Innovation Policy Instruments
ABSTRACT The Lisbon Agenda that was launched in 2000, and had a set time-period of ten years. The purpose of the Lisbon Agenda was to make the EU the most competitive, knowledge-based economy in the world, and at the same time preserving, or even improving social cohesion and maintain environmental sustainability. The Lisbon Agenda had a large number of goals, in both quantified and qualified measures, in different areas. The main instrument that was put forward was the open method of co-ordination (OMC) that includes indicators, benchmarking, peer pressure, and best practise demonstrations. The forthcoming Lisbon Agenda will certainly need new approaches, and new instruments. One of the areas of instruments that can be further explored is innovation policies where the use of R&D and human capital is enhanced. Human capital is a natural part of a knowledge-based economy, and has positive impacts on growth, and jobs in the economy. Innovation policy instruments are diversified and are integrated in many areas of an economy and on many levels, which make them ideal for the next Lisbon Agenda. The instruments can have a general or specific characteristics and some span over the two characteristics.
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ABSTRACT: This paper focuses on the effect public subsidies for innovation have on the exit of firms. Utilizing Finnish firm level data I employ a kernel matching approach to eliminate the selection bias of public funding and estimate the counterfactual. As a robustness check a treatment model is estimated. Public funding for innovation exhibits a significant effect reducing the probability of exit. Distinguishing between exit by merger and exit by closure shows that public funding has a significant effect on the former. No significant effect on the latter can be found. KeywordsPublic funding–Innovation–Exit of firmsJournal of Evolutionary Economics 08/2010; 21(3):519-543. · 1.00 Impact Factor
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ABSTRACT: Innovation policies play an important role throughout the development process of emerging industries in China. Existing policy and industry studies view the emergence process as a black-box, and fail to understand the impacts of policy to the process along which it varies. This paper aims to develop a multi-dimensional roadmapping tool to better analyse the dynamics between policy and industrial growth for new industries in China. Through reviewing the emergence process of Chinese wind turbine industry, this paper elaborates how policy and other factors influence the emergence of this industry along this path. Further, this paper generalises some Chinese specifics for the policy-industry dynamics. As a practical output, this study proposes a roadmapping framework that generalises some patterns of policy-industry interactions for the emergence process of new industries in China. This paper will be of interest to policy makers, strategists, investors and industrial experts.International Journal of Environment and Sustainable Development 01/2013; 12(1):3 - 21.
Electronic Working Paper Series
INNOVATION POLICY INSTRUMENTS
Börje Johansson, Charlie Karlsson and Mikaela Backman
Innovation Policy Instruments
Börje Johansson, Charlie Karlsson and Mikaela Backman*
Jönköping International Business School and the Royal Institute of Technology
P.O. Box 1026, SE-551 11 Jönköping, Sweden
The Lisbon Agenda that was launched in 2000, and had a set time-period of ten years. The
purpose of the Lisbon Agenda was to make the EU the most competitive, knowledge-based
economy in the world, and at the same time preserving, or even improving social cohesion and
maintain environmental sustainability. The Lisbon Agenda had a large number of goals, in both
quantified and qualified measures, in different areas. The main instrument that was put forward
was the open method of co-ordination (OMC) that includes indicators, benchmarking, peer
pressure, and best practise demonstrations.
The forthcoming Lisbon Agenda will certainly need new approaches, and new instruments. One
of the areas of instruments that can be further explored is innovation policies where the use of
R&D and human capital is enhanced. Human capital is a natural part of a knowledge-based
economy, and has positive impacts on growth, and jobs in the economy. Innovation policy
instruments are diversified and are integrated in many areas of an economy and on many levels,
which make them ideal for the next Lisbon Agenda. The instruments can have a general or
specific characteristics and some span over the two characteristics.
Keywords: Lisbon Agenda, innovation policy instruments, beyond Lisbon 2010
Jel-codes: F 00, N 24,
* Corresponding author, Mikaela.firstname.lastname@example.org, +46-36-101746
The European Union (EU) is lagging behind the US, and other major regions of the world in
many areas. The most important aspect is possibly the progress of becoming a knowledge
economy which at the moment has been too slow in EU. Even though the EU is making progress
there are still a lot of challenges ahead, in order to catch-up with the US and parts of Asia. The
main picture is a lack of investments in R&D, internet penetration, and so forth.
