to fill existing gaps to improve the potential for benefit transfer. Copyright 2005 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd..
We attempt to replicate for the UK the Corrado, Hulten and Sichel (2005, 2006) work on spending on intangible assets in the US. Their work suggests private sector expenditure (investment) on intangibles is about 13% (11%) of US GDP 1998-2000, with intangible investment about equal to tangible capital investment. Our work, using a similar method, suggests the UK private sector spent, in 2004, about £127bn on intangibles, which is about 11% of UK GDP. The implied investment figure is around £116bn (10% of GDP) which is about equal to UK investment in tangible assets. Of the £127bn expenditure, (in round numbers) about 15% is spent on software, about 10% on scientific R&D, almost 20% on non-scientific R&D (design, product development etc.), about 14% on branding, about 20% on training and the rest on organisational capital.