Capturing Innovation Complementarities for Green Growth

ISSUE NOTE Session 1

GREEN GROWTH AND SUSTAINABLE DEVELOPMENT FORUM

14 & 15 December 2015 - OECD, Paris

ISSUE NOTE

SESSION 1, 2015 GREEN GROWTH AND SUSTAINABLE DEVELOPMENT FORUM “CAPTURING INNOVATION COMPLEMENTARITIES FOR GREEN GROWTH”

OECD GREEN GROWTH AND SUSTAINABLE DEVELOPMENT FORUM

The Green Growth and Sustainable Development (GGSD) Forum is an OECD initiative aimed at providing a dedicated space for multi-disciplinary dialogue on green growth and sustainable development. It brings together experts from different policy fields and disciplines and provides them with an interactive platform to encourage discussion, facilitate the exchange of knowledge and ease the exploitation of potential synergies. By specifically addressing the horizontal, multi-disciplinary aspects of green growth and sustainable development, the GGSD Forum constitutes a valuable supplement to the work undertaken in individual government ministries. The GGSD Forum also enables knowledge gaps to be identified and facilitates the design of new works streams in order to address them.

Authorship & Acknowledgements

This issues paper was prepared for the 2015 GGSD Forum to steer discussion around the theme of Session One, “Capturing Innovation Complementarities for Green Growth.” Daniel Kupka, consultant to the Secretariat, was the lead author and Mario Cervantes provided substantive input. This issues paper benefitted from OECD staff comments including Dirk Pilat and Dominique Guellec (STI), as well as Kumi Kitamori and Ryan Parmenter (ENV). The opinions expressed herein do not necessarily reflect the official views of the OECD member countries.

CAPTURING INNOVATION COMPLEMENTARITIES FOR GREEN GROWTH

EXECUTIVE SUMMARY 4

1. THE LINK BETWEEN INNOVATION AND GREEN GROWTH 6

1.1 THE POLICY CONTEXT 6 1.2 THE CURRENT STATE OF POLICIES FOR GREEN GROWTH: A RAPID OVERVIEW 8 1.3 BEYOND CONVENTIONAL STI POLICY: MAKING THE CASE FOR SYSTEM INNOVATION 10

2. ENABLING GOVERNANCE STRUCTURES TO FACILITATE TRANSITION 13

2.1 PROVIDING VISIONS AND STRATEGIES 13 2.2 POSSIBLE POLICY INSTRUMENTS 15 2.3 POLICY INTELLIGENCE 18 2.4 CREATING LEARNING AND AGILE GOVERNMENT INSTITUTIONS 19

3. RESEARCH GAPS, PRIORITIES FOR FUTURE RESEARCH AND QUESTIONS FOR DISCUSSION 23

6. REFERENCES 28

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EXECUTIVE SUMMARY Innovation is necessary to enhance economic growth while addressing environmental degradation and resource depletion. The policy conclusions from the 2011 OECD Green Growth Strategy and the 2015 OECD Innovation Strategy suggest that achieving green growth will involve and require a broad policy approach to enhance the sustainability of socio-economic systems as a whole, including a mix of policy tools and instruments, such as economic instruments, intellectual property rights (IPRs), public R&D, public procurement, financing incentives, and voluntary initiatives, amongst others.

Innovation for green growth in this context is best facilitated by policies that take a system perspective, which allows for the exploitation of synergies between the range of institutions, sectors, technologies and stakeholders from different levels of government, industry and civil society which are involved. Policy responses, however, in such complex settings are inherently more difficult. Charting the policy space is therefore necessary in order to improve current policy governance practices and arrangements. As such, effective policy governance requires both the mobilisation of existing policy frameworks and the development of new ones. System innovation is a useful concept to illustrate a horizontal policy approach that mobilises technology, market mechanisms, regulations and social innovations to solve complex societal problems in a set of interacting or interdependent components that form a whole ‘socio-technical system’.

One defining element of the system innovation approach is a set of credible and sufficiently ambitious objectives and visions in government, in firms as well as intellectual and opinion leaders in civil society. And a well-crafted strategic vision or plan needs to be supported through a refinement of policy instruments as well as the overall mix of policy instruments based on the objectives that have been set. Nevertheless, design and implementation issues remain, such as instrument co-ordination, timing and sequencing, adequate balancing and the interplay of policy instruments, technology-neutrality and the impact on “incremental” and “radical” innovation, amongst others.

In addition, system innovation requires a considerable upscaling of policy intelligence gathering and analytics capacities, including new and large volumes of data, in order to make decision-making processes smarter, more confident, and more ambitious. To this effect, a variety of new data sources have recently been collected, such as social network and business records data, to help understand technology emergence and to improve funding strategies. A policy intelligence task that is generally underappreciated but seems distinctly necessary for system innovation is that of mapping the system. Discovering the system’s internal organisation and precisely mapping its boundaries can be important in understanding the system’s boundaries and identifying potentially profitable missing links with sub-systems and other systems.

To enable transitions and systemic changes, government institutions need to rethink or innovate in how they work; in the services they provide and how they provide them; and in how they interact with citizens, businesses and civil society. As such, government institutions are part of the solution to enable a transition for green growth, but sometimes, they are part of the problem too (e.g. the case fossil fuel subsidies).

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To enhance the contribution of system innovation for green growth, future research could pay more attention to the policy levers that can accelerate the development and deployment of emerging green technologies. We have limited knowledge of policy-induced factors (e.g. funding, regulation) that enable certain technologies to emerge while others do not. Improving the available data on emerging technologies as well as case studies could prove useful in this respect.

Equally important are insights into topics as diverse as behavioural change, engineering constraints and opportunities, as well as user and customer practices that might bear fruit providing practical and actionable policy advice.

Moreover, future research on system innovation should be shaped by the problems of practitioners and not only by concepts. Policy instruments that are important for system innovation include technology and industry roadmapping, large scale industrial and technology demonstrators and regulation to name a few.

Lastly, if governments are to be serious about a green transition, change necessarily needs to start within government institutions. It may require relative improvements in a set of (broader and/or administrative) governance capabilities and capacities, including capacities needed for policy development, implementation, learning as well as the engagement of stakeholders. They also need to be good at brokering cooperation between business and civil society; be ready to take risks and not simply seek consensus; and make use of new techniques for fostering innovation.

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1. THE LINK BETWEEN INNOVATION AND GREEN GROWTH

1.1 THE POLICY CONTEXT

The relationship between green growth and innovation policies is a mutually dependent one but it is one where the co- dependence is ambiguous; at times complementary and reinforcing, at times neutral or at times contradicting. The mutual dependence arises from two factors. The first is the existence of market failures in the environment that affect incentives for innovation in firms and the behaviour of consumers. Market failures also arise in the incentives for firms to adopt and invest in innovations that are “greener”. If market prices do not reflect the cost of polluting and depleting natural resources, economic actors (firms and public services) will not be induced to innovate. In addition, consumers will not be induced to change behaviour or to pay for the cost of polluting. The second source of mutual dependence arises from the failure of public policies and/or their misalignment such as policies that subsidise fossil fuels or tax policies that favour short-term financial investments (OECD/IEA/NEA/ITF (2015). The effects of policies on innovation and green growth can be complementary, but not always. Innovation will not automatically lead to greener growth if, for example, “green” innovations do not offer a competitive price-quality ratio; if regulations and standards increase the costs of green innovations; if incumbents are protected and new entrants are blocked from entering the markets, or if consumer taste and behaviour is not incentivised to change. In fact, history provides us with many examples of innovations which while fostering economic growth, have had negative externalities on the environment1.