The Lisbon Agenda that was launched in 2000 was a response to this development, and had a set
time-period of ten years. The purpose of the Lisbon Agenda was to make the EU the most
competitive, knowledge-based economy in the world, and at the same time preserving, or even
improving social cohesion and maintain environmental sustainability. The Lisbon Agenda had a
large number of goals, in both quantified and qualified measures, in different areas. The main
instrument that was put forward was the open method of co-ordination (OMC) that includes
indicators, benchmarking, peer pressure, and best practise demonstrations.
In 2005, the results that so far had been reached were evaluated in mid-term reviews. The
findings were not positive. The EU was still lagging behind other major regions, and in some
areas had the gap even widened. Due to the lacking results, the Lisbon Agenda was forced to
change some of the implementation processes. The many quantitative goals were reduced, and
only the goal to dedicate three percent of GDP to R&D stayed in its original shape. The main
goals were now on growth and jobs. The member states were to formulate national reform
programmes, and use these as their main instrument in order to reach the goals (“The Lisbon
agenda from 2000 to 2010”, 2006).
The importance of the context of the Lisbon Agenda is still very valid, and will be even more so
if the EU continues to lag behind other major economics in the world. The next step is now to
reconsider and formulate a new Lisbon Agenda. If the EU wants to reclaim some of its lost
ground, there is no time to waste since the economic world is moving fast.
The forthcoming Lisbon Agenda will certainly need new approaches, and new instruments. One
of the areas of instruments that can be further explored is innovation policies where the use of
R&D and human capital is enhanced. Human capital is a natural part of a knowledge-based
economy, and has positive impacts on growth, and jobs in the economy. Innovation policy
instruments are diversified and are integrated in many areas of an economy.
The purpose of this report is to investigate which innovation policy instruments that exist and
how they can be used in the process of the beyond Lisbon 2010.
The report has the following structure: section 2 includes some of the thoughts about the next
step in the Lisbon Agenda, which is followed by a short introduction to growth theory in section
3. The fourth section explains briefly innovation policy instruments. The fifth and the sixth
section discuss general and specific innovation policy instruments respectively. In the last
section of this report the conclusions are presented.
2. BEYOND LISBON 2010
Calls have been made to set up a strategy for the developments connected to the Lisbon agenda
that goes further than 2010. For example, the High Level Group on Key Technologies says that
Europe needs a long-term vision (30-50 years) and a transition agenda for creative system
disruption. The group is asking for a research policy that compared to the US and Japan has a
differentiation rather than imitation approach, building on the European strength in current,
potential and emerging sectors. The global competitiveness in research can be enhanced by
global cooperation in basic research areas where cooperation has been found to be successful.
Competition has proved more viable and efficient in the innovation front. The report further
stresses how important the interface between science and society is for increased
competitiveness. These are; the absorptive capacity for innovation and the knowledge transfer
mechanisms that bring knowledge to the market as commercialised products (Key Technology
Expert Group, 2006).
Eurochambres, the organization for chambers of commerce, raised their fears that there will not
be any program of economic goals after 2010. Eurochambres recommends in spite of the
shortcoming of the Lisbon strategy for the EU to prepare a new multi-annual programme, this
time using more forceful instruments of implementation than the open method of co-operation
3. ECONOMIC GROWTH THEORY
In this part there will be a brief summary of economic growth theory: endogenous growth theory
and evolutionary growth theory. This will give an insight about what the theory predicts about
economic growth and what instruments that affects it.
3.1 Endogenous growth theory
In the neoclassical growth theory, long-run growth is determined by the savings rate and
traditional an exogenous rate of technical changes (Solow, 1957). The obvious weakness of these
models is that nothing within the model determines the long-term growth rate. A higher savings
rate could boost the growth for a period but because of the decreasing returns to capital there is
an upper boundary where increased investments (determined by savings) will not affect the long-
run growth rate. Endogenous growth models were developed in the 1980s as a response to the
oversimplified and sterile exogenous models of Solow type.
The endogenous school of growth theory distinguished itself mainly by emphasising that growth
is an endogenous outcome of an economic system. Endogenous growth theory builds on
microeconomic fundamentals where firms maximize profits given their production function and
consumers maximize utility given their budget.
