The interest for innovation and diffusion of energy technologies arises from the fact that technological advances in these fields can potentially reduce the costs of complying with a stringent climate change policy. Designing successful policies to promote innovation requires, however, a thorough understanding of innovation dynamics and drivers. This is true both for technologies that reduce or eliminate greenhouse gases (and thus address the climate change challenge) and for any other innovation.
The relative importance of different determinants of innovation – such as geographical location, technological specialization and level of economic development – has been addressed in the general innovation literature, while contributions focusing on energy and climate innovation are much more limited in number and scope. These research efforts are important because energy and environmental technologies might have different dynamics and drivers than the “average” innovation.
Clarifying this point and providing a complete picture in this respect is, however, far from easy. Some of the challenges faced by researchers in this area were also faced by those studying general innovation. As a result, environmental and energy researchers can “stand on the shoulders of the giants” since they can learn from past experiences and methodologies.
The use of patent data as proxy for innovation is one of these cases. There are two major sources of patent data. The NBER Patent Statistics Database includes all patents granted to both US and foreign innovators by the United States Patent and Trademark Office (USPTO) since the mid-1960s. The EPO/OECD PATSTAT Database, on the other hand, includes patents granted by more than 80 patenting authorities worldwide.
Environmental economists have improved on the previous literature by selecting patents specifically addressing energy efficiency or emission reductions. A number of research groups are currently working on these issues. Joint effort by the OECD and FEEM resulted in the selection of patents for fossil fuel electricity production technologies. Energy and environment-related patents has acquired so much relevance that the European Patent Office has recently included an ad hoc patent class (Y2 class) in the European Patent Classification (ECLA) to specifically tag these technologies.
The results of such efforts are twofold. On the one hand, research can be carried out specifically with respect to energy and the environment, and the peculiarities of innovation dynamics in this field can be uncovered. On the other hand, the large availability of patent data allows extending the research beyond IEA and OECD member states. This is particularly important for a number of reasons. First, fast developing countries are becoming leading innovators in a number of technologies (as for example Brazil with respect to biofuels). Second, the extent to which a new technology will impact emission reductions depends on the ability of the receiving countries to absorb it and to adapt it to local needs. In this respect, the dynamics of technology diffusion and “adaptation” in developing countries has become one of the major areas of interest.
In addition to the typical difficulties of innovation studies, environmental economics researchers face challenges of their own. Unlike the general innovation literature, they cannot directly study the dynamics of energy-specific R&D investments due to scarce availability of data. While it is possible to retrieve information on R&D investments for a number of countries, only few sources specifically distinguish between energy and non energy-related innovation activities. Those sources focus mainly on government-sponsored energy R&D. No database exists which contains both private and public investment focused on energy efficiency or climate-friendly technologies.
These shortcomings significantly limit the possibility to explore important issues such as the crowding-out between public and private (or energy and non energy) R&D. An important question yet to be answered is whether increases in R&D investment of the public sector simply “crowd-out”, i.e. displace, investments by the private sector. A similar question is whether increases in energy-related/climate-friendly research lead to a reduction of innovation in other sectors and areas.
Data availability for the USA is slightly better than for the rest of the world. Popp and Newell (2009) exploit R&D data for different (energy-intensive and non energy-intensive) sectors of the economy and empirically test the hypothesis of crowding-out between energy and non energy R&D investments. They find some evidence of crowding-out (at the sectoral level) in sectors active in energy R&D, but not in other sectors. This seems to suggest that funds for energy R&D do not come at the expense of R&D from other sectors, but from a redistribution of research funds in sectors performing energy R&D. However, as the authors themselves acknowledge, the robustness of these results is limited by the high level of data aggregation and the lack of long time series, which make these conclusions far from solid.
Answering such questions and, if crowding-out occurs, understanding the magnitude of these displacements is paramount. This is the only possible way to assess whether R&D subsidies and investment by the public sector achieve the intended effect.
One of the very few efforts to provide a picture of private R&D investment is the 2009 Report “R&D Investment in the Priority Technologies of the European Strategic Energy Technology Plan”, prepared by the Institute for Prospective Technological Studies (IPTS) of the European Commission’s Joint Research Centre (JRC). This report offers a benchmark of the environmentally friendly R&D spending in 2007 by estimating the magnitude of R&D investments by companies with headquarters registered in the EU. The report focuses on the Priority Technologies of the European Strategic Energy Technology Plan (SET-Plan), namely wind and solar technologies, carbon dioxide capture and storage (CCS), biofuels, hydrogen and fuel cells, smart grids, nuclear fission and fusion. The report shows that private spending in these fields is higher than that of public sources. These results confirm the relevance of questions about “crowding-out” of private and public spending.
The importance of energy innovation dynamics has also been acknowledged in the fourth wave of the Community Innovation Survey (2002-2004), which includes a question on the environmental impact of innovation. While the inclusion of this question demonstrates the increased relevance of environmental issues, a long way is still ahead of us before being able to obtain good quality data on this issue. The CIS is not specifically designed to explore eco-innovations. Moreover, the data collected takes into account only the “perceived” environmental impact of a given innovation. This might be very different from the real impact, because of respondents’ bias or lack of appropriate knowledge.
While some effort has been spent so far in order to overcome the lack of data, availability still remains a concern for all researchers involved in studying energy innovation. A number of research groups around Europe and the world are willing to take these improvements further, including our team of ICARUS researchers. To this end, we are gathering data on both patents and private R&D. With respect to private R&D investment, we are planning the design of an Energy Innovation Survey that will specifically address the above-mentioned issues. . In the initial phase, we will administer the Survey to selected innovating firms and entities in technological fields of high interest for the project, such as firms active in the renewable sector and in fossil fuel extraction and transformation. We hope this effort will succeed in constituting the basis for a more organized and continuous collection of data with respect to innovation and the environment. Such intense activity will surely lead to better conclusions about innovation and diffusion dynamics in energy technologies, with important implications for policy makers.
References
- Hall, B. H., A. B. Jaffe, and M. Trajtenberg (2001). The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools. NBER Working Paper 8498.
- EPO/OECD PATSTAT Database (2009)
- European Commission (2009), ‘R&D Investment in the Priority Technologies of the European Strategic Energy Technology Plan’, prepared by the Institute for Prospective Technological Studies (IPTS) of the European Commission’s Joint Research Centre (JRC), SEC (2009) 1296.
- Popp, D. and R. Newell (2009), ‘Where Does Energy R&D Come From? A First Look at Crowding Out from Environmentally-Friendly R&D’, October 2009, NBER Working Paper 15423