Innovation policies must therefore be complementary to a wider range of public policies and instruments to promote innovations that are green or at least green-friendly. These include instruments that change the economic incentives of actors (e.g. fiscal measures, subsidies), regulation, international co-operation but also incentives for new entrants to bring innovation to the market.

With regards to the Green Growth challenge, a wealth of different analytical perspectives have been adopted to investigate the dynamics, characteristics and determinants of innovation2 and their impact on economic systems and societies as a whole (Box 1). These suggest that a variety of factors determine how green innovations come about and the speeds of both invention and diffusion but also highlight the primary role played by public policies. Previous OECD work has shown that markets, in particular those for “green” technologies, are highly dependent on government intervention, and with few exceptions, these markets have been policy-induced. Examples include amongst many others the waste management and the renewable energy sectors (OECD, 2011a; Johnstone et al., 2010). In the 1980s-1990s, stringent environmental regulations for waste recycling in Germany led to domestic development of technologies that today are widely used internationally. These policies turned out to be very effective in inducing innovation (e.g. Haščič, 2012).

1 The example of leaded gasoline is illustrative. Tetraethyl lead (TEL) was mixed with gasoline (petrol) beginning in the 1920s as a patented innovation that reduced engine knock in internal combustion engines and increased vehicle performance. Leaded fuel however was identified in the 1970s as being the leading source of lead contamination of the earth’s environment and as well as dangerous neurological agent. 2 Generally, notions/terms to describe innovations that have a reduced negative impact on the environment include “green”, “eco”, “environmental” and “sustainable”; these are often used interchangeably.

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Box 1. Fostering innovation for green growth: Policy lessons learned

• The scope of potential market and systemic failures suggests that policies for environmental and green innovation will only succeed if they enhance the performance of the economic system as a whole. Thus, policies that focus only on one element of a system are unlikely to be effective in improving overall environmental performance. For example, policy interventions to address market failures in one part of the system (e.g. investment in renewable energies) may require complimentary interventions in others parts of the system (e.g. standards and regulations on CO2 emissions of new or existing buildings).

• Boosting green innovation requires clear and stable market signals, e.g. carbon pricing or other market instruments addressing the externalities associated with environmental challenges. Such signals will enhance the incentives for firms and households to adopt and develop green innovations. However, better pricing will not be enough to deliver the necessary green innovation.

• One important policy action is public investment in basic and long-term research. Such research has a public good character and is therefore unlikely to be undertaken by the private sector. It helps address fundamental scientific challenges and fosters technologies that are considered too risky, uncertain or long-gestating for the private sector.

• Support for private investment in innovation, notably R&D, and for the commercialisation of green innovations. Such support may be required as green innovation faces additional barriers in some markets, e.g. barriers to entry in the electricity sector. Provision of targeted support can be risky because of the lack of information on the maturity of specific technologies, and their likely future commercial potential.

• Support for general-purpose technologies. Because targeted support tends to be focused on specific innovations, the problematic prospect arises of governments attempting to pick winners. One possible approach to providing support that is technology neutral is supporting general infrastructure or basic conditions for a wide range of alternative technologies, e.g. storage technologies that are needed for a wide range of technologies, or general-purpose technologies such as ICT that have a wide range of applications.

• New entrepreneurial firms play an important role in delivering more radical green innovations that challenge existing firms and business models. Policy needs to create the room for such new firms by enabling their entry, exit and growth, ensuring fair competition and improving access to finance, which remains a major constraint for the entry and growth of young firms.

• To foster the wide diffusion of green innovation within and across countries, new approaches to the diffusion of knowledge and technologies need to be explored. Such approaches need to be based on well-functioning systems of intellectual property rights (IPR) protection and enforcement that provide incentives for investment in innovation and establish the framework for IPR protection and diffusion.

• In addition to the need for carbon pricing or other ways of dealing with environmental externalities, demand-side innovation policies are an important part of the policy mix to foster green innovation as these can help strengthen green innovation in specific markets. Standards, well-designed regulations and innovative procurement, for example, can encourage green innovation in areas where market signals are not fully effective, e.g. housing markets.

• Furthermore, environmental pressures also require radical changes in lifestyles and behaviour and policies such as consumer policies, eco-labelling and consumer education can support such changes.

• Policy also needs to consider the innovation timeframe and the respective benefits and risks of specific policies. Some innovations are already available commercially and can be deployed rapidly, and some win-win options may exist too; these may need no or only limited policy action to become effective in improving environmental performance.

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1.2 THE CURRENT STATE OF POLICIES FOR GREEN GROWTH: A RAPID OVERVIEW

The recognition that innovation is desirable to cope with sustainability and Green Growth issues is not sufficient in itself. One needs effective policies to ensure the potential benefits are actually achieved. What is required then is better knowledge about how to best influence innovation for green growth from a policy-makers perspective. Credibility and predictability in policy frameworks is also essential (OECD, 2015c).

A lot of progress has been made in developing policy frameworks and instruments to help guide policy-makers more effectively. The work is still ongoing and resulted so far in a host of useful policy lessons, messages and tool boxes regarding policy governance and the choice and design of policy instruments, notably stemming from OECD´s Green Growth and Innovation Strategies (2010, 2011b, 2015a), and related works on innovation and green growth across academia and International Organisations (e.g. World Bank, UNEP). As a result, there is a growing consensus on basic principles, rationales of public intervention 3 and the positive inducement effects played by those policy

3 There are several rationales for policy action in the area of “green” innovation (OECD, 2015a). One is the negative externalities associated with climate change and other environmental challenges. They have implications for both the creation and diffusion of innovations and technologies. Because greenhouse gas (GHG) emissions are not priced by the market, incentives to reduce them through technology development are limited. Similarly, there is less diffusion and adoption, once green technologies are available, if market signals regarding the environmental benefits are weak, so that demand for green innovation will also be below the social optimum. In turn, there will be little incentive for companies to invest in innovation, because there will be little demand for any resulting products or processes. Apart from the externalities associated with the environment, there are also important market failures specific to innovation, and particularly to green innovation. These include technological path dependencies, dominant designs in certain markets, such as energy and transport that favour incumbents, uncertainty about the prospects for success, the long timescales for infrastructure

Box 1 (continued). Fostering innovation for green growth: Policy lessons learned

• A key challenge is the alignment of the goals of ministries, research funding agencies, higher education institutions and social and market-based institutions so that they focus on green growth in all of its dimensions.

• The effectiveness of policy design for specific areas will depend on the innovation and knowledge capacity of a given country and its ability to develop an appropriate policy mix for green innovation that includes energy, trade, transport, agriculture and the links between them. Strategic policy intelligence, including via the exploitation of open government data and sharing of that data across ministries, can help deliver more effective policy mixes for greener growth.

• A greater research effort focused on fostering green innovation will also benefit from enhanced international co-operation. This will help share the costs of public investment and can also help improve access to knowledge and foster the transfer of technology across countries.

Source: Compiled from OECD 2010, 2011b, 2015a

SECTION SUMMARY • Innovation is an engine of growth which affects the environment, positively or negatively. • Innovation and its impact on economic systems, societies and the environment depend on

public policies. • There are a number of strengths and advantages that can be realised through the

application and use of a systems approach

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instruments, in particular of “Science, Technology and Innovation” policies (STI) on the dynamics of innovation for green growth.