Romer (1990) builds his argument for endogenous growth mainly on three points. Firstly he
claims that the technological change, which is the improvement of technology by the use of new
knowledge, is one of the main drivers in growth. The technological change is an incentive for
capital accumulation. The endogenous part of the model comes from Romer’s second point
being that the technological change is mainly the result of individuals acting on market
incentives. Firms, for example, develop new products to earn extra profits. The third point is that
technologies, once developed, is applicable repeatedly at no additional cost. According to
Romer, policies should subsidise the accumulation of human capital, this will in turn foster
technical change and capital accumulation resulting in economic growth (Romer, 1990).
The fact that technology spills over between agents in the market is one of the main arguments
behind innovation policies. The spillover effects imply that the benefits of new technology are
larger than the private one reaped by the firms. Innovation policies should protect the private
returns to encourage investments and subsidise research and development in order to raise
investments to a socially optimal level. Many economists (among others Lucas 1998 and
Grossman and Helpman, 1991) claim that spillovers across actors and firms are characterised by
increasing returns. That is, the more firms and actors that integrate in R&D the larger the
positive spillover effects will be.
3.2 Evolutionary growth theory
In evolutionary theory the role of diversity creation and selection, or competition, are
emphasised as main drivers of innovation. Another important point is the path dependency of
Structural-evolutionary (SE) theory is a set of theories that tries to capture long-term economic
growth as the result of evolutionary dynamic concepts. Real world concepts affect the processes
under which technologies evolve under the influence of a stream of innovations. Therefore
factors such as uncertainty and selection are taken into account. When technology is given, neo-
classical theories and endogenous theories has served well in questions such as resource
allocation. When technology is expected to change endogenously, the SE approaches may be
more suitable (Lipsey et al. 2005).
SE approaches are taking views on both the firm and the market that are different to that of the
standard neo-classical ones. SE-theories say that it is reasonable to believe that maximizing
behaviour by the firm is a reasonable assumption when it concerns simple choices under fairly
predictable conditions. When it comes to innovating, inventing and diffusing new technologies,
uncertainty is in the picture and then the firm is rather profit oriented and markets are not
directed by an invisible hand but rather path- dependent. These views have important policy
implications. Ortodox economists generally take a very sceptical view on technology enhancing
policies and see them as distorting and that informed profit maximizing firms perform anything
that the government can do better and more efficiently. A SE-traditionalist then argues that
distortion relates to optimality conditions and hence has no place in a growing economy. Support
for technology enhancement policies is often taken from real world examples. For developing
nations, the Asian tiger economies are often taken as examples but also the early days of the now
developed nations. When looking at policies in developed countries, directed policies has often
led to a technological lead for nations for example it can be said that many groundbreaking
technologies of the twentieth-century has been developed assisted by public funds, in many
cases from the US department of defence (Lipsey et al. 2005).
4. INNOVATION POLICY INSTRUMENTS
The innovation concept has many features. Innovation can be classified as radical or
incremental. The later involves gradual improvements in existing and current technologies.
Radical innovations entail the introduction of new technologies and discontinuous change
(Murphy and Gouldson, 2000).
To make an innovation arena work, many different aspects has to be included. There must be (i)
science, both hard and soft aspects (ii) product development, with technological and social
aspects and (iii) entrepreneurship, which plays a vital role. There cannot exist any innovation
without any entrepreneurship. These factors create together a system in which the change
process is cyclic in nature (Berkhout et al., 2006).
Budgetary and monetary policies and a countries trade are getting less autonomy due to the
globalisation process and the liberalisation of financial markets. Hence, labour market policy,
social policy, infrastructure policy, education policy and not least, innovation policy is becoming
even more important and these are essential factors for sustainable economic growth. If regions
or firms do not have any innovation and learning, they will be unable to establish sustainable
growth. Innovation represents a potential source of dynamic comparative advantages by
enhancing a firms or workers learning abilities (Lundvall and Borrás, 1997).
To make the distinction between tacit or codified knowledge is important for innovation policy.
When knowledge is tacit, it is stickier and does not flow as easily across borders within
organisations or in space. Knowledge stays tacit if it is complex or changeable in quality, if e.g.
understanding social relationship is crucial, skilful physical behaviour is needed or several
different human senses is needed at the same time (Karlsson and Johansson, 2005). There would
be little incentives for firms, regions and nations to invest in R&D, if all knowledge were easily
transformed into information that everyone could access the technology gaps between regions
and countries would be minor and temporary (Lundvall and Borrás, 1997).
