The knowledge economy in Europe : a review of the 2009 EIB conference in economics and finance.
Date: 2010-10-13
Institutions: European Investment Bank
Subjects: conference proceedings, financing, innovation, intellectual capital, knowledge economy, macroeconomics, research and development

European Investment Bank • European Investment Bank • European Investment Bank • European Investment Bank

 The knowledge economy 
in Europe

A review of the 2009 EIB Conference  
in Economics and Finance

by Kristian Uppenberg

About the author

Kristian Uppenberg is a Senior Economist in the Economic and 

Financial Studies division of the EIB, specialising in issues related 

to innovation and economic growth.

Disclaimer

The views expressed in this document are those of the author 

and do not necessarily reflect the position of the EIB.

 The knowledge economy 
in Europe

A review of the 2009 EIB Conference  
in Economics and Finance

by Kristian Uppenberg

The knowledge economy in Europe 

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1.   Preface
by EIB President Philippe Maystadt

Founded by the Treaty of Rome in 1958, the 
European Investment Bank (EIB) is a major 
f inancial  ins titution  supp or ting  the 
European Union’s public policy objectives. 
A m o n g   s u c h   o b j e c t i v e s ,   e c o n o m i c 
integration,  convergence  and  regional 
cohesion have featured most prominently 
over the years in the EIB’s operations. In 
concrete terms, this has meant the EIB providing financial and advisory 
support to countless infrastructure and other projects connecting 
European countries, regions and people. 

But as the European economy has evolved over time, so has the EIB. 
Specifically, in the decades following World War II, the European economy 
was dominated by the expansion of traditional manufacturing. In this 
context, investment for the most part meant infrastructure, buildings, 
machinery and equipment. These remain substantial components in 
overall investment, but the European economy has over time become a 
predominantly post-industrial society. Today, services account for around 
70 percent of value added and employment in the EU. Investment in this 
economy does not mean quite the same as it meant in the manufacturing-
dominated societies of the post-war era. A large portion of business 
sector investment today consists of investment in “knowledge”.

This is reflected in the operations of the EIB. Today, a non-negligible 
portion of the EIB Group’s activities is directed at the knowledge economy. 
To illustrate, in 2009, the EIB provided about €18 billion in support of (i) 
research and development, (ii) innovation, and (iii) education and training. 
This accounts for around one-third of the EIB’s total lending.

  Plutarchos Sakellaris (EIB Vice President) and Philippe Maystadt (EIB President)

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The knowledge economy in Europe

 
Against this background, for the EIB a sound understanding of the 
knowledge economy is crucial. What drives investment in the knowledge 
economy? What hinders it, and how could possible roadblocks be 
removed?  How  does  investment  in  knowledge  affect  aggregate 
economic performance? These questions were addressed at the 2009 EIB 
Conference in Economic and Finance1, titled “R&D and the Financing of 
Innovation in Europe” (henceforth referred to simply as the “2009 EIB 
Conference”). The conference papers were published in volume 14 of the 
EIB Papers2. 

This overview discusses some key findings of the papers presented at the 
conference and draws some policy conclusions from them in the context 
of the broader literature. The papers and the wider academic discussion 
are sorted into three broad groups. The first looks at macroeconomic 
issues: The measurement of intangible capital and how this affects 
economic  growth  (Sections  2-4).  The  second  group  analyses  the 
motivations of firms to invest in R&D and the role of public policy in 
spurring innovation (Section 5). The third group focuses on the financing 
of innovation (Section 6). Section 7 concludes.

2.   R&D investment and capital stocks
One of the key findings of the empirical growth literature of the past half-
century is that the increased supply of labour and fixed and human 
capital can only account for between half and two-thirds of economic 
growth in most countries. The remainder is driven by something else. 
Over time the empirical literature has shown that this residual can be 
broadly defined as the stock of “knowledge”. It is also commonly referred 
to as Total Factor Productivity (TFP), since it entails an expansion in 
output for a given set of inputs. 

1  The Conference was held in Luxembourg on 22 October 2009
2 

 Hard copies are available on request from the EIB (infoefs@eib.org). Electronic versions are avail-
able from the EIB web site: http://www.eib.org/infocentre/efs/publications/eib-papers/index.htm

The knowledge economy in Europe 

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Another finding of the empirical literature is that investment in research 
and development (R&D) is a key input into the process of innovation and 
in the expansion of the knowledge stock. Other things being equal, 
countries and sectors devoting a larger share of their resources to R&D 
also tend to enjoy higher productivity growth. In this sense, the inclusion 
of explicit R&D targets in the Lisbon strategy was supported by empirical 
evidence. The complexity of the innovative process blurs, however, the 

relationship between R&D and productivity growth.

Setting the stage at the 2009 EIB Conference, EIB Economist 
Hubert Strauss (presenting a paper written together with 
Christian Helmers and Christian Schulte, published as Helmers et 
al. 2009 in the EIB Papers) provided some key figures on R&D 
expenditures and R&D capital stocks in Europe. 

As illustrated by Figure 1, Europe continues to spend notably less 
on R&D than either the US or Japan. The bulk of this spending gap 
is accounted for by lower R&D spending in the European business sector. 
The fact that this gap has been remarkably stable over a long period of 
time  suggests  that  it  has  structural  causes.  Despite  their  stated 
commitment to the Lisbon Strategy, European countries have made little 
progress in closing this gap in the past decade. There are also large and 
persistent differences across individual European countries. While R&D 
intensity in Sweden and Finland exceeds that of Japan, a number of 
European countries spend less than half the EU average.

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 
by the R&D capital stock. The R&D capital stock accumulates gradually as 

  Hubert Strauss

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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 alone would not have an immediate impact on its 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 1:  R&D expenditures in 2006, percent of GDP

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Government and Higher education R&D

Business R&D

Source:  Eurostat

Helmers et al. produced business sector R&D capital stock estimates for 
22 countries, including new estimates for seven additional countries 
(Figure 2). Mirroring the distribution of annual investment in R&D, Japan 
and the US have notably larger business sector R&D capital stocks than 
the EU, relative to business sector gross value added (the sectoral 
equivalent of GDP). Furthermore, the dispersion across European 
countries is much larger in terms of R&D capital stocks than for other 
factors of production. Finally, the authors find little evidence of convergence 
in these R&D capital stocks over time.