As stated by the OECD and others, this will involve and require a broad policy approach to enhance the performance of the economic system as a whole, including clear incentives to encourage structural and behavioural changes, e.g. through environmental taxation, as well as significant investments in infrastructure, equipment, knowledge, and human capital. It also requires an appropriate mix of innovation policy tools and instruments, such as:

• Public procurement of green innovations that can create “lead markets” of users and stimulate technology diffusion and adoption;

• Intellectual property rights (IPRs) that incentivise investments in R&D and innovation and other types of regulation which affect product, labour and capital markets;

• Public investment in research. Many of the technological innovations that are needed in transport or energy will come out of public research in a range of scientific fields from physics, to materials science to computer science. This also implies effective support for the commercialisation of “green” innovation from public research;

• Public support to business R&D is also needed to reduce the costs of innovation. This includes both direct and indirect support in the form of competitive grants or investment tax credits and accelerated depreciation schemes.

• Support to business entrants, exits and start-ups and their growth. Green growth builds not only on technological innovations of large organisations, but also that of start-ups.

Moreover, as innovation of importance to green growth may occur in any economic sector, industry or type of application, public support for innovation should be broad-based. Essential to this is support for basic research and the use of key enabling technologies with wide applications (i.e. ICTs, nanotechnologies, biotechnologies). The evolution of sustainable manufacturing has been realised through both technological and non-technological green innovations. For example, circular manufacturing processes that rely on ICTs and new business models, such as product-service systems, which facilitate the move towards closed-loop production systems, have gained ground. Environmental pressures also require radical changes in lifestyles and behaviours as well as policies such as consumer policies, eco-labelling and consumer education.

Insofar as a transition 4 towards a sustainable economic system is a high level political goal, innovation policies should therefore adopt a systemic perspective. Policy interventions to address market failures in one part of the system (e.g. investment in renewable energies) may require complimentary interventions in others parts of the system (e.g. standards and regulations on CO2 emissions of new or existing buildings).

replacement and development, a lack of options for product differentiation, liquidity constraints of smaller challenger firms or barriers related to behaviour (e.g. consumer resistance to change). Other barriers to innovation are more generic such as lack of capabilities, etc. (OECD, 2012a). 4 Note that terminology of “transitions” is not standardised in these areas, so these descriptions reflect general usage, not hard-and-fast definitions.

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Policies that focus only on one element of a system are unlikely to be effective in improving overall environmental performance. At the same time, a nuanced and flexible approach to policy-making by government is needed.

1.3 BEYOND CONVENTIONAL STI POLICY: MAKING THE CASE FOR SYSTEM INNOVATION

Appropriate policy responses in complex settings previously described are inherently more difficult to prescribe and co-ordinate than those discussed in connection with clear cases of market failure. One might argue that it seems no more likely that such a systemic STI policy for green growth could be established than a systemic policy for social housing, health, transport or energy. These issues are simply too complex and comprise too diverse a collection of interests to be brought under any systemic process of governance or regulation. Indeed, the challenges to the governance of STI policy for green growth are many and include: the pervasiveness of innovation and environmental issues throughout the government and across policy domains; the mixed track record of most government institutions working horizontally (e.g. across ministries) and vertically (e.g. between ministries and implementing agencies at regional and local levels); inertia of actors; the dominance of certain ministries/agents as well as the need to include an unprecedented range of public and private actors vying for priority.

In the same vein, it appears that most current governance structures and practices seem ill-adapted to tackle complex challenges characterised by interdependencies that while not new, have been intensified by globalisation and ICTs, especially big data and social media. This is also in line with a recent OECD stock taking exercise of country experience in implementing green growth. The report concludes that new governance arrangements are needed, to help align economic (such as STI policies) and environmental policies, and overcome institutional inertia in policy-making (OECD, 2015b). As such, there is still space for investigating how new governance arrangements may facilitate and underpin innovation trajectories towards more sustainable paths.

Charting the policy space is an exercise in relative improvements in current governance arrangements, rather than panacea. It is therefore critical to experiment with different ways of structuring policy in this area so as to overcome the various conceptual and practical policy challenges. Some OECD countries are already experimenting with alternative policy governance arrangements and mechanisms in complex areas such as smart cities, smart grids, or sustainable buildings (see Box 2).

SECTION SUMMARY • Innovation is an engine of growth which affects the environment, positively or negatively. • There is a broad consensus among policy-makers on basic principles, rationales of public

intervention and the positive innovation-inducement effects played by policy instruments, in particular of “Science, Technology and Innovation” policies (STI).

• Systemic and broad policy approach required to enhance the performance of the economic system as a whole. Policies that focus only on one element of a system are unlikely to be effective in improving overall environmental performance.

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In this respect, what can be hoped for is the development of a more systematic concept taking into account the long time-horizon of changes, the uncertainties and complexities of innovation and the multitude of actors and interests involved. This would be an improvement over current tendencies toward ad hoc and static planning approaches and one-off policy measures. Filling this gap and addressing such implementation issues is the aim of the ongoing OECD project on “System Innovation”, which intends to clarify and advance the debate, with a particular interest on policy governance (see Box 3).

Box 2. Sustainable building in Sweden - Malmö´s Innovation Platform

Swedish housing policy has over the past years been characterized by a growing awareness of the significant role housing and especially cities have, in meeting the challenges of climate change and sustainable development. To complete the government’s interventions – in particular through laws and regulations – municipalities are key actors to address these challenges. Municipalities were given the authority to identify and prioritize local environmental problems and to apply for funding for the solutions that they considered effective. This served as strong stimulus to municipalities and regions to intensify their efforts and to build competence and knowledge to increase ecological sustainability.

At the same time, the Research Council Formas doubled its funding of research for ‘built environment’ between 2010-2013, partly reflecting earmarked funding for the area in the most recent government research and innovation bill. In 2013, the Energy Agency started a new programme, “research and innovation for energy efficient construction and dwelling” with an annual budget more than twice that of a similar previous program. VINNOVA’s, Sweden´s innovation agency, involvement with urban development has increased after it launched its programme “challenge-driven innovation” in 2011. Projects in the area of “sustainable and attractive cities”, one of the four broad challenges addressed in the programme received about SEK 80 million in funding in 2013, part of which was allocated to the called Innovation Platforms in Malmö and three other cities.

For example, the Malmö Innovation Platform uses the need of renovation as an engine for a wider process of change towards a sustainable city. The aim is to experiment with innovative financing models and to involve stakeholders from policy, industry and society. The Platform is a result of an increased awareness of the importance of systemic and collaborative approaches. However, evidence shows that the potential for innovation in this area, the pace and depth of renovation is much slower than what would be desirable. Major bottlenecks are adequate non-monetary incentives, financing models, coordination and practical verification of technical solutions. Source: Compiled from OECD 2010, 2011b, 2015a

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Box 3. Pushing for breakthrough innovation: The Global Apollo Programme (GAP)

System innovation is a concept used to illustrate a horizontal policy approach that mobilises technology, market mechanisms, regulations and social innovations to solve complex societal problems in a set of interacting or interdependent components that form a whole ‘socio-technical system’. In some ways it is similar to “whole-of-government-policy” approaches that aim to enhance coherence (or in the best case align policies in different domains, see OECD/IEA/NEA/ITF, 2015), but system innovation aims to achieve much more than coherence or policy alignment since it involves actors outside government – notably firms and civil society - and takes a longer term view. System innovation is problem oriented and focused on addressing systemic problems in particular sectors/technology areas.