When new policies are to be implemented in the EU, several dimensions have to be taken into
account, vertical and horizontal. In the case of innovation polices, the vertical dimension, where
European, national and regional instruments and strategies must be harmonised with the new
policy. They should mutually complement and support each other to yield innovativeness in the
EU. In the horizontal dimension, different policy areas must be co-ordinated to bring positive
synergies to enhance the learning ability in the system (Lundvall and Borrás, 1997).
To implement an innovation policy is complicated and according to Lundvall and Borrás (1997)
there are three main features that one should take into account before implementing the policy:
• Policies concerning the transformation pressure (competition policy, trade policy, and the
position of general economic policy).
• Policies concerning the ability to innovate and handle change (human resource
development and innovation policy).
• Policies constructed so that they are able to take care of the misfortunes in the
transformation process (social, labour market and regional policies with redistribution
5. GENERAL INSTRUMENTS
The formulation of the general instruments gives the framework for the specific instruments.
One important question to lighten is if the EU is to give priority to general or specific
instruments. To classify the innovation policy instruments into general and specific instruments
can be problematic since the instruments can both have the characteristics of being general and
specific, where the term specific indicates that an instrument is designed to influence a specific
technology area or a special group of innovation agents. The EU needs to be more general in
their instruments in for example: the property rights, patent system and a common admittance of
The institutional framework of economies is a critical factor not only for innovation but also for
economic growth and development more generally. The formal institutions are the general rules
that are guiding the behaviour of economic agents. They have two basic roles: first, they define
the property rights of economic agents, and second they determine the level of transaction costs
in the economy.
The formal institutions represent a structured system of laws that is imposed by representative
forms of governance (Stiglitz, 2000). The formal institutions play an important role for
innovation, since they support the efforts of the technological advance. They also reduce
uncertainty and opportunism. The formal institutions are of great help when actions need to be
coordinated within a nation or a region.
The institutions can be classified into internal and external institutions. External institutions,
routines and behaviour regularities are those shared by the population. Internal institutions are
the shared solutions or mental models to solve the problems of social interaction. This can be
further explained from a firm point of view, where the internal institutions come from the
decision-makers within the company and the external institutions is restrictions from outside the
company (Mantzavinos et al, 2004).
Even though the main formal institutions are important there exist also a large number of
intermediate institutions such as trade associations, professional associations of engineers, and
chambers of industry. These can act as learning laboratories for their respective firm and
industry. These intermediate institutions work well in Germany and Japan and have a strong
position in contrast to the UK were they tend to be weak. For these institutions to work properly
they need to come from within the nations or the regions (Morgan, 1997).
Intellectual property rights such as patents, copyrights, trade secrets, and registered trademarks
are the base for building and extending the markets for new technologies, i.e. innovations. The
specification and enforcement of private rights to market a firm’s product is vital in almost all
industries, partly because it is becoming easier and cheaper to copy new technologies.
Intellectual property rights are in the long run promoting economic growth, technology transfer
and local innovation (Maskus, 2000). The intellectual property rights have the characteristics of
being negative, i.e. they are rights that limit other parties in their behaviour, they stop pirates,
imitations, counterfeiters, and in some cases limit third parties that have independently reached
the same ideas from using them without a licence from the right-owner (Cornish and Llewelyn,
In most countries a patent is potentially powerful during 20 years. However, it has to be renewed
every year. When the patent is granted it is only granted in that specific country. In Europe, the
European Patent Office (EPO) has the authority to grant the patent in the whole of EU or in a
selective number of member countries, if it is a request from the applicant (Maurseth, 2002).
Patents provide the inventor with a monopoly on his invention for a given time period. In theory,
and often also in practice, patents solve the problem of fully appropriating the returns when
R&D is successful and generates an invention. Patents obstruct a wider use of the invention and
restrict the diffusion of technological knowledge. Thus, patents may be an impediment,
especially when the returns from knowledge diffusion are high. Some authors even reject the
patenting of academic research in order to stimulate commercial applications, and argue instead
that the public expenditures for fundamental scientific research should be increased.