The knowledge economy in Europe 

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Figure 2: 

 Business sector R&D capital stocks in 2005, percent of 
value added

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Source:  Helmers et al. (2009)

Helmers et al. also point to evidence of complementarities between R&D 
capital and the ICT capital stock (information and communications 
technology). As suggested by the growth literature, new inventions 
resulting from investing in R&D affects the wider economy only when 
they are commercially applied on a large scale. This suggests that there 
are positive complementary effects between the stock of R&D and the 
stock of tangible fixed capital. These positive interaction effects are 
believed to be particularly strong between R&D and ICT capital. Helmers 
et al. find some evidence in support of this conjecture. In high technology 
manufacturing in Europe, industries with a high R&D intensity also tend 
to have a larger stock of ICT capital. This result is particularly striking since 
such positive correlation cannot be detected between R&D capital and 
other types of fixed capital.

The ratio of R&D capital to fixed tangible capital gives an indication of 
the “knowledge intensity” of the economy relative to its fixed capital 
stock (Figure 3). It should be stressed here that the R&D stock is of a 

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The knowledge economy in Europe

 
 
different order of magnitude than tangible fixed capital. In no country 
included in the study does the R&D stock exceed one-tenth of the fixed 
capital stock. As shown in the figure below, Japan and the US do not 
differ significantly on this measure of knowledge intensity. Even though 
Japan’s R&D intensity is higher than that of the US, so is its stock of 
tangible fixed capital, relative to the size of the economy. As a result, 
Japan’s knowledge intensity is not substantially higher than that of the 
US when scaled against the stock of fixed capital. Europe, on the other 
hand, has a knowledge-intensity relative to fixed capital that is around 
one-quarter lower than that of both the US and Japan. Again, there are 
notable differences across individual European countries. 

Figure 3. 

 R&D capital stocks as a ratio of total-economy capital 
stock, 2005 (percent)

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Source:  Helmers et al. (2009)

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The knowledge economy in Europe 

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3.    Intangible capital and economic 

growth

The traditional concept of productive fixed capital includes tangible 
asset s  such  as  non - residential  buildings  and  machiner y  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. As we have 
already suggested, 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. 

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 tends to be more difficult to measure 
than tangible fixed capital. For much of the post-war period, this 
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  of f icial  statistics  has  led  to  a  growing 
misrepresentation of the economic growth process. The reason is that 
many  advanced  economies  have  shif ted  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 

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The knowledge economy in Europe

 
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 shift towards a 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 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 

The knowledge economy in Europe 

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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 expenses);

•  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 
important result of their 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 

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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. 

Box 1:  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 neo-
classical 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= A K αL1 - 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 through an expansion 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 neo-
classical economy to keep growing on a per capita basis is by 
continuously expanding the stock of knowledge.

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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 stemmed directly from the expansion of 
labour and fixed capital3. 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 
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 
un explained TFP residual can be reduced.* 

3 

 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 equilibrium 
and under the additional assumption of perfect competition. Under these circumstances, 
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 (2009).

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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 1). As illustrated by Figure 4, productivity growth is higher in the 
presence of intangible capital. The reason is that spending on intangibles, 
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 4:  

 Contributions to US output growth per hour worked 
(percentage points)

Excluding intangibles

Including intangibles

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Labour composition 

Intangibles excl. software

Software

Tangible capital excl. IT equipment

IT equipment 

* Capital deepening

Source:  Corrado et al. (2009)

With  capital  deepening  explaining  a  larger  share  of  growth,  the 
contribution from the TFP residual becomes correspondingly smaller, 

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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 
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. 

In Europe, 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 one of the key findings by Bart van Ark 
(The Conference Board and University of Groningen) in his 
contribution to the 2009 EIB Conference (see 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 extended 
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 5 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.

  Bart van Ark

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Figure 5: 

 Intangible investment in the market sector (percent of 
GDP, 2006 or latest)

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Economic competencies

Innovative property

Computerized information

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 van Ark et al. (2009); Edquist (2009); Fukao et al. (2009); Jalava et al. (2007);  
Van Rooijen-Horsten et al. (2008)

We see here that the ratio of intangible investment to GDP varies 
markedly across countries, not least within Europe. Also the composition 
of intangible investment varies across countries. Economic competencies  
(which include investment in human capital) 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 European countries. 

Figure 6 below 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 European economies, however, investment in intangibles 
remains far below tangible investment. 

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Figure 6: 

 Intangible and tangible investment in the market sector, 
percent of GDP, 2006

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Intangible investment

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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 7, 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 
0.1-0.2 percentage points during this period. The figure 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.

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The knowledge economy in Europe

 
 
Figure 7: 

 Contribution of inputs to labour productivity growth, 
annual average in percent, 1995-2006

5

4

3

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TFP

Labour Quality

Intangibles

NonICT

ICT

Source:  van Ark et al. (2009)

To  sum  up,  this  literature  shows  that  the  exclusion  of  intangible 
investment has tended to generate a growing misrepresentation of 
growth in economies that have become increasingly specialised in 
knowledge-intensive production. A more complete accounting of 
intangibles demonstrates that the business sector in fact 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 composition of economic 
growth. Most importantly perhaps, this literature points to the large and 
indeed growing role that investment in intangibles has in economic 
growth in post-industrial societies. This is an important observation to 
consider if Europe is to succeed in catching up with US productivity 
growth in coming years.

The knowledge economy in Europe 

17           

 
4.    Can the EU close its productivity gap 

with the US?

The growth accounting literature provides an indication of how different 
forms of investment have contributed to economic growth. This literature 
has its limitations, however, especially in terms of policy conclusions. 
Growth accounting rests on simplifying assumptions regarding the rates 
of return on investment. The parameters determining the impact of 
investment on growth are imposed ex ante, rather than estimated. This 
implies that the estimated growth contribution of a factor of production 
is always strictly proportional to the growth of the factor itself, even if in 
reality there is too much of the factor to begin with, so that increasing it 
further has a minimal impact on growth.