System innovations are thus defined as radical – insofar as they alter existing system dynamics - innovations in socio-technical systems that fulfil societal functions, entailing changes in both the components and the architecture of systems. They are characterised by three main features: 1) disrupting or complementary types of knowledge and technical capabilities; 2) fundamental changes in consumer practices and markets; and 3) novel types of infrastructures, institutional rules and skill sets. Examples of such systems include an e-mobility urban transport system, a sustainable public housing system, or an e-health care system.

System innovation clearly resonates with the new “challenge-driven” agenda of innovation policy. It does so by (re-) introducing a focus on the “direction” of innovation policies, (oriented towards solving social problems), which differs from the “rate” of innovation, focused increasing R&D investments and the number of innovative firms, products and processes. Source: OECD, 2013 and 2014.

SECTION SUMMARY • Relative improvements in current governance practices and arrangements are required. • Establishing a sound theoretical policy framework is necessary for a new set of policies

and governance practices.

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2. ENABLING GOVERNANCE STRUCTURES TO FACILITATE TRANSITION Systemic changes across the economy are difficult to manage and steer, because these are open, uncertain and complex processes, involving multiple groups and co-evolution between various system elements, many of which are outside the immediate control of policy-makers. If policy-makers face multiple complex socio-technical systems (e.g. the energy system or subsystems of it), with multiple trade-offs and synergies, with various forms of “market and system failures” and, of course, with different costs associated to address those failures– what is the departing point for policy-makers? Or put differently, what are the managers and front-line staff in STI policy making bodies supposed to do and what steps need to be taken when it comes to decision-making considering the role for innovation in reducing environmental pressures?

As mentioned earlier, the government and its respective agents are not all-powerful and all-knowing actors, which can steer innovation by pulling levers from an outside ‘cockpit’ point of view. There are obvious limits in the policy-makers planner’s ability to know enough and to know it early enough to act. Even if complete and timely information were available, identifying policies for proper alignment and initiating change in governance arrangements and practices is not a trivial task.

2.1 PROVIDING VISIONS AND STRATEGIES

Transitions towards more sustainable paths may be impossible to predict, but policy-makers can be strategic about them. Providing orientation and the vision of change is therefore of paramount importance. It helps conceptualise boundaries and provide a common frame of reference for co-ordinated action. The likelihood of success increases when policy-makers at the top of decision-making hierarchies (in government, in firms as well as intellectual and opinion leaders in civil society) adopt it first (OECD, 2014). For example, the Green Growth Strategy already conveyed such a vision to governments and other relevant stakeholders at the highest levels. Similarly, an assessment of mainstreaming practices found that both high-level leadership and providing a clear analytical framework were critical success points for mainstreaming green growth (OECD, 2015b).

There are understandable hesitations about (political) visions, stemming from the fact that they rest on (implicit or explicit) predictions. But creating visions and long-term policy strategies are key instruments. When both credible and sufficiently ambitious, they are found to be important drivers of innovation in their own right, independent from the policy instruments designed to achieve them. For example, the signing of the Kyoto Protocol in 1997 in ratifying countries may have positively affected private actor’s expectations about future returns of “green” innovation as indicated by the post-2000 acceleration of climate-related patents (Dechezleprêtre, et al., 2011)5.

Despite the obvious difficulty for policy-makers, the possible role of policy needs to be considered carefully. Will the system concerned self-organise – through the price-mechanism or by other means – to achieve a timely and effective transition? Would the transition (e.g. in a particular area/sector) entail risks and costs to the system that need to be managed, if possible? Who should be in charge of decision-making? Which goals and objectives (ultimate and direct) should be emphasised? How should corresponding policy instruments be designed? These are hard questions to which the answers

5 The signature of the Kyoto protocol may not be the only factor that changed the development of innovation activities as measured by “green patents”. Other economic reasons might be, for instance, the rise of China and India or the liberalization of the European energy markets, amongst others.

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will depend strongly on context, system boundaries, detail and the level of analysis as well as where the power for change or for status quo lies in the system.

Nonetheless, some strategic choices must be made in allocating scarce public resources, especially where multiple policy objectives co-exist. The process of setting long-term strategic priorities is based on a range of different factors, including value judgments, political opportunities and pressures, questions of efficiency and effectiveness and the available evidence, amongst many others. As a result of these processes, policy priorities in countries for facilitating system-wide changes may yield a range of different policy strategies.

Recent initiatives such as the Dutch Top Sectors approach (see Box 4) demonstrate that this does not have to be exclusively a top-down exercise such as through national innovation or energy strategies. Some initiatives on long-term priority setting use a mixture of top-down and bottom-up inputs, while others are mainly driven by central government [e.g. the development of electric vehicles (EV) industry in China is characterised by a top-down model through the “Plan of Energy-Saving and New Energy Vehicle Industry Development” (2012-2020)]. Ultimately though, the task of bringing this together into a coherent strategic vision, whether through top-down, bottom-up or other mechanisms and initiatives, falls upon governments and its agents.

Being strategic and visionary does not stop with a well-crafted strategic vision or plan. It continues with managing policy instruments, and portfolios of policy instruments with respect to the objectives and system boundaries that have been set, while at the same time acknowledging the need for flexibility in the choice and design of policy instruments.

Box 4. The Netherland’s top sectors approach for innovation in the business sector

Motivated by concerns over international competitiveness and emerging social challenges, the Dutch government announced the top sectors approach in February 2011. This new form of industrial policy focuses public resources on specific sectors and promotes co-ordination of activities in these areas by businesses, government and knowledge institutes. The nine area chosen (which do not correspond exactly to industrial sectors in established classifications) represented strong economic sectors: agri&food, horticulture and propagation materials, high-tech systems and materials, energy, logistics, creative industry, life sciences, chemicals, and water. In 2011 these sectors accounted for over 80% of business R&D and for just under 30% of value added and of employment.

Whereas traditional approaches to industrial policy are government-centred, industry representatives are at the centre of the co-ordination process in the top sectors. For its part government undertakes to develop sector-specific policies across ministerial portfolios, including education, innovation and foreign policy, as well as regulatory burdens. The relevant policy also envisages reducing the administrative burden for businesses, uniting the henceforth disparate channels of public support to businesses with a one-stop shop for service delivery (the so-called Ondernemersplein).

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2.2 POSSIBLE POLICY INSTRUMENTS

The OECD identified different types of policy instruments relevant for innovation and green growth that have been classified into several categories (see Hood, 2011 and on de Serres et al., 2010 for more information). Admittedly, policy instruments can be characterised in several ways, such as their target groups, their goals, their desired outcomes, or the funding mechanism employed. Many of the most popular characterisations are multidimensional and binary in nature6. A popular categorisation among the STI community is supply-side (influencing innovation generation) and demand-side (influencing those requesting, buying or applying innovations) instrument typologies (see OECD, 2012a for more information).

It is important to note that the relationship between policy instruments and innovation (or innovation for the environment, respectively) can be direct or indirect. A direct relationship refers to the situation where policy instruments have been designed with the explicit purpose of positively affecting innovative activities. For example, none of the price-based environmental policies introduced in OECD countries (e.g. subsidies for emissions-reducing activities, emissions trading systems, taxes on CO2) have innovation as their primary goal. They nonetheless constitute the policy environment on top of which more ambitious and direct STI policies for green growth will be introduced. The magnitude of the positive relationship (whether direct or indirect) on innovation for green growth as well as their specific design has been discussed extensively in recent years at the OECD and elsewhere (e.g. OECD, 2011c, 2012, 2014b, Popp et al, 2009, Crespi et al., 2015).

