1. Underinvestment: The Energy Technology and R&D Policy Challenge
2. Induced Innovation and Energy Prices
3. The impact of R&D on innovation for wind energy in Denmark, Germany and the United Kingdom
4. Innovation in the energy sector: Lessons learnt from R&D expenditures and patents in selected IEA countries
5. Technological innovation in the energy sector: R&D, deployment, and learning-by-doing
6. R&D drivers and obstacles to innovation in the energy industry
7. Why and how to subsidise energy R+D: Lessons from the collapse and recovery of electricity innovation in the UK
8. Missions-oriented RD&D institutions in energy between 2000 and 2010: A comparative analysis of China, the United Kingdom, and the United States
9. Decision frameworks and the investment in R&D
10. A portfolio decision analysis approach to support energy research and development resource allocation
Robert M. Margolis (Princeton University)
Daniel M. Kammen (University of California, Berkeley)
This Viewpoint examines data on international trends in energy research and development (R&D) funding, patterns of U.S. energy technology patents and R&D funding, and U.S. R&D intensities across selected sectors. The data present a disturbing picture: (i) Energy technology funding levels have declined significantly during the past two decades throughout the industrial world; (ii) U.S. R&D spending and patents, both overall and in the energy sector, have been highly correlated during the past two decades; and (iii) the R&D intensity of the U.S. energy sector is extremely low. It is argued that recent cutbacks in energy R&D are likely to reduce the capacity of the energy sector to innovate. The trends are particularly troubling given the need for increased international capacity to respond to emerging risks such as global climate change.
American Economic Review (2002)
David Popp (Syracuse University)
I use U.S. patent data from 1970 to 1994 to estimate the effect of energy prices on energy-efficient innovations. Using patent citations to construct a measure of the usefulness of the existing base of scientific knowledge, I consider the effect of both demand-side factors, which spur innovative activity by increasing the value of new innovations, and supply-side factors, such as scientific advancements that make new innovations possible. I find that both energy prices and the quality of existing knowledge have strongly significant positive effects on innovation. Furthermore, I show that omitting the quality of knowledge adversely affects the estimation results.
Ecological Economics (2005)
Ger Klaassen (International Institute for Applied Systems Analysis (IIASA))
Asami Miketa (International Institute for Applied Systems Analysis (IIASA))
Katarina Larsen (Royal Institute of Technology)
Thomas Sundqvist (Swedish Energy Agency)
This paper examines the impact of public research and development (R&D) support on cost reducing innovation for wind turbine farms in Denmark, Germany and the United Kingdom (UK). First we survey the literature in this field. The literature indicates that in Denmark R&D policy has been more successful than in Germany or the UK in promoting innovation of wind turbines. Furthermore, such studies point out that (subsidy-induced) capacity expansions were more effective in the UK and Denmark in promoting cost-reducing innovation than in Germany. The second part of the paper describes the quantitative analysis of the impact of R&D and capacity expansion on innovation. This is calculated using the two-factor learning curve (2FLC) model, in which investment cost reductions are explained by cumulative capacity and the R&D based knowledge stock. Time-series data were collected for the three countries and organized as a panel data set. The parameters of the 2FLC model were estimated, focusing on the homogeneity and heterogeneity of the parameters across countries. We arrived at robust estimations of a learning-by-doing rate of 5.4% and a learning-by-searching rate of 12.6%. The analysis underlines the homogeneity of the learning parameters, enhancing the validity of the 2FLC formulation.
Energy Policy (2014)
Raphael Bointner (Vienna University of Technology)
Long time series of the IEA and international patent offices offer a huge potential for scientific investigations of the energy innovation process. Thus, this paper deals with a broad literature review on innovation drivers and barriers, and an analysis of the knowledge induced by public research and development expenditures (R&D) and patents in the energy sector. The cumulative knowledge stock induced by public R&D expenditures in 14 investigated IEA-countries is 102.3 bn EUR in 2013. Nuclear energy has the largest share of 43.9 bn EUR, followed by energy efficiency accounting for 14.9 bn EUR, fossil fuels with 13.5 bn EUR, and renewable energy with 12.1 bn EUR. A regression analysis indicates a linear relation between the GDP and the cumulative knowledge, with each billion EUR of GDP leading to an additional knowledge of 3.1 mil EUR. However, linearity is not given for single energy technologies. Further, the results show that appropriate public R&D funding for research and development associated with a subsequent promotion of the market diffusion of a niche technology may lead to a breakthrough of the respective technology.
Energy Policy (2006)
Ambuj D.Sagar (Harvard University)
Bobvan der Zwaan (Harvard University & Energy research Centre of the Netherlands)
Technological innovation is fundamental for rendering the energy economy cleaner and more efficient with concomitant economic, developmental, and environmental benefits. This paper discusses aspects of R&D and ‘learning-by-doing,’ the main contributors to technological change that are complementary yet inter-linked. The relationship between the level of national energy R&D investments and changes in the trajectory of the country's energy system is complex; targeted efforts to promote deployment of new energy technologies play a major role in translating the results of R&D activities to changes in the energy system. Learning-by-doing is an important element of deployment, but it remains largely poorly understood. Hence this phenomenon needs to be ‘unpacked’ and its various aspects analyzed in detail, so as to allow better design of early deployment efforts to enhance learning gains. This paper highlights how public R&D and deployment efforts must work in tandem to expand the portfolio, and realize the potential, of new and improved energy technologies.