The EU is missing some of the important platforms that are needed for innovations to reach the
market, including institutions. The EU, compared to the US, have severe problems in reaching
the firms with university spillovers and have a low rate of university spinout companies (Klomp
and Roelandt, 2004). There exist different systems in the EU for fostering patenting through
universities many member states have weak incentives and institutions for universities to
commercialise their innovation. This is regulated, exception for academic researchers (called the
“lärarundantaget”), in Sweden, which states that teachers, researchers and PhDs is the owner of
the patents even if they are developed at their workplace at an university. One way is of course
to sell the patent and receive financial compensation. In the US universities the patents belong to
How competition in the different markets for goods and services affects the level of innovation
within the EU and its different member states is an important aspect. The incentives for
innovation increases, if there are more agents in a market because the social return on innovation
can be assumed to increase with competition. A monopolist has limited incentives to innovate
particularly in terms of new products, since the monopolist will compete with himself and risks
only carrying extra R&D costs without being able to increase his monopoly profit. Thus, a
monopolist risks hurting himself by being innovative.
The intensity of competition has an ambiguous effect on the willingness to innovate. In
competitive markets, there are no losses for innovative entrants, since they have no monopoly
profits to loose. The difference in profits from innovation in competitive and monopolistic
markets is known as the Arrow effect. However, innovation has spillover effects, since
competitors may profit from each others R&D-efforts. Hence, the higher the spillover risks, the
lower the incentives to innovate. With fewer competitors, there are fewer potential free riders,
and, thus, the incentives to innovate are stronger because firms can appropriate relatively more
of the returns from their own R&D-efforts.
The structure of the actual industry will determine which of the effects that will dominate. An
‘even’ industry consists mainly of firms with comparable productivity levels. A higher intensity
of competition in such an industry will stimulate innovation because the positive Arrow effect
dominates the reduced spillover from R&D. Firms in even industries will concentrate on
incremental innovations. In ‘uneven’ industries, with substantial differences between leading and
lagging firms, a higher intensity of competition will lead to fewer innovations. The Arrow effect
is too small in such markets to compensate for reduced spillover effects. Thus, potential entrants
will not make a sufficient return on their drastic innovations.
“The Porter hypothesis” suggests that countries that have stricter environmental regulations then
other countries will increase their innovations within the field and will therefore become a net
exporter of newly developed environmental technologies. There have been some case studies
that indicate that more stringent regulations have resulted in innovations but they do not provide
a general consensus of the impact that environmental regulations have on innovations. This
phenomenon is difficult to test empirically due to lack of data. It has however been found that
regulatory compliance cost have a positive effect on patenting of environmental technologies
(Jaffe and Palmer, 1996).
Environmental regulations in any form, command-and-control or market-based, have the
potential for inducing or forcing some amount of technological change, since by their very
nature, they induce or require firms to act in ways they would not otherwise choose. It is,
however, impossible to say by how much the firms will change their behavior. Empirical
evidence and theoretical findings suggests that market-based instruments are likely to have
greater, positive impacts over time than command-and-control approaches on the invention,
innovation, and diffusion of environmentally-friendly technologies (Jaffe et al, 2002).
There is a fine line between too much and just right amount of institutions. University systems
may provide stable and efficient conditions for interactive learning. However, they may also
become a hinder in the process and lower the learning and innovation capability. Institutions
might also become a constraining factor since there is interdependence between the institutions.
All single institutions have its own fixed place in the system and if one institution changes it will
bring instability since the whole structure of system changes. This yields that either no changes
at all are taken or only minor changes are taken that does not shake the structure. Thus,
institutional rigidity hinders new institutions that are needed for implementation of new ideas
and innovations. On the other hand, a weak formal institution, which arises due to too little
institutions, is also negative for the innovation capacity in a nation or a region (Boshma, 2005).
Another type of institution that is important for innovation is the social institutions, which refer
to repeated patterns of behaviour, such as habits, routines and conventions. Innovation is
strongly dependent upon the social institutions, and their variety of routines and social
conventions (Morgan, 1997).
Infrastructure and in particular transport infrastructure has for a long time been a major policy
issue within the EU. Special interest has been devoted to, on the one hand, provision of better
transport connections between the different member states to stimulate trade by decreased
transport costs, and, on the other hand, improvement of the infrastructure in less favoured
regions within the community in order to make EU more coherent. Plans for trans-European
transport networks (TENs) have been presented and approved. Some of the links in the trans-
European networks have also been built but the speed of implementation has generally been all
too low due to a lack of funding and political will. The investments in TENs have to a large
extent been motivated by a wish to implement the common market i.e. improve the mobility of
goods and people. In general, the importance of infrastructure for research and development
(R&D) and innovation seems to have been neglected.