Neo-classical growth accounting also cannot provide an explanation of 
what causes TFP to grow. TFP is simply the residual that is left after the 
growth contributions from capital and labour have been accounted for. 
Since TFP remains a substantial component in economic growth even 
after the inclusion of intangible capital, the underlying drivers of long-
term economic growth in part remain a mystery. 

4.1   Cross-country evidence from the broader 

empirical growth literature

There are several alternative methods of assessing the economic growth 
process, which are valuable complements to growth accounting in light 
of its limitations. Rather than imposing the parameter values ex ante, 
growth regressions estimate these on the basis of cross-sectional data 
and sometimes also on time series data. Cross-sectional regressions can 
be based on country-, sector-, or firm-level data. These methods allow for 
extracting the productivity effects of investment without a priori 
assumptions. They offer a way of estimating the importance for growth 
not only of investment, but also of different institutional arrangements 

18            

The knowledge economy in Europe

 
such as trade openness and the flexibility of labour and product markets. 
This literature can be used to answer questions such as: How can Europe 
close its growth gap vis-à-vis the United States?4 

One key conclusion of the cross-sectional literature is that a large portion 
of income differences across countries stems from different knowledge 
stocks (i.e. different levels of TFP), rather than differences in factor input 
levels. In order for poor countries to catch up with richer ones it is thus 
not enough to just boost fixed investment. They have to address the 
underlying impediments to convergence in TFP levels. This result is 
consistent with the observations made in the growth accounting 
literature, which also identified TFP as a key driver of growth. This is true 
for both developed and developing countries, although there are also 
important differences in the make-up of growth between these two 
groups. 

An illustration of this is provided by the experience of the EU’s New 
Member States in Central and Eastern Europe (NMS). Over the course of 
the past two decades, these countries have achieved an impressive 
convergence in income levels towards the rest of the EU, mostly on 
account of a convergence in TFP levels. For inefficient economies, which 
is a fair characterisation of the NMS at the outset of the transition process, 
large TFP-driven gains can arise from removing product and labour 

4 

 While cross-sectional data have tended to dominate this literature historically, there is also grow-
ing use of time series evidence. Panel data analysis has emerged as an alternative to pure cross-
sectional analysis, combining time series and cross-sectional data. The different approaches have 
their respective strengths and weaknesses. A lack of variability across time in many structural vari-
ables sometimes makes pure time series analysis of growth unreliable. But cross-country growth 
regressions have their own weaknesses. Some argue that the fundamental drivers of growth are 
so different across countries that single-country regressions may be the only reliable way to go. 
See Brock and Durlauf (2001) and Temple (1999) for further discussion on these issues. While it 
is important to have these caveats in mind, cross-country growth regressions have nevertheless 
been used extensively and often productively to sort out the relative importance of different ele-
ments as fundamental drivers of long-term economic growth. One advantage of this approach is 
also that it can assess the impact of a given institution or policy regardless of whether it affects 
growth through capital deepening or TFP. For policy makers, what matters is that a certain policy 
or institutional framework has a positive impact on growth. Exactly through what channels it oper-
ates is often of secondary importance.

The knowledge economy in Europe 

19           

market  inef ficiencies,  from  liberalising  foreign  trade  and  from 
macroeconomic stabilisation. High TFP growth in transition economies 
and other fast-converging middle income countries have thus not 
stemmed primarily from investing in R&D, but from the adoption of best 
practice  and  technologies  already  developed  elsewhere.  While 
improvements in the quantity and quality of tangible fixed capital have 
played a large role as well, more important has been the massive 
improvement in the efficiency with which factor inputs are being used.

For advanced economies, there is less scope of achieving high growth 
through  efficiency  gains  and  the  adoption  of  best  practice  and 
knowledge from abroad. Advanced countries are more dependent on 
indigenous R&D and knowledge creation, although they too benefit from 
cross-border knowledge spillovers. What developing and developed 
countries all have in common is that the ability to benefit from knowledge 
spillovers is highly dependent on domestic conditions and institutions. 
Specifically, empirical evidence shows that countries are on average 
more receptive to foreign knowledge spillovers if they: are more open to 
foreign trade (Coe and Helpman 1995); invest in R&D and human capital 
(Cohen  and  Levinthal  1989;  Griffith  et  al.  2004;  Guellec  and  Van 
Pottelsberghe 2004; Khan and Luintel 2006) and; have more flexible 
product markets (Parente and Prescott 2000). This literature also shows 
that the importance of investing in R&D tends to increase as countries 
close in on the global technological frontier (Benhabib and Spiegel 1994; 
Engelbrecht 1997, 2000).

20            

The knowledge economy in Europe

 
4.2   What should Europe do to close its 

productivity gap vis-à-vis the US?

Simulations offer an instructive alternative to growth accounting and 
growth regressions in their ability to demonstrate how changes 
in different key variables may affect the final outcome. An 
example of this was provided at the 2009 EIB Conference by 
Werner Röger (European Commission). His papers (written 
together with Kieran Mc Morrow and available in the 2009 volume 
of the EIB Papers as Mc Morrow and Röger 2009) draws on empirical 
estimates for the rate of return on R&D to calibrate their growth 
model, which is an extension of the QUEST III model employed by 
the European Commission for quantitative policy analysis.

Opting for a reasonable mid-range approximation consistent with the 
empirical literature, Mc Morrow and Röger assume a rate of return of 30 
percent, which they then plug into their calibrated growth model, which 
is then used to analyse how the productivity gap between the EU and 
the US could be closed. In this semi-endogenous model, research output 
is a function of both current research inputs in the form of high skilled 
labour and the knowledge capital accumulated in the past. The model 
accounts for the interaction between several different key variables and 
accounts specifically for transatlantic differences in several innovation 
parameters, including fixed entry costs for startups, the share of skilled 
labour, and the financial market risk premium. The model thus allows the 
authors to assess the macroeconomic impact of several concrete policy 
measures, either in isolation or in conjunction with each other.