Some might be policy instruments created ex-novo, but rarely are policy instruments ready for the task at hand. Often, policy instruments need to be re-designed, and adapted to the specific problems, and combined with other instruments. Thus, instrument design can change over time according to changing preferences, objectives and technological challenges (see Box 4).

Policy making requires not only a sound basis for intervention but also criteria against which to design policies. The ideal policy instrument will be one which is sufficiently stringent to encourage an optimal level of innovation; stable enough to give investors adequate planning horizons for risky investments; flexible enough to encourage novel solutions; and closely targeted on the policy goal, so as to avoid misallocation of effort and provide incentives for continuous change. An essential set of criteria against which innovation policies aimed at improving environmental performance should be measured includes (Johnstone, Haščič and Kalamova, 2010):

• Stringency – how ambitious is the policy target? • Predictability –what effect does the policy have on investor uncertainty?

6 The number of policy instruments is naturally a consequence of the classification effort one can take.

SECTION SUMMARY • Providing orientation and the vision of change is of paramount importance to

conceptualise boundaries and provide a common frame of reference for co-ordinated action.

• Creating visions and long-term policy strategies are key instruments. When both credible and sufficiently ambitious, they are found to be important drivers of innovation in their own right.

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• Flexibility – whether potential innovators are free to identify the best way to meet the objective?

• Incidence – does the policy target the environmental objective as closely as possible? and • Depth – that is, do incentives exist to innovate through a range of potentially ascending

objectives?

Policy instruments also need to be continuously monitored and evaluated. This learning process can help re-design and adapt instruments to the specificities of the context for intervention. Thus, instrument design can change over time according to changing preferences, objectives and technological challenges (see Box 5).

Box 5. The evolution of the German Feed-in-Tariff (FIT)

The main policy instrument in Germany targeted at fostering the diffusion and development of power generation from renewable energy sources are feed-in tariffs (FIT) which guarantee purchases of green power at fixed prices over longer periods. The FIT has triggered a massive expansion of electricity from renewable energy sources in Germany over the last decade, and has been emulated across OECD and non-OECD countries. However, various empirical studies found mixed results on the cost-efficiency and the inducement effect on innovation of the FIT in Germany (Böhringer et al., 2014 for an overview).

The innovation impacts of renewable promotion policies have been investigated in various empirical studies. For example, Johnstone et al. (2010) examine the effects of environmental policies on technological innovation in renewable energy using panel data across 25 OECD countries and across several technology areas. They conclude that broader market-based regulation such as tradable green certificates are more likely to induce innovation in renewable technologies which are close to competitive, while specific feed-in tariffs are needed to induce innovation in more costly energy technologies such as solar power. Peters et al. (2012) for photovoltaic and Dechezlepretre and Glachant (2013) for wind power respectively show that domestic and foreign demand-pull policies (e.g. production tax credits) in OECD countries trigger innovation within national borders and also create country-level innovation spillovers.

However, while most of the empirical studies consider all demand side policies and thus fall short of differentiating the specific innovation impacts of various demand policies, empirical results by Böhringer et al. (2014) suggest that the German Renewable Energy Sources Act (Erneuerbaren Energien Gesetz - EEG) did not lead to considerable innovative output (as measured by patents). They found insignificant innovation inducement impacts in particular in solar photovoltaic which has received very high feed-in tariffs under the EEG. At the same time, the cost of the feed-in tariff system amounted to roughly 20 billion € in 2013 with the reallocation charge to be paid by electricity consumers rising to more than 6 cents/kWh in 2014, i.e., roughly a fourth of the average household’s consumer price.

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It is rarely the case that a transition can be brought about by a single policy instrument or that transitions are seamless. There are winners and losers from transitions. Most OECD governments have implemented instruments to begin pricing pollution and provide incentives for efficient resource use, such as pricing instruments, regulatory measures and subsidies. For example, all OECD countries, and many non-OECD countries, now use environmentally related taxes (OECD, 2015b). Moreover, OECD countries have implemented STI policies to reduce the cost of the new technology and help bring it to market competitiveness, ranging from firm incentives to engage in “green” innovation and R&D activities, “green” public procurement to thematic funding of basic and applied energy research, amongst others (see OECD, 2014b for an overview). For example, Canada’s Economic Action Plan 2013 has expanded the tax incentives that encourage businesses to invest in clean energy generation and energy efficiency equipment with an accelerated capital cost allowance (CCA) to encourage investment in particular assets or sectors in specific circumstances.

This has resulted in a large increase in complexity for policy-makers, whereby it is common for many policy instruments to co-exist within the same country or region, based on different rationales, corresponding to different policy domains, and targeting different actors. At the same time, governments in OECD countries practice different policy styles and have different policy priorities (e.g. due to a countries´ scientific and economic specialisation), which likely translates into a different composition of policy instrument mixes. For example, a screening of OECD EU member states’ climate policies indicates strong differences among EU countries in terms of policy mixes (Landis et al., 2013; OECD, 2014).

Leaving aside the precise mix of policy and instruments employed to capture this complexity, there seems to be some reoccurring issues raised in policy discussions and circles on the choice and design.

Box 5 (Continued). The evolution of the German Feed-in-Tariff (FIT)

Hoppmann et al. (2014) showed how complex interdependencies and the uncertain nature of technological change shape the process of targeted policy interventions in socio-technical systems. Using the case of the German FIT system for solar photovoltaic (PV) power, they found that the FIT policy has been subject to a considerable number of changes, many of which are the result of policy-makers addressing specific system issues and bottlenecks (e.g. lack of maturity and high cost of PV technology, increasing competition from China). In part, these changes can be explained through characteristics of and factors residing in the political system. Moreover, the decisions to first implement, and then raise and finally remove the ceiling to the maximum cumulative capacity of PV constitutes as a typical case of policy learning as costs were not foreseeable. In the case of the German FIT system for PV such changes were facilitated by the recognition of policy-makers that the instrument had to be re-designed at a frequent basis. Interestingly, however, often policy design changes were driven by unforeseen technological developments induced by previous policy interventions. While policy interventions often contributed to resolving the issues in focus, in many cases technological changes induced by the FIT scheme led to the emergence of new, unexpected issues that policy-makers addressed in subsequent steps.

To cope with such challenges and to address them more effectively, policy-makers implemented a revision cycle which was supported by expert consultations, frequent political negotiations and numerous experience reports commissioned from external authorities. This institutionalisation of policy learning on the side of the policy-makers allowed a continuous evolution and adaptation of the instrument (Hoppmann et al., 2014) (see also Section 2.3 on policy intelligence). For a review of the coupling between environmental and innovation policies in Germany see OECD (2012b).

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These include: instrument co-ordination, timing and sequencing, adequate balancing and the impacts of the interplay of policy instruments (e.g. supply and demand policies), technology-neutrality and the impact on “incremental” and “radical” innovation, amongst others. Opinions and strategies differ as to how to address those issues. To date, there is an inadequate empirical evidence to comprehensively provide practical and actionable recommendations to policy-makers yet beyond anecdotal economic advice and theoretical assumptions.

Therefore, appropriate design and implementation of policy instruments rely on very strong policy intelligence (see Section 2.3) and an adaptive and agile policy governance apparatus (see Section 2.4).

2.3 POLICY INTELLIGENCE

Policy-makers rely on accurate information about emerging technological risks and opportunities, system boundaries, structure, functions and performance of a particular system, and the monitoring of the impact of policy interventions. Furthermore, real-time policy intelligence also matters increasingly for policy-making. For example, the rapid falling of oil and gas prices may undermine public investments in electric and hybrid mobility as they compete directly with rivals such as petrol-fueled cars that are becoming cheaper to run. These may in turn require immediate adjustments or rethink of current policies.