Research has shown that knowledge flows tend to be spatially bounded and that an extension of
functional regions by means of shorter travel times may stimulate knowledge production
(Ejermo, 2004; Gråsjö, 2006) as well as productivity growth (Andersson & Karlsson, 2007).
Studies have acknowledged the importance of “networks” in the innovation process.
Infrastructure plays an important role in the networks and in their capability of the internal
communication (Cooke, 1996).
Innovations depend on the geographical infrastructure and its capability of mobilising technical
resources, knowledge and other inputs needed in the innovation process. This infrastructure
includes sources of knowledge, such as networks of firms, concentrations of R&D and business
services. Once the infrastructure is established, it enhances the capability of innovation, since the
region will develop and specialise toward a technical or industrial sector (Feldman and Florida,
Ebadi and Utterback (1984) find that there exists a positive relationship between the frequency,
centrality and diversity of communication and technological innovation, at the individual level,
where the frequency of communication has the largest impact. At the firm level, the same
patterns were found, and also network cohesiveness was found to have a positive impact.
The innovations in information and communication technology (ICT) have increased during the
last years and have brought positive effects on productivity. This process has differed
considerably between countries, which is partly due to the capital market structure in different
countries (Houben and Jakes, 2002). ICT and innovation tends to be closely related. Firstly, ICT
is itself a technological innovation. Secondly, ICT also affects innovation in a broader sense
since it supports the creation of new and better applications and production processes. According
The existing literature suggests the following policies:
• Support the growth of intermediate institutions
• Further develop EPO
• Focus on the relationship between university spillovers and firms
to this view, ICT is supporting the productivity of all inputs, and can therefore be capable to
increase the total factor productivity (TFP). Labour productivity can be enhanced by ICT
through a direct approach, capital deepening, and through an indirect approach, by enhancing
innovation (van Leeuwen and van der Wiel, 2003).
Some empirical evidence support the belief that clusters tend to bring a higher level of
innovations which is partly caused because clusters create economies of scale, facilitates face-to-
face interaction and shorten interaction distances in general. Product innovations are strongly
connected to clusters within a region. One important feature of these clusters is the technological
infrastructure (Feldman and Florida, 1994).
Knowledge flows in Europe is a key issue. Knowledge flows have different characteristics and
can be (i) transaction based, (ii) transaction-related or (iii) pure knowledge spillovers (Karlsson
& Johansson, 2006). However, knowledge flows tend to be bounded in space, irrespective of the
type. Several studies have confirmed the need to improve the transport infrastructure in Europe
to improve the accessibility to new knowledge for regions outside the metropolitan regions and
also to improve the knowledge exchange between the metropolitan regions in Europe. Another
instrument to speed up knowledge flows in Europe is to encourage a higher rate of spatial
mobility among knowledge handlers (Zucker, Darby & Armstrong 1998; Zucker, Darby &
Brewer, 1998; Almeida & Kogut; Möen, 2000).
Concluding remarks on infrastructure policies:
• Continue to invest in TENs, in order to improve the knowledge
accessibility for regions surrounding metro regions
• Improve and expand the infrastructure since it enhances the knowledge
production and productivity growth, it is also beneficial for networks
• Continue with the investments in ICT and promote the use of ICT
Incentives such as intellectual property rights have already been discussed earlier in the report.
Incentives systems can either rely on the private sector and its investments, or it can rely on
public expenditure. The incentives can also be a mixture of private and public spending. The
incentives aim at augmenting the R&D-efforts, which will enhance the rate of innovation. The
incentives are based on the fundamental role that diffusion of knowledge plays in technological
progress and economic growth.
Tax-based subsidies to R&D leave the choice to the private sector, of how to conduct and pursue
R&D-efforts. R&D-efforts are expensed and can therefore be subject of tax subsidies, compared
to fixed investments. There exists evidence that the tax system has an impact on R&D-efforts.
The tax-based system has some flaws compared to government financed or firm financed R&D-
effort. Fiscal incentives seem to be ineffective in raising private R&D-efforts since the response
elasticity is very low. Thus, it would take a large tax cut to reach the socially desirable level of
R&D spending. Another problem faced by the firms is when the financial incentive system
change often and thereby causes uncertainty for the firms (Hall and Reenen, 2000).