Energy Economics (2014)
M.T. Costa-Campi (University of Barcelona)
N. Duch-Brown (University of Barcelona & European Commission)
J. García-Quevedo (University of Barcelona)
The energy industry is facing substantial challenges that require the fostering of innovation. In this paper we analyse the main drivers of R&D investment and obstacles to innovation in this industry. We examine, firstly, whether the stated R&D objectives pursued by firms play a role in their R&D effort. Secondly, we analyse the effects of financial, knowledge and market barriers on the innovation outcomes of the firms. The data is taken from the Technological Innovation Panel (PITEC) for Spanish firms for the period 2004–2010. We use a structural model with three equations corresponding to the decision to carry out R&D or not, the R&D effort, and the production of innovations. The results of the econometric estimations show, first, that R&D intensity is positively related to process innovation. Second, the main barriers that hamper innovation in the energy industry are related to market factors while financial and knowledge obstacles are not significant.
Energy Policy (2015)
Tooraj Jamasb (Durham University Business School)
Michael G. Pollitt (Cambridge Judge Business School)
The UK electricity sector liberalisation was a pioneer in the worldwide reform trend and its reform model and outcomes have been the subject of many studies. However, lesser known are the effects of privatisation, market based reforms, and incentive regulation of networks on research and development as well as patenting activities in the sector. This paper updates our previous studies of this subject and discusses the recent developments in the innovative activities in the UK electricity sector. We find that, in recent years, the initial absence of support policies and the subsequent decline in innovation efforts in the aftermath of the reform has resulted in efforts towards forming an energy technology and innovation policy. Although we already observe some positive outcomes from these efforts, we discuss whether the balance of the innovation efforts are calibrated appropriately and whether the institutional framework can be further improved to promote long term progress.
Research Policy (2012)
Laura DíazAnadón (Harvard University)
In the first decade of the 21st century, governments in many countries around the world expanded or redesigned their support for the development and deployment of advanced energy-supply and energy-demand technologies. By analyzing the institutions that have been created to stimulate energy technology innovation in the United States, the United Kingdom, and China-three countries with very different sizes, political systems and cultures, natural resources, and histories of involvement in the energy sector-this paper highlights how variations in national objectives and industrial and political environments have translated into variations in policy. The analysis shows that the countries’ activities differ in terms of three general elements: whether the government's various activities are coordinated or autonomous, whether the business community is significantly involved in the design and running of the initiatives, and whether the implementing institutions focus on single or multiple missions and innovation types. These differences constitute different types of governments’ attempts to activate the state-industry innovation complex. The paper concludes with a discussion of the trade-offs involved in the design of systems for public support of energy RD&D, points to possible gaps in the government approaches to support energy RD&D, and highlights areas of future research.
Energy Policy (2015)
Erin Baker (University of Massachusetts)
Olaitan Olaleye (University of Massachusetts)
Lara Aleluia Reis (Fondazione Eni Enrico Mattei (FEEM))
In this paper we provide an overview of decision frameworks aimed at crafting an energy technology Research & Development portfolio, based on the results of three large expert elicitation studies and a large scale energy-economic model. We introduce importance sampling as a technique for integrating elicitation data and large IAMs into decision making under uncertainty models. We show that it is important to include both parts of this equation – the prospects for technological advancement and the interactions of the technologies in and with the economy. We find that investment in energy technology R&D is important even in the absence of climate policy. We illustrate the value of considering dynamic two-stage sequential decision models under uncertainty for identifying alternatives with option value. Finally, we consider two frameworks that incorporate ambiguity aversion. We suggest that these results may be best used to guide future research aimed at improving the set of elicitation data.
Energy Policy (2017)
Margaret Kurth (US Army Corps of Engineers)
Jeffrey M. Keisler (University of Massachusetts Boston)
Matthew E. Bates (US Army Corps of Engineers)
Todd S. Bridges (US Army Corps of Engineers)
Jeffrey Summers (US Department of Energy)
Igor Linkov (US Army Corps of Engineers)
Research sponsored by the US Department of Energy (DOE) aims to facilitate a clean and independent energy future for the nation. Strategic planning for energy research and development (R&D) can be complex and dynamic, in part due to federal budgetary constraints and volatility. Managing R&D funding to advance energy technologies, in spite of these challenges, is a crucial component of the nation's long term energy policy. This study demonstrates a portfolio decision analysis (PDA) approach to support R&D resource allocation decisions for the DOE Office of Fossil Energy's Carbon Capture and Storage R&D program. A multi-attribute value model uses technology readiness levels (TRLs) and other metrics to represent the overall objectives of the R&D program in order to evaluate alternative research portfolios given limited funding. Mathematical optimization identifies efficient funding allocations for each technology program area to maximize the multi-attribute value generated from the total budget. This is especially useful for responding to externally imposed budget changes. As the case study demonstrates, explicitly funding the most value-generating options leads to greater expected R&D programmatic value than typical strategies of equal or proportional distributions of a budget change among technology program areas.
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