On the basis of this exercise, Mc Morrow and Röger conclude that 
stimulating R&D investment directly through subsidies is not nearly 
enough to close the EU-US productivity gap, due to crowding out effects 

  Werner Röger

The knowledge economy in Europe 

21           

and decreasing returns in the production of knowledge. A key finding is 
that additional ‘framework policies’ are needed for Europe to reach its 
productivity goals. More effective would be to combine R&D subsidies 
with increases in the supply of scientists and engineers, while substantially 
lowering entry barriers for start-ups. If all these variables were on par 
with the US, this would reduce the EU-US productivity gap by around 
half. Additional measures to further narrow the transatlantic productivity 
gap would include improvements in the quality of higher education and 
liberalisation of Europe’s non-manufacturing sectors, such as services 
and agriculture.

5.   The microeconomics of R&D
Most  of  the  literature  discussed  up  to  this  point  has  adopted  a 
macroeconomic perspective, shedding light on the growth impact of 
R&D and the broad policy frameworks needed to foster R&D and 
innovation. In order to design effective public support mechanisms it is 
also important, however, to understand the motivations of individual 
firms to invest in R&D and to innovate. This section zooms in on the 
microeconomics of innovation and specific policies and institutions that 
aim to boost business sector investment in R&D. 

5.1   Market failure and the case for public support 

for R&D

Before going into the specifics of these support mechanisms, it is 
important to recognise that public support of R&D is motivated by the 
presence of market failure. Specifically, in the absence of public support, 
there is good reason to expect that the business sector underinvests in 
R&D from the perspective of what is socially optimal. This perception 
draws support from both theoretical and empirical research. 

The theoretical argument for why there may be collective underinvestment 
in R&D is linked to the inherent nature of knowledge, which is the main 

22            

The knowledge economy in Europe

 
output of R&D. As we argued in section 3, knowledge can be viewed as a 
form of productive capital, similar to machinery and equipment. Investing 
in the creation of new knowledge is thus motivated by its ability to 
increase  future  output  and  income.  But  knowledge  differs  from 
conventional fixed capital in two important respects. The first is that it is 
non-rival, which means that its use by one firm in no way diminishes the 
ability of other firms to use the same knowledge simultaneously. Non-
rivalness gives rise to positive externalities, yielding additional benefits 
to  society  beyond  those  accruing  to  the  investing  firm.  Second, 
knowledge is also often non-excludable. The firm investing in the 
creation of new knowledge may not be able to prevent others from using 
it, nor can it be sure to get compensated by the firms that use this 
knowledge. 

To the extent that knowledge is both non-rival and non-excludable, it 
has the properties of a pure public good. Private firms have no incentive 
to invest in a pure public good since doing so gives them no advantage 
over free-riding competitors. Knowledge that has these properties may 
have to be financed by the government if it is to be created at all. This is 
indeed the case with a lot of basic scientific research conducted in 
universities.

Not all knowledge has the properties of a public good, however, and the 
private business sector does invest substantial amounts in R&D. The 
reason is that quite a lot of knowledge is at least partially excludable. It 
may be difficult or costly for other firms to acquire second-hand 
knowledge, for instance because of secrecy or costly learning. Some 
knowledge is tacit, which means that it is embedded in the minds of 
individual researchers or in the organisational structure of the investing 
firm. But even tacit knowledge can migrate when a researcher moves to 
a competing firm, and competitors can learn about new innovative 
products through reverse engineering and trade links. Hence, even 
though the investing firm may be able to appropriate at least some of 
the  profits  from  its  inventions,  some  unremunerated  knowledge 

The knowledge economy in Europe 

23           

spillovers are bound to occur. Such knowledge spillovers insert a wedge 
between the private and social rates of return, as the investing firm does 
not take into consideration the benefits accruing to others when making 
its investment decisions. This in turn may cause the level of investment in 
R&D to be below what would be socially optimal. Romer (1986) provides 
a theoretical illustration of how this may occur.

As discussed by Mc Morrow and Röger (2009), empirical evidence points 
in a similar direction. For instance, the rate of return of investing in R&D 
tends to be higher in country level studies than in firm level studies, 
which is consistent with the inability of firms to appropriate all the returns 
from their investments.

The theoretical and empirical case for underinvestment in R&D has 
spurred many governments to provide public support for R&D through 
several channels. As discussed in three different presentations at the 
2009 EIB Conference, policymakers can for instance use a tax credit to 
lower the cost of R&D and thus lift the private rate of return towards a 
level that is optimal from society’s point of view. Alternatively, they can 
encourage R&D cooperation between firms in the same area of research, 
thus allowing for the internalisation of knowledge spillovers, again 
bringing the private and social rates of return closer to each other. 
Alternatively, governments can resort to property rights protection to 
compensate the investing firms for the use of knowledge by others.

Since knowledge spillovers have a positive impact on the wider economy, 
it would be counterproductive to prevent them outright. Doing so could 
for instance trigger several simultaneous research efforts aiming at 
creating the same knowledge. Given the non-rivalness of knowledge, 
this would be wasteful. Policies that allow investors to appropriate more 
of the rents from their investment therefore tend to be socially preferable. 
These  issues  are  complex,  however,  and  all  policy  options  have 
advantages and disadvantages. The three papers presented at the 2009 
EIB Conference should only be seen as a sample of this debate.

24            

The knowledge economy in Europe

 
5.2   Public support for inter-firm and science-

industry cooperation in R&D 

Collusion  between  competing  firms  is  generally  prohibited  by 
competition law when it comes to the products and services they provide 
to consumers. If it were not, small groups of market leading firms in many 
industries would soon team up to form a cartel. Yet, in R&D there is a 
strong case for permitting cooperation between firms, even when they 
are competitors in their final products. In his contribution to the 
2009 EIB Conference (published in the 2009 volume of the EIB 
Papers), Dirk Czarnitzki (Catholic University of Leuven and 
Centre for European Economic Research, Mannheim) shows how 
cooperative R&D agreements can help foster more investment in 
R&D in the presence of knowledge spillovers. Cooperation in R&D 
allows the investing firms to internalise such spillovers, while also 
exploiting the economies of scale and scope of R&D. A pooling of 
risk and fixed costs can also broaden the research horizon of 
cooperating firms. This is particularly true for research that is 
closer to basic science, where the rents are typically harder to appropriate. 
On the basis of data from Belgium and Germany, Czarnitzki finds that 
private firms collaborating with academia invest more in R&D than firms 
collaborating with other firms – even in the absence of subsidies – and 
that subsidies of such science-industry collaborations would boost R&D 
investment  even  further.  However,  Czarnitzki  also  points  to  the 
opportunity cost of these vertical collaborations and the subsidies that 
are used to foster them. To the extent that government funding is 
reallocated  from  basic  research  to  subsidising  science-industry 
collaborations, this could steer academic research in a more applied 
direction, thus undermining the complementarity between science and 
industry that made such collaboration valuable in the first place.