Policy intelligence exercises are very resource intensive and imply a considerable upscaling of current policy intelligence gathering capacities. Though typically associated with quantitative measurement and statistics, policy intelligence can take various forms, depending on the questions policy-makers seek to answer and the stage of the policy cycle (e.g. direction-setting and orientation, policy delivery and/or monitoring and evaluation).

At its simplest form policy intelligence can be seen as the outcome of continuous interaction between policy-makers and actors in the system. Qualitative insights about visions and desirable outcomes, regulatory barriers (e.g. which discourage pollution prevention); interdependencies between technologies, and harmful incentives are of central importance. Those insights can be codified in detailed case studies and statistics, or they can take a more tacit form, resulting from stakeholder/public consultations and network building activities.

A policy intelligence task that is generally underappreciated but seems distinctly necessary for system innovation is that of mapping the system, in a more or less continuous fashion. Discovering the system’s internal organisation and precisely mapping its boundaries can be important in understanding the particular system and identifying potentially profitable missing links with sub-systems and other systems. Doing so may bring into view the bottlenecks that stand in the way of extending the system’s boundaries and facilitating the transition.

Generally, policy intelligence is much more robust and reliable if supported and informed by a shared evidence base and a process of monitoring and evaluation. For example, the set of OECD green patent

SECTION SUMMARY • There exists a wide range of policy instruments to foster innovation for green growth,

which has resulted in a large increase in complexity for policy-makers.

• In order to cope with the complexity, this will require very strong policy intelligence and an adaptive and agile policy governance apparatus.

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indicators7 provides information on the development and diffusion of a wide range of environment-related technologies worldwide. Some OECD countries take a step further, using more intensively new sources of large volumes of data (i.e. “big data”, see Box 6). Evidence and data are key to this process, but as policy makers have a broader view of the evidence-base, insights from firms and expert opinion are also important. New data analytics tools for exploiting big data will also contribute to enhance the evidence base for decision-making.

2.4 CREATING LEARNING AND AGILE GOVERNMENT INSTITUTIONS

The history of innovation indicates that innovation alone does not “drive” history, or the “next green industrial revolution” for that matter. Generating a few bursts of technological advances is one thing, creating a socio-economic system in which sustainable and sustained progress becomes the rule rather than the exception is another. In fact, innovation and technological change will only improve

7 http://www.oecd.org/env/indicators-modelling-outlooks/green-patents.htm; see also Haščič and Migotto (2015)

Box 6. Big data for better STI policy intelligence

The current policy discussion focuses on large volumes of data due to fact that nearly all written (and other) materials are now or soon to be available in a digital format. This simplifies their accessibility, extraction, classification, and analysis. E-government administrative records, proprietary data sources and social media are now potential sources of data for analysis. Even more so, the adoptions of online digital platforms create new and ever-larger data quantities every day. There are remarkable opportunities available as data from initially incompatible sources can be matched and combined in relational databases to examine associations that were previously evasive. While the picture is still evolving in terms of what information and data will be useful, policy interest has been matched by a range of stakeholders who have developed a variety of methods to help navigate policy-makers in a range of important policy spheres. (For more information on big data and innovation see OECD 2015c).

For example, the Defense Advanced Research Projects Agency (DARPA), an agency of the US Department of Defense responsible for the development of emerging technologies for use by the military, in pursuit of potential uses of big data, has for several years applied quantitative tools to analyse patent data, business data and media stories to identify areas of technologies they should be supporting (using software designed by big data start-ups such as Quid). Similarly, TEKES, Finland’s technology funding agency, has been using social network analysis and business records data to understand its technology clusters in order to improve its funding strategy (NESTA, 2015). In addition, the “Future & Emerging Technologies” (FET) initiative funded by the European Commission (EC) and the “Foresight and Understanding from Scientific Exposition” (FUSE) research program funded by the US Intelligence Advanced Research Projects Activities (IARPA) have both aimed to develop methods for the reliable early detection of technology emergence (Rotolo et al., 2015).

SECTION SUMMARY • To govern transitions, policy-makers rely on information and knowledge about emerging

technological risks and opportunities, functions and performance of particular socio-technical systems, and the monitoring of the impact of policy instruments and interventions, amongst many others.

• Policy intelligence is much more robust and reliable if supported and informed by a shared evidence base. Such evidence includes the monitoring and evaluation of policies.

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economic and environmental performance if and when they are accompanied by complementary changes in institutions, governance and ideology (Mokyr, 2002; Acemoglu and Robinson, 2012).

As a point of departure, governments in particular STI policy-making bodies need to become agents of change, leaders in conceptualising a vision and in steering, and facilitating learning across the system. But it is not sufficient to be willing to realise concrete visions of change and place bets on a few emerging technologies. Policy-makers also need to be willing to face controversial issues, including changes in their own existing operational functioning and ask themselves whether their system(s) of governance remain suited for a Green Growth transition. More concretely, they need to rethink or innovate in how they work; in the services they provide and how they provide them; and in how they interact with citizens, businesses and civil society. While there is a growing consensus within and outside government institutions that new ways of working are needed (OECD, 2015c), there is considerable disagreement about how to achieve it.

First of all, it may require relative improvements in a set of (broader and/or administrative) governance capabilities and capacities, including capacities needed for policy development, implementation, learning as well as the engagement of stakeholders (see Box 7). OECD country examples are too numerous to be listed here, but some are already very active in this area for quite some time. For example, Australia, Korea and New Zealand have created joint decision-making modes of governance such as Green Growth committees to improve capacities for coordination and network-building across ministries. A number of OECD countries have also introduced specific mission agencies as a means of improving the overall coherence policy instruments. Chile’s Renewable Energy Centre, the Slovak Republic’s Innovation and Energy Agency, South Africa’s Energy Finance Subsidy Office, Switzerland’s Federal Energy Research Commission and the United Kingdom’s Technology Strategy Board are such examples.

Secondly, government institutions will need to be agile in many areas. They need to be good at brokering cooperation between business and civil society; be ready to take risks and not simply seek consensus; and make use of new techniques for fostering innovation, amongst others (NESTA, 2014).

Box 7. Policy capacity considerations

Policy capacity considerations represent a key function for transitions. Previous OECD research on systemic innovation policy (2005a, b) identifies a number of specific capacities (or “capabilities”) relevant for the promotion of “green” innovation. Given the pervasiveness of innovation and environmental issues across the government, it highlights the importance of establishing mechanisms for horizontal and vertical policy coordination, such as joint task forces or committees and joint programs. Secondly, mechanisms for monitoring and evaluation are considered, not only for the purpose of assessing progress but also as additional coordinating mechanisms. Thirdly, OECD research also suggests the need for “distributed network organisations of strategic intelligence”, which combine different sectoral and stake-holder perspectives as well as pragmatic public-private interfaces to manage transitions in structures and infrastructure.

In addition, mechanisms to facilitate constructive dialog between the governments and relevant stakeholder actors are relevant. Furthermore, the transfer of authority for decision making to other parts of government or outside can have considerable potential to affect the efficiency and effectiveness of policies (e.g. ranging from the complete transfer of executive powers to different organisations to arm’s-length co-ordination on a voluntary and ad hoc basis). Lastly, government and regulatory agencies should also be robust to the actions of vested interests, for example, through accountability mechanisms such as conflict of interest restrictions.