Behavioral additionality is a measure to determining how firms change their R&D behavior as a
result of government policy instruments. It differs therefore from the traditional evaluation
which focuses on determining the amount of additional spending on R&D that result from a
government intervention. The behavioral additionality has so far been underdeveloped which is
to be considered as a flaw since it contains many advantages. Behavioral additionality provides
policymakers with a useful vocabulary, reveals qualitative changes in firm conducted R&D and
reveal the procedure firm choose when conducting the R&D when participating in a government
funding programmes (OECD, 2006).
As in the case of fiscal incentives, the financial subsidies to R&D aim to correcting the
underinvestment in private R&D-efforts caused by market failures such as incomplete returns to
knowledge investments. Another factor that influence is the fact that knowledge is partly a
public good with characteristic such as non-excludability, or incomplete financial markets. The
main reasons behind financial subsidies to R&D-efforts are incomplete R&D assessments and
financing constraints in the firms. Financial subsidies can increase the R&D-efforts in firms,
since they decrease the market uncertainty for new products by increasing the expected return
from the R&D-efforts (Czarnitzki and Toole, 2006).
The government has the same difficulties as a bank when handing out financial subsidies. The
government faces adverse selection, problems with monitoring the quality, reliability, credibility,
asymmetric information and general lack of information. The design of the financial subsidy can
easily result in a selection which is directed towards the worst performing firms within a sector.
Governments can stimulate private investments in R&D by subsidies. The problem is however,
that a subsidy often generates little additional R&D-investments. Public subsidies to R&D-
investments run the risk of only reducing the private costs of R&D-projects, which would have
been undertaken anyhow, i.e. they crowd-out non-subsidized investments in R&D. Subsidies
may also be given to R&D-investments whose returns are too low from a social point of view.
Often no cost-benefit analyses are made and it is genuinely difficult to evaluate the social returns
of individual R&D-projects. Firms may also take advantage of the system by presenting other
costs to the government claiming that they are R&D-costs. Subsidies can, however, also be
positive and alert firms, in particular SME’s, and their co-operation with public organisations
such as universities. Hussinger (2003) finds that that public funding increases firms’ R&D
expenditure. However, the size of the effect depends on the assumptions imposed by the
particular selection model.
If subsidies are effective, they lead to an increased demand for R&D-personnel and thus to wage
increases for such personnel, if they are in short supply. It is an open question, whether there is a
shortage of R&D-personnel within the EU. Certainly, the situation differs between the different
member states but at least in the case of high level R&D-personnel, the labour market is global
and it should be possible for the different countries to recruit enough personnel given that the
offers are attractive enough.
5.4 Education and training
Human capital is an important factor when explaining innovation and economic growth. This can
be seen in the human capital index given by the Lisbon Agenda. The index is used to rank the
European countries and involves four dimensions (i) endowment, (ii) utilisation, (iii)
productivity, and (iv) demography and employment.
5.4.1 Higher Education
It is important to analyze the role of higher education in promoting innovation and the effects of
education on labour productivity. Empirical research has convincingly shown that education
raises labour productivity. However, the link between higher education and innovation is weak.
A possible explanation might be that only a minor part of the workers with higher education
moves into innovative jobs.
Although it is hard to establish a link between higher education and innovation at the macro
level, there should be such a link at the micro level through R&D. The reason is that graduates
with an engineering, technical, or science education are the most important input in R&D-
production. Since R&D has substantial positive external effects, the supply of this type of
graduates is of crucial importance for EU’s innovative capacity.
Engineering, technical, and science studies have lost substantial popularity in recent decades in
many member states. Thus, the supply of graduates in these fields has decreased relative to other
fields. Assuming a stable level of demand for graduates from engineering, technical and science
studies, this should have resulted in higher wages for such graduates compared with graduates
from other fields. However, empirical studies indicate that the relative wages for graduates from
engineering, technical and science studies have remained the same or have even been falling.
This implies that the labour demand for other types of graduates must have increased so much
that any wage pressure due to a reduced supply of graduates from engineering, technical and
science studies has been offset, given that the demand for such graduates has not decreased. The
general conclusion seems to be that there is no general shortage of graduates from engineering,
technical, and science studies within the EU.
A related issue is the quality of the engineering, technical and science education offered by
universities within the EU. Here the problems are obvious. What the EU needs is that a sufficient
number of universities are given opportunities within a competitive race to develop to elite
universities that can compete with the best universities in the US and which are open for top-
students from any country in the world.