  Dirk Czarnitzki

The knowledge economy in Europe 

25           

5.3   Public support for R&D by means of a tax 

credit

The most common policy tool used to compensate for underinvestment 
in R&D is a public subsidy, typically in the form of a tax credit that allows 
a company to deduct part of its R&D expenditure from its tax bill. At the 
2009 EIB Conference, Jacques Mairesse (CREST, ENSAE, Paris; NBER), 
presented a paper co-authored with Damien Ientile (published in the 
2009 EIB Papers as Ientile and Mairesse 2009) reviewing the 
effectiveness of such R&D tax credits. The paper surveys a number 
of studies estimating the direct effects of the tax credit on R&D 
investment. These suggest mixed effects of such policies. While 
business R&D investment increases in all cases reviewed, one euro 
of taxpayer money sometimes leads to less than one euro of 
additional R&D. Specifically, there is notable variability across 
countries. The survey article also shows that the R&D tax credit 
increases the likelihood of firms starting own R&D activities and 
that it is conducive to higher innovation output such as the 
number of new products or their share in a beneficiary firm’s total 
sales. They point out that the best evaluation of the R&D tax credit would 
take into account the additional GDP generated by the additional R&D as 
well as all direct and opportunity costs of the measure.

Jacques Mairesse

26            

The knowledge economy in Europe

 
 
5.4   Intellectual property rights and patent 

applications

The third type of policy support for R&D is through intellectual property 
rights. Patents have for a long time been used to strengthen the ability of 
innovative firms to appropriate the rents from their R&D investments. 
Since patents aim at the protection of existing scientific discoveries, they 
can be used as a proxy for the output of R&D.

Drawing on a paper co-written with Jérôme Danguy and Gaetan 
de Rassenfosse (published in the 2009 EIB Papers as Danguy et al. 
2009), Bruno van Pottelsberghe (Free University of Brussels) 
presented at the 2009 EIB Conference an investigation of the 
relationship between R&D expenditures and patent applications at 
the industry level. This relationship reflects both a productivity 
channel – i.e. R&D leads to inventions – and a ‘propensity-to-patent’ 
channel, whereby firms in different countries and industries differ 
in their eagerness to patent-protect their inventions. Firms seek 
patent protection either as a means (among others) to appropriate 
income from their intellectual property (IP) or to make life difficult for 
competitors (‘strategic propensity’). The study finds that more R&D does 
lead to more patents, but this relationship is not very strong. This suggests 
that the propensity to file for patent protection, as expressed by the 
stringency of IP rights protection and exposure to international markets, 
matters more than the productivity of R&D as the key determinant of 
patenting. Countries with strong IP rights rely more on the patent system, 
as do industries with high international exposure. Yet, a significant part of 
the dramatic increase in patent filings worldwide remains unaccounted for. 
The authors disentangle which countries and industries contribute most to 
this surge. They also demonstrate that the ‘global patent warming’ reflects 
firms’ growing desire to extend national patents to the world market rather 
than an increase in national patent filings.

  Bruno van Pottelsberghe

The knowledge economy in Europe 

27           

6.   Financing innovation
In addition to knowledge spillovers, public intervention to support R&D 
may also be justified by market failure in finance. At the 2009 EIB 
Conference, Bronwyn Hall (University of California at Berkeley and 
University of Maastricht) discussed a paper (subsequently published in 
the 2009 volume of the EIB Papers) reviewing the main theories 
and empirical evidence regarding the financing of innovation. Key 
questions addressed are whether new and/or innovative firms are 
fundamentally different from established firms and whether they 
therefore require a different form of financing. She points to a 
large literature suggesting that this is indeed the case. First, 
intangible assets typically account for a larger portion of total 
assets in innovative firms. Such assets are less easily used as 
collateral when seeking external finance. Second, in the case of 
young innovative firms, these tend to be inherently riskier and 
have less of a track record. The particularly severe asymmetric 
information and agency problems that characterise such firms tend to 
make external finance costlier and more difficult to obtain. By addressing 
the information and incentive issues directly through better monitoring 
and risk sharing, equity financing in general – and venture capital in 
particular – tends to be the preferred form of external financing for such firms.

The market for venture capital (VC) developed later in Europe than in the 
US. As shown in Figure 8, VC investment in the EU stands at just over 
 0.1 percent of GDP, which is around two-thirds the US level. There are 
also substantial differences across EU countries. In the three largest euro 
area economies the level of VC investment is low. In contrast, in the UK, 
Sweden and Denmark it exceeds that of the US, relative to the size of 
their economies. The figure also illustrates how a large portion of VC 
funding is aimed at the expansion phase of new ventures rather than 
early stage financing. 

  Bronwyn Hall

28            

The knowledge economy in Europe

 
Figure 8:  Venture capital investment, percent of GDP, 2005 or latest

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0

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Source:  OECD (2007)

Expansion

Early Stages

At the 2009 EIB Conference, Laura Bottazzi (Bologna University) 
reviewed the role of venture capital in financing new dynamic 
firms in Europe. On the basis of her own research, Bottazzi finds 
that venture capital in Europe is not associated with particularly 
dynamic or successful companies, whether one looks at sales 
growth or employment. This stands in contrast to US experience, 
where venture capital has tended to accompany the formation 
and  grow th  of  dynamic  companies.  A  key  fac tor  in  the 
effectiveness of venture capital appears to be its own human 
capital. Human capital affects the level of activism of venture capitalists 
and thus the value added that they bring to the firms they invest in. This 
points to the importance of postgraduate education for the level of 
professionalism in the European venture capital industry. In the last 
decade, however, Europe has experienced new entrants in the industry, 
which seem to operate in a manner closer to the US investment style.