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This may sound intuitive and logical, but in practice it requires both a strong and conducive culture and organisation that encourage in-house public sector innovations as well as civil servants with an entrepreneurial mind-sets and strong capabilities. In addition to contextual factors that create the environment in which civil servants operate, there is some evidence that national differences in how work is organised, the national culture, and organizational conditions can influence how government institutions innovate (Walker, 2006; Arundel et al., 2007). Not surprisingly, research on the sources of ideas and/or the initiators suggests that the majority of public sector innovations in high income countries are proposed by middle managers and front-line staff and not by politicians acting through legislation or political directives (e.g. Borins, 2001; Arundel and Huber, 2013). Such (policy) entrepreneurs (see Box 8) can be also be taken in through flexible staffing systems such as in the case of the US digital services. This programme brings together groups of developers, designer and product leads with civil servants to improve government's services in key areas such as climate change.

Making government institutions more flexible and agile are not new ambitions. Policy-makers across the world are actively considering how to re-engineer policy governance to cope with these complex Green Growth challenges. The OECD Secretariat took important steps in this direction to assists OECD governments to conceptualise the drivers and barriers of public sector innovations (OECD, 2015c) 8 . Nonetheless, these issues highlighted above may help facilitate the discussion that government institutions as crucial actors itself can be part of the solution to enable a transition for green growth, but might be part of the problem too.

Because system innovation takes place in concrete sectors or domains, innovation policy needs be (horizontally) coordinated with sectoral policies (transport, energy, agriculture). In addition to co-ordination, high level political signals will be needed to enhance the legitimacy and visibility of transition initiatives (e.g. reinforcement though broader national environmental policy strategies). There is clearly a need for an adaptive and agile governance system but very few experts actually know how to design one, let alone legislation that permits it.

8 Similar to the private actors, there are a number of drivers as well as barriers to innovate and change, some of which are similar, while others are sector specific.

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Box 8. Who doesn't love policy entrepreneurs?

Policy entrepreneurs influence political processes in a way that alters policies or institutions. They are broadly defined as organisations, individuals or teams who seek to initiate dynamic policy change and are willing to invest their resources—time, energy, reputation, and sometimes money—in the hope of a future return (Kingdon, 1984; Mintrom and Norman, 2009; Perkmann, 2003; Mintrom, 1997). Policy entrepreneurs are said to play an important role in identifying opportunities for new policy initiatives, creating new policy venues and framing policy debates, mobilising and linking interests, forging coalitions and making others learn in the process (Doig and Hargrove, 1987; Roberts, 1992; Mintrom and Norman, 2009; Cohen and Noll, 1991; Mintrom, 1997; Cohen, 2012). Their key functions thus relate to the process of agenda setting, policy formulation and decision making, less so to the implementation of policy.

Mintrom and Norman (2009) identify key characteristics of policy entrepreneurs: (a) social acuity, or perceptiveness, in understanding others and engaging in policy conversations and in being able to recognise windows of opportunity; (b) defining problems: the way a policy problem is defined determines how actors perceive their own interests and how they rate solutions that are presented to them. Policy entrepreneurs influence the problem definition by providing a changed narrative and/or new evidence, highlighting the importance of a specific issue and the failure of existing policies; (c) building teams: individual actors within organisations understand that they need support from a range of actors, both within and outside their own organisation. As Meier (1995) and Roberts and King (1996) have shown, successful policy entrepreneurs often work in teams with different skill sets, knowledge and network connections; (d) leading by example: policy entrepreneurs are more credible if they practice what they preach, i.e. if they act in line with the policy change idea they promote.

Rabe (2004) documented the emergence of policy entrepreneurs (several state governors and their advisors) who proposed new approaches to environmental policy at the state level in the United States. They used their specialised knowledge of policy processes and governmental systems to significant advantage, worked carefully over time to craft strategic coalitions of supporters and were then able to discern windows of opportunities for policy action when they emerged. Source: Compiled from Edler and James, 2015; Rabe, 2004

SECTION SUMMARY • Innovation and technological change will only improve economic and environmental

performance if and when they are accompanied by complementary changes in institutions, governance and ideology.

• Governments in particular STI policy-making bodies need to become agents of change, leaders in conceptualising a vision and in steering, and facilitating learning across the system.

• Government institutions will need to be agile in many areas. They need to be good at brokering co-operation between business and civil society; be ready to take risks and not simply seek consensus; and make use of new techniques for fostering innovation.

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3. RESEARCH GAPS, PRIORITIES FOR FUTURE RESEARCH AND QUESTIONS FOR DISCUSSION Governments are today, perhaps more than ever before, under pressure to base their intervention and legislation on evidence. As such, they are badly in need of resilient data, empirical evidence and narratives explaining and supporting their decisions in increasingly complex, multidimensional and interrelated settings as in the case of the Green Growth challenge.

Over the past few years, there has been much discussion about how we can improve the use of evidence, novel datasets and policy-frameworks in STI policy decision-making. The knowledge and evidence proved to be highly relevant to frame policy discussions, understand some of the dynamics of innovation in all its forms and abstract from highly complex real-world situations. However, there are still major research (or knowledge) gaps into green growth and innovation, in particular as regards from the viewpoint of a policy practitioner.

#1 Develop mechanisms and tools to identify emergent technologies relevant for green growth [see the issues paper for Session 2: Emerging Technologies & Firm Dynamics: Implications for Green Growth].

A lot of STI policy for green growth involves the government trying to support new technologies. A key question is whether governments should support existing technologies (e.g. hydro, wind, solar) or whether they should support more radical innovations, many of which are embryonic and not yet cost-effective. Yet, radical innovations involve a lot of trial and error and a lot of investment goes into projects that often do not succeed. The question is important because governments have limited information on the potential of new technologies or the market and second, there is today greater urgency for innovations for sustainability. In contrast, industry is good at identifying problems with existing technologies and can improve upon them. Consequently, a lot of government support goes to research and demonstration for existing technologies. This support can take the form of sectoral R&D support and market creation support (e.g. subsidies, pricing, public procurement).

In addition, while policy-makers often express support for technology-neutral policies, technology-specific policies are often implemented. Therefore the debate should address the issue of how specific technology support policies should be and how investments should be distributed among different technology/research areas relevant for green growth (Azar and Sandén, 2011).

Future research should explore the factors that enable certain technologies to emerge while others remain on the shelves of government or corporate labs. Recent research at the OECD and in academia is exploring the role of various tools (e.g. horizon scanning, green technology forecasts and patent and bibliometric statistics) in understanding how technologies emerge [see Dernis et. al. (2015) and Egli et al. (2015)]. Still, more work is needed to combine and link different methods and data to get a more reliable, timely and complete picture. Equally important is research on the diffusion and adaption of new technologies, including the role of societal groups. The issue of better measurement of technology diffusion has emerged as an important policy issue in the context of the OECD discussion on the future of productivity. Indeed, there is perception that many of the productivity benefits of key technologies are held back due to barriers to diffusion and market entry of new innovative firms or due to biases that favour incumbents.

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Questions for discussion:

• Governments are not able to determine with any accuracy where innovations will come from, but they still need to make choices to allocate public support to R&D and innovation. What knowledge, evidence and/or novel data would prove valuable to increase the likelihood of identifying areas for public investment to support technologies for green growth?

• Can incremental improvements in green technologies and innovations happen without government funding?

• Policy-makers need to be ready to discontinue initiatives that are not working, or to modify incentives as new technologies grow and mature. What lessons have been learned on this issue?