Concluding remarks on incentives policies:
• Develop the behavioral additionality
• Subsidies from the public sector should target specific groups of firms,
where the subsidy produces positive externalities
An often-used motivation for government intervention in higher education is that education
generates positive external effects similar to the R&D case. In the presence of positive social
effects, governments should subsidise education up to the point where the social and private
returns are equalized. However, in contrast to R&D, external effects of higher education are
notoriously difficult to measure empirically and most reliable estimates that the social returns to
higher education equal the private returns, i.e. the individuals taking higher education are able to
appropriate all the benefits of higher education. Thus, there is no argument for further increases
in the public expenditures on higher education at the current level of education subsidies within
most of the EU-15 states. The EU is limited, in its education formulation, by its social policies;
this is one major difference that exists between the education system in the EU and in the US.
One important aspect of the markets for higher education within the EU is that the union does
not function properly due to lack of competition. As a consequence of the policy-induced
structure of the higher education sector, publicly financed institutions of higher education are
able to take advantage of a kind of monopoly situation, which is essentially unchallenged
because non-subsidized potential entrants cannot compete with the subsidized “monopolists”.
This situation undermines the quality of higher education within the EU and is harmful for
investments in human capital. It also explains why so few, if any, universities in the EU can
compete with the leading elite universities in the US. Making universities into self-governing
institutions and reducing barriers to entry in the market for higher education, by creating a level
playing field can stimulate entry, foster competition, make institutions of higher education more
efficient, and provide students with more educational choice.
The returns from investment in education are found in the following table. Table 5.1 shows that
Europe and OECD countries have a low rate of return in their investment in education, from a
social view. From a private perspective, OECD countries are far below the rest of the world. It is
therefore important that the private investment in universities increases and become profitable so
that universities receive financial resources to develop.
Table 5.1 Returns to education by level, in percentage.
Source: World bank statistics
5.4.2 Primary and Secondary education
The primary and secondary education is both included in the concept of human capital. Human
capital is in the new growth theory the main source of innovation since it allows individuals to
produce and adapt technological change. A high ratio of human capital generates economic
growth since more human capital makes it easier to absorb technologies from other countries and
develop it further, which is important from the secondary education level and up. The primary
education is a prerequisite for the other education levels and should therefore also be included as
an important factor. It is important to separate the quantity from the quality in all levels of
education (Barro, 2001).
Countries that are less-developed with lower average income tend to have a higher return on
their investment in primary and secondary education. Higher education is more vital for the
growth in OECD countries. However, a general finding is that the initial average level of
education i.e. the stock of human capital, measured as the literacy rate or primary and secondary
enrolment ratio, has a positive impact on economic growth (Blundell et al, 1999). When
evaluating 21 OECD countries Gemmel (1996) found a positive relationship between investment
and the ratio of the labour force with secondary education.
5.4.3 Other sources
Firms that invest in human capital do this by investing in on-the-job-training. The training
increases the productivity of the employees since they become more efficient. On-the-job-
training can be any activity undertaken at the firm that increases the productivity of the
employees. These activities can be formal, workshops and specific education and informal
training, such as learning-by-doing (Kalaitzidakis, 1997).
On-the-job-training is needed the most when firms adopt new technologies or if the firm is
experiencing a large change in their environment such as a shift from low to high skill jobs. This
is found in many OECD countries. According to several surveys conducted in firms, the
appropriate skill of the employees is an important factor when adopting innovations and
technologies (Acemoglu, 1997). On-the-job-training can affect the demand for labour due to
their observed abilities, such as education but also due to the unobservable abilities
In an imperfect labour market, future employers will benefit from the on-the-job-training that the
employees receive. This externality is between the today’s employer and future employers and
will lead to that too little on-the-job-training will be conducted. When many firms adopt an
innovation the employees expect a higher return from their skills and are more eager to get
involved in on-the-job-training. The probability of innovation and training will therefore
increase by the thickness of the labour market. There exist also a relationship between the
employee and the current employer which arises due to incomplete contracts and credit market
imperfections. The later problem can be solved by, for example, penalties for workers that leave
the current employer (Acemoglu, 1997).
Lifelong learning is a concept that is broader then the education period or the knowledge
acquired at the working place through, for example on-the-job-training. It is continuous spectra
of the learning process that takes place at all levels in the society, formal, non-formal and
informal. Since it is increasing, the stock of human capital it is beneficial for the innovation level
in a nation or in a region. The reason behind the need of lifelong learning is the rapid changing
technological environment and the structure of the economy that puts pressure on the employees.