  Laura Bottazzi

The knowledge economy in Europe 

29           

 
It is only through commercial application that most technological 
discoveries can affect the productivity of the wider economy. To the 
extent that scientific research is conducted in universities and specialised 
research institutions, successful commercialisation of technological 
discoveries requires linking scientific research to the wider business 
sector. This is what is commonly known as technology transfer. In 
his presentation to the 2009 EIB Conference, Jacques Darcy 
(European Investment Fund, presenting a paper written together 
with Helmut Krämer-Eis, Dominique Guellec and Olivier Debande) 
provided a mapping of the specific financial constraints, risks and 
asymmetric  information  problems  that  may  impede  such 
technology transfer. The scaling up of scientific research for 
commercial application requires large amounts of capital typically 
not available in the research community itself. But similar to 
venture capital, the financing of technology transfer entails more 
than just the provision of funds. If technology transfer is to take off in 
Europe, there is a need to tailor both intellectual property rights and 
financial instruments in such a way that the incentives, risks and rewards 
are optimally aligned between universities, inventors, entrepreneurs and 
investors.

Jacques Darcy

The commercialisation of new technological discoveries in part 
suffers from a shortage of financing because intangible capital is 
more difficult to use as collateral. These problems would be 
alleviated with the development of a better market for technology. 
If patented knowledge could be bought and sold in a marketplace, 
then it would also become more attractive as collateral when 
seeking  external  finance.  Dietmar  Harhoff  (Institute  for 
I n n o v a t i o n   R e s e a r c h ,   Te c h n o l o g y   M a n a g e m e n t   a n d 
Entrepreneurship, Ludwig-Maximilians University Munich) focused on 
this issue in his presentation at the 2009 EIB Conference. A key condition 

30            

The knowledge economy in Europe

 
 
for patents to serve not only as intellectual property protection, but also 
as collateral, is that they have a residual market value outside the 
investing firm. European experience in this area has so far been mixed. 
Some intermediaries have attempted to provide external finance to 
innovative firms based on their patent portfolios. Patents have been 
used  either  as  collateral,  or  as  assets  in  patent  funds  seeking  to 
commercialize the patent rights. Patent auctions are indicative of a 
nascent market for patented technology. Supported by changes in 
valuation techniques and accounting regulation, it seems likely that 
patent rights will increasingly be used as collateral in debt finance. The 
development of a liquid market for technology and the use of patents as 
collateral  are  complementary,  but  they  depend  crucially  on  an 
appropriate design of patent systems. Uncertain and questionable patent 
rights tend to hamper the development of markets for technology and 
the use of patents as collateral, which in turn drives up the cost of 
innovation finance.

  Dietmar Harhoff

In  his  concluding  comments  to  the  2009  EIB  Conference, 
Plutarchos Sakellaris (Vice President of the EIB) reminded the 
audience that a proper understanding of knowledge creation and 
innovation is paramount to ensure high standards of living in the 
long run. Large players like the EU need to take the lead in 
addressing the policy challenges and the EIB Group has a role to 
play in alleviating financing constraints.

  Plutarchos Sakellaris (Vice President of the EIB)

The knowledge economy in Europe 

31           

7.   Concluding remarks
The empirical growth literature has confirmed that growth of the 
knowledge stock accounts for a large portion of growth in output per 
worker. Treating some of the knowledge stock as intangible capital that 
is proprietary to the investing firms does not fundamentally change this 
conclusion, but it makes it easier to account for the relative importance 
of the different types of tangible and intangible capital in economic 
growth. These expanded growth accounting efforts have shown that 
investment in R&D and other intangible capital has over time become 
increasingly important drivers of growth. This is particularly the case in 
countries that have made the most complete transition from traditional 
manufacturing to knowledge-based economic activity.

Given the large role that knowledge plays in economic growth, it is 
crucial for policymakers to obtain a better understanding of the complex 
mechanisms that underpin knowledge creation and business innovation. 
European policymakers have also recognised that sustained growth is 
increasingly dependent on innovation as the economy has converged 
towards the global technological frontier. But efforts to boost Europe’s 
R&D have so far met with limited success and a substantial investment 
gap remains vis-à-vis Japan and the US. This is also mirrored by a 
persistent transatlantic productivity gap. 

Even though the economic literature has acknowledged that R&D 
subsidies are justified to compensate for knowledge externalities, such 
incentives are likely of second order importance for the innovative 
business sector. It is becoming increasingly clear that the pace of 
innovation and the rate of productivity growth in Europe are unlikely to 
budge unless policymakers continue to improve the wider economic 
framework that create the incentives for firms to innovate. These 
conditions affect not only the propensity of firms to invest in R&D, but 
also their willingness and ability to apply this new knowledge in the form 
of product and process innovation. Innovation generates productivity 

32            

The knowledge economy in Europe

 
gains primarily by allowing for a more efficient organisation of the 
economy, often combined with a reallocation of resources towards new 
industries with higher growth prospects. Crucial elements in this process 
are competition and product and labour market flexibility, the exit and 
entry of firms, and the provision of financial and other means allowing 
new innovative companies to expand quickly when successful. There is 
also a strong case for improving European patent laws and policies and 
for further developing markets for patented technology. This would both 
encourage firms to invest in intangible capital and make it easier for them 
to then use these assets as collateral when seeking finance.

The knowledge economy in Europe 

33           

 References
Benhabib, J. and Spiegel, M.M. (1994). “The role of human capital in 
economic development. Evidence from aggregate cross-country data”. 
Journal of Monetary Economics (34), pp. 143–173.

Bottazzi, L. (2009). “The role of venture capital in alleviating financial 
constraints of innovative firms”. EIB Papers, (14:2), pp. 30-53.

Brock, W.A. and Durlauf, S.N. (2001). “Growth empirics and reality”. World 
Bank Economic Review, (15:2), pp. 229-272.

Coe, D. and Helpman, E. (1995). “International R&D spillovers”. European 
Economic Review, (39), pp. 859–887.

Cohen, W. and Levinthal, D. (1989). “Innovation and learning: The two 
faces of R&D”. Economic Journal, (99), pp. 569–596. 

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, USA.

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.

Czarnitzki, D. (2009). “The virtue of industry-science collaborations”. EIB 
Papers, (14:1), pp. 120-143.