#2 Diversify the sources of evidence to policy-makers

The complexity of innovation warrants not only interaction within science disciplines but also closer collaboration with groups that have studied systemic approaches to innovation, technology and policy from different points of view. For example, little information is available on non-technological innovation, such as changes in business models, work patterns, city planning or transport arrangements that are also instrumental in driving a transition to green growth (OECD, 2014c). From the policy perspective, there is little practical evidence how STI policy for green growth has actually been designed and implemented and which social forces have governed these activities. A larger question that may be also asked is whether all policy instruments designs can be equally utilised by OECD and developing countries as certain policy instruments require a high level of capabilities (e.g. selection of R&D proposals, administration issues, collaboration with stakeholders, etc.).

While there have been conceptual advances stemming from inter-disciplinarily collaboration, for example, in understanding the significance of systemic innovation approaches to policy (e.g. through the ongoing OECD Systems Innovation project), future research into topics as diverse as behavioural change, engineering constraints and opportunities, user and customer practices, the foundations of production and consumption, participatory governance mechanisms, the political economy of STI policy-making, amongst many others, may bear fruit in terms of providing practical and actionable policy advice. Studying innovation and STI policy in a historical perspective should also contribute to an improved understanding of Green Growth issues.

Questions for discussion:

• During the past decades many scholars have analysed the complex processes of innovation in their wider economic, political and social context. What particular research perspectives and/or views with regards to Green Growth have been neglected by policy-makers in their decision-making process?

• If any, what might be the reasons for it?

#3 Make research more relevant to the needs of policy-makers

Although there is a need for an upscaling in current policy intelligence gathering capabilities (e.g. #1 and #2), but just as often the priority is to ensure that the evidence and data being collected and analysed is made relevant and practicable to the needs of policy-makers. It even appears that limitations exists on how useful some of these policy recommendations, either coming out of impact evaluations or empirical studies, can be useful to policy middle managers and front-line staff dealing

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with innovation and environmental issues. Furthermore, governments have very little effective information about the policy that the government itself makes to influence innovation; meaning they are less effective at identifying causal policy outcomes (such as the effect of a particular instrument on innovation). In particular, many government-sponsored impact evaluations that look at outcomes do not use credible strategies to assess the causal impact of policy interventions. But the quality and breadth of these assumptions is crucial to making sound policy-decisions.

These gaps highlight the need for greater experimentation, with a shared fact base and more credible evaluations to be embedded in policy design, and thinking differently about the policy cycle as a whole. What is needed, therefore, is a more realistic appraisal of what policy intelligence in all its forms can do to the understanding of real-life problems and dilemmas for STI policy-makers.

Future research into STI policy should be thus shaped by the problems of practitioners and not only a theoretical framework for understanding innovation. This will require the interaction of theory, data, and policy in order to reduce the knowledge gap between theory and policy practicability. Another challenge is to integrate and synthesise the available knowledge and evidence from different streams of policy research (including from outside the technology and innovation field). This essentially involves narrowing the topic down to ensure it is manageable, and using strict criteria to ensure that only the highest quality evidence is included in systemic reviews. For example, the Maryland Scientific Methods Scale (a scale to evaluate the methodological quality of studies) could be utilized in many ways to help improve the significance of impact evaluations relevant for Green Growth and innovation.

Questions for discussion:

• The current debate on the role of the government in fostering green growth has reached an inflection point on the eve of the COP21 discussions. There is consensus on the need to reduce emissions, but there are many ways to go about this. How can policy learning from different domains - environment, innovation and industry policy- be combined to better inform policy choices?

• What precise information would be required to support policy-makers in their decision making, in particular for front-line staff in designing and managing STI policy instruments that take a system approach to achieve green growth?

#4 Digitisation of innovation for green growth [see also Session 3: The Role of New Data Sources in Greening Growth].

The digital revolution is enabling the greening of production and consumption. And because of the ubiquity of ICTs networks and platforms, systemic eco-innovation can be accelerated: smart and interconnected devises enable the reduction of carbon emissions in real time across entire value chains. Governments play a role in not only removing barriers to digitisation but also enabling it through open data and open science policies that promote public access by firms and consumers to data that could be used to develop new innovative solutions to sustainability challenges. Indeed, also the private sector accounts for most of the data infrastructure, the government owns a large share of it in the form of scientific data and socio-economic data. Future research in this area could examine in more detail the innovation policies that could accelerate the contribution of digitisation to green growth in a more systematic manner.

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Questions for discussion:

• What type of government data could support improved policy-making for Green Growth and innovation?

• If any, what are potential bottlenecks and/or challenges in providing reliable and understandable open government data in the context of Green Growth?

#5 Public innovation should play a prominent role in future research agendas

If governments are serious about a Green Growth transition, change necessarily needs to start with government institutions themselves. Therefore, there is no specific reason why public innovation should not be a central part in future research agendas. The OECD has made already valuable contributions collecting case studies but little empirical research has been conducted to understand drivers and barriers of public sector innovation (e.g. managerial and staff involvement in public innovation). There is a need now to go further to identify the organisational models and human resource policies that can foster public sector innovation and serve as a reference point for public sector reform.

Questions for discussion:

• There is growing understanding that government institutions are actors on their own and their degree of autonomy can be highly variable from case to case. What are the key factors that enable these actors to innovate?

• With regards to green growth, what specific “green” public innovations would be needed?

#6 Bottom-up and decentralisation approaches should play a central role in systemic policies for innovation

The central narrative of a systems perspective on innovation involves viewing the socio-economic system as a complex evolving system—beyond strict control of government and its agents. As a matter of fact, we don’t understand the complex evolving socio-economic system, and probably will never be able to understand it. As such, system innovation sees the social-economic system as complex and adaptive, developing multiple (endogenous) control mechanisms that make it work, and which are continually evolving over time. Government is just one component of those control mechanisms. While governments and its agents cannot control innovations within complex socio-economic systems (with characteristics of path dependencies, nonlinearities, and lock-ins), they can influence its development in a myriad of ways.

In general, governments and its agents should encourage the development of an institutional environment that is conducive to bottom-up and decentralized solutions. Much will depend on the success of a large variety of experiments with bottom-up government to create a structure conducive to allow firms, individuals and other non-governmental stakeholders in the institutional space to self-organize in new ways to solve environmental problems through trial and (small) error discovery and constant “tinkering”.

However, in many ways the greater the amount of direct top-down government intervention on innovation, the less successful a particular system has been in getting the bottom-up structure right. The problem with having the top-down government try to solve coordination problems is that it often does so in ways that undermine and suppresses creative forces that lead to innovation. Therefore, if

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national governments are to play this role effectively, it will require major governmental institutional changes (see #4).

Future research could look at all sorts of research questions relevant to system innovation. For example, policy research could investigate bottom-up decentralized approaches to innovation strategies or decentralized decision-making for innovation as a way to discover what works and what does not. Large and innovation-active companies in fast-pace innovation environments have for some time now looked at how decentralization generates experimentation. There is a similar role for governments to play. In the same vein, there is a growing recognition that there is a deep and implicit link between system change and the actions of civil society organisations (CSOs) at local levels. For example, a number of new models have emerged through which voluntary participants have been able to leverage their purchasing power or work together to lower costs and increase access to renewable energy such as community-owned windfarms and biofuel projects. Thus, research into voluntary civil society initiatives may lead to valuable insights.

Questions for discussion:

• How can policy makers and private actors learn from policy experience? How can such learning processes be organized and embedded and institutionalised in the policy-making process.

• How can such learning processes help lower resistance to change among stakeholders in order to enable system-level change?

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