Danguy, J., de Rassenfosse, G., and van Pottelsberghe de la Potterie, B. 
(2009). “The R&D-patent relationship: An industry perspective”. EIB 
Papers, (14:1), pp. 170-195.

Darcy, J., Krämer-Eis, H., Guellec, D. and Debande, O. (2009). “Financing 
technology transfer”. EIB Papers, (14:2), pp. 54-73.

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Edquist, H. (2009). “How much does Sweden invest in intangible assets?” 
Research Institute of Industrial Economics Working Paper No. 785.

Engelbrecht. H.J. (1997). “International R&D spillovers, human capital and 
productivity in OECD economies: an empirical investigation”. European 
Economic Review, (41), pp. 1479–1488.

Engelbrecht. H.J. (2000). “Human capital and international knowledge 
spillovers in TFP growth of a sample of developing countries: An exploration 
of alternative approaches”. Applied Economics, (34), pp. 831–841.

Fukao, K., Hamagata, S., Miyagawa, T. and Tonogi, K. (2009). “Intangible 
investment in Japan: Measurement and contribution to economic 
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.

Griffith, R., Redding, S. and van Reenen, J. (2004). ”Mapping the two faces 
of R&D: productivity growth in a panel of OECD industries”. Review of 
Economics and Statistics, (86:4), pp.883-895..

Guellec, D. and van Pottelsberghe de la Potterie, B. (2004). “From R&D to 
productivity growth: do the institutional settings and the source of funds of 
R&D matter?”. Oxford Bulletin of Economics and Statistics, (66:3), pp. 353-378.

Hall, B.H. (2009). “The financing of innovative firms”. EIB Papers, (14:2), pp. 8-29.

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.

Harhoff, D. (2009). “The role of patents and licenses in securing external 
finance for innovation”. EIB Papers, (14:2), pp. 74-97.

The knowledge economy in Europe 

35           

Helmers, C., Schulte, C., and Strauss, H. (2009). “R&D expenditure and 
capital in Europe”. EIB Papers, (14:1), pp. 36-61.

Ientile, D. and Mairesse, J. (2009). “A policy to boost R&D: Does the R&D 
tax credit work?”. EIB Papers, (14:1), pp. 144-169.

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.

Khan, M. and Luintel, K.B. (2006). “Sources of knowledge and productivity: 
how robust is the relationship?”. OECD Science, Technology and Industry 
Working Papers 2006/6, OECD, Paris, France.

Mc Morrow, K., and Röger, W. (2009). “R&D capital and economic growth: 
The empirical evidence”. EIB Papers, (14:1), pp. 94-119.

OECD (2007). Science, Technology and Industry Scoreboard 2007. OECD, 
Paris, France.

Parente, S.L. and Prescott, E.C. (2000). Barriers to Riches, MIT Press: Cambridge, 
Massachusetts.

Romer, P. (1986). “Increasing returns and long-run growth”. Journal of 
Political Economy, (94:5), pp. 1002–1037.

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.

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Temple, J. (1999) “The new growth evidence”. Journal of Economic 
Literature, (37), pp. 112–156.

Uppenberg, K. (2009) “Innovation and economic growth”. EIB Papers, 
(14:1), pp. 10-35.

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.

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.

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 EIB and the financing of innovation in 
Europe*

By EIB Vice President Eva Srejber

As the long term financing arm of the European Union, the 
European Investment Bank is committed to support innovative 
projects undertaken by the public and private sectors in Europe.

Since the European Council in Lisbon in 2000, the EIB has had a 
specific lending objective for innovation, or - as it was decided to 
call it in 2008 - the Knowledge Economy. This covers not only 
research and development but also investments in information 
and communication technology (ICT) and support for higher education 
institutions, all of which are important and interactive ingredients in 
helping improve European competitiveness.

Our aim is to support all areas of the “Knowledge Triangle”: innovation, 
research and education. All three components are important in improving 
the productivity of the EU. Research and innovation drive the knowledge 
frontier and create applications and enabling infrastructures, while 
education enhances the skills to innovate. Also, enabling certain types of 
education, such as full-day schools, where school meals are served also 
increases labour productivity as parents can spend more time at work. 

Between 2000 and 2009, out of total lending to support the Knowledge 
Economy of 87 billion euro, R&D projects accounted for some 46 bn, 
more or less evenly split between the business sector and public-sector 
research facilities, universities, and science and technology parks.  
Examples include the financing of the Large Hadron Collider at CERN in 

*  An earlier version of his article first appeared in “Innovation Europe” in October 2009

  Eva Srejber (Vice President of the EIB)

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The knowledge economy in Europe

 
Geneva and the laser synchrotron in Trieste. The Bank follows closely 
projects  identified  by  the  European  Strategy  Forum  on  Research 
Infrastructures, such as the planned European Spallation Source in Lund.

18 bn euros – or one fifth of total signatures over the 10-year period – 
were allocated to education and training, which mostly meant education 
infrastructure. In 2008, for example, EIB lent 75 million euro for new 
biomedical research and training facilities at Trinity College in Dublin. 

20 bn euros went to projects in ICT, including advanced telecommunications 
networks and state of the art ICT production facilities such as semiconductor 
production plants.  Around two-thirds of this was to private sector 
projects.  One of the chief aims of this lending has been to facilitate a 
modern and interconnected ICT infrastructure so as to expand the 
environment necessary for developing further the knowledge-based 
economy in Europe, including for example widespread availability of 
fixed and mobile broadband networks in order to improve ICT-based 
productivity.  

Demand for EIB loans was notably higher in 2009 as the financial crisis 
has made it harder for companies to obtain other sources of finance. 
Responding to these circumstances, the Bank increased its total lending 
under the knowledge economy objective by 46 percent in 2009 relative 
to the year before. 

The knowledge economy in Europe 

39           

EIB lending under the Knowledge Economy objective

Cumulative signatures knowledge
economy 2000-2009 (€bn) 

- Total 
- R&D 
- Education, training 
- Innovation/ICT 
- Global Loans etc. 

86.8
45.9
18.0
20.5
2.4

20
18
16
14
12
10
8
6
4
2
0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Global loans or projects not classified

R&D

Innovation / ICT

Education, training

The EIB raises finance by issuing bonds on capital markets. Thanks to its 
owners – the EU’s 27 member states – and its own solid capital base it 
can raise this money on favourable terms. It aims to pass on this 
financial benefit to project promoters, its customers, either directly, in 
the case of larger loans, or indirectly via partner banks and financial 
intermediaries. 

The Bank offers a wide range of financial instruments to accommodate 
everything from small start-up companies to large investment grade 
companies and the public sector. One of EIB’s instruments that support 
the Knowledge Economy is a  special  window for more risky RDI loans 
created together with the European Commission, where one billion euro 
from the 7th Research Framework Program of the EU together with one 
billion euro from the EIB is the capital cushion for possible losses on these 
loans. EIB and the Commission are sharing the risk of losses. Using this 
one billion euro from the EU budget as a buffer together with a one 
billion euro buffer from EIB will enable loans of several billons over the 
years for the benefit of RDI . 

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The knowledge economy in Europe

 
Since the start of operations in June 2007, cumulative signatures under 
this risk sharing facility (named RSFF) amount to 4.5 billion euro.

Part of the indirect lending of the EIB is directed at SMEs and Mid-Caps, 
acknowledging their importance as early adopters of more innovative 
processes as well as innovators. Total lending under this heading stood 
at 2.4 bn euro for the 2005-2009 period. 

In early start-up operations in the field of Innovation, the high risk profile 
of the companies may demand an equity-type of financing rather than a 
loan. The EIB can accommodate this through the European Investment 
Fund (EIF), whose shareholders are the EIB (with 62% of the capital), the 
European Commission (29%) and several European banks (9%). The EIF 
operates in support of SMEs, not through direct investments, but through 
equity investments in venture capital and growth funds that support in 
particular early-stage and technology-oriented SMEs.

For venture capital investments, EIF uses its own resources, as well as 
resources from the European Investment Bank, from the European 
Commission’s Competitiveness and Innovation Programme (CIP), from 
Member States and regions through the Joint European Resources for 
Micro to Medium Enterprises (JEREMIE) initiative and other third parties.

EIF’s total net equity investment commitments amounted to EUR 3.9bn 
by the end of 2009, invested in over 300 funds. EIF’s portfolio still remains 
largely focused on the early stage sector with over 45% of its portfolio in 
seed and start-up funds, although growth and mezzanine funds are 
being included to balance the portfolio by offsetting the higher risks 
inherent in early stage investing. Within the early stage technology 
portfolio, information and communications technologies and life 
sciences figure strongly.

The EIB’s support to the Knowledge Economy covers all areas in the 
Knowledge Triangle; Innovation, Research and Education. Developments 
in these areas lead to subsequent productivity gains and market-related 
competitiveness, growth and jobs. 

The knowledge economy in Europe 

41           

The EU has made progress in certain areas of the Knowledge Economy in 
the last years - the EU is world-leading in terms of clusters (automotive 
and telecommunications) – and the EIB aims to help the EU reinforce its 
leadership in this area. The Bank recognises that R&D and innovation are 
conducted in very different types of organisations and has adapted its 
financial instruments accordingly. Our aim is to offer continued support 
and attractive financing solutions for all parts of the Knowledge Economy 
enabling the narrowing of the current R&D gap that Europe has vis-à-vis 
the United States and Japan. 

About the author: 

Eva Srejber is EIB vice president responsible for knowledge economy 
lending.

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The knowledge economy in Europe

 
EIB Papers 1997 – 2009

2009  

 Volume 14, Number 2, R&D and the financing of innovation in Europe. 
Financing innovative firms 

2009  

 Volume 14, Number 1, R&D and the financing of innovation in Europe. 
Stimulating R&D, innovation and growth

2008  

 Volume 13, Number 2, Infrastructure investment, growth and cohesion.  
The economics of regional transport investment

2008  

 Volume 13, Number 1, Infrastructure investment, growth and cohesion.  
Public investment: Composition, growth effects and fiscal constraints

2007  

2007  

2006  

2006  

2005  

2005  

 Volume 12, Number 2, An efficient, sustainable and secure supply of 
energy for Europe. Meeting the Challenge

 Volume 12, Number 1, An efficient, sustainable and secure supply of 
energy for Europe. Global and European policy perspectives

 Volume 11, Number 2, An industrial policy for Europe? From concepts to 
action

 Volume 11, Number 1, An industrial policy for Europe? Context and 
concepts

 Volume 10, Number 2, Innovative financing of infrastructure - the role of 
public-private partnerships. Lessons from the early movers

 Volume 10, Number 1, Innovative financing of infrastructure - the role 
of public-private partnerships. Infrastructure, economic growth, and the 
economics of PPPs

2004  

 Volume 9, Number 2, The internationalisation of production in Europe. 
Case studies of foreign direct investment in old and new EU members

2004  

 Volume 9, Number 1, The internationalisation of production in Europe. 
Causes and effects of foreign direct investment and non-equity forms  
of international production

2003  

 Volume 8, Number 2, Europe’s changing financial landscape.  
The financing of small and medium-sized enterprises

2003  

 Volume 8, Number 1, Europe’s changing financial landscape. Recent 
developments and prospects

2002 

 Volume 7, Number 2, The financial integration of an enlarged EU. 
Macroeconomic interlinkages

2002  

 Volume 7, Number 1, The financial integration of an enlarged EU.  
Banking and capital markets

The knowledge economy in Europe 

43           

2001 

 Volume 6, Number 2, The 2001 EIB Prize

2001 

2000 

 Volume 6, Number 1, European economic growth. The impact of new 
technologies

 Volume 5, Number 2, Regional convergence in Europe. Theory and 
empirical evidence

2000  

 Volume 5, Number 1, Regional development in Europe. An assessment of 
policy strategies

1999  

 Volume 4, Number 2, The 1999 EIB Prize

1999  

 Volume 4, Number 1, European banking after EMU

1998  

 Volume 3, Number 2, International financial institutions in the 21st century

1998  

 Volume 3, Number 1, Employment in Europe

1997  

 Volume 2, Number 2, The 1997 EIB Prize

1997  

 Volume 2, Number 1, Banking in an uncertain world

1996  

 Volume 1, Number 1, Special Issue on EMU

44            

The knowledge economy in Europe

 
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