Impact assessment of emissions stabilization scenarios with and without induced technological change

The main aim of this paper is to investigate quantitatively the economic impacts of emissions stabilization scenarios with and without the inclusion of induced technological change (ITC). Improved technological innovations are triggered by increased research and development (R&D) expenditures that advance energy efficiencies. Model results show that ITCs due to increased investment in R&D reduce compliance costs. Although R&D expenditures compete with other investment expenditures, we find that increased R&D expenditures improve energy efficiency, which substantially lowers abatement costs. Without the inclusion of ITC, emissions targets are primarily reached by declines in production, resulting in overall welfare reductions. With the inclusion of ITCs, emissions mitigation can result in fewer production and GDP drawbacks.     

R&D investment strategy for climate change

The economic costs of stabilizing greenhouse gas concentrations over the coming century depend critically on the development of new technologies in the energy sector. Our research and development (R&D) investment strategy is the control variable for technology availability. This paper proposes an analytic framework for determining optimal R&D investment allocation and presents some numerical results to demonstrate the implementation of the methodology. The value of technological advance in three targeted areas–fossil-based generation, renewables, and carbon capture and storage–is represented by the increase in expected welfare in the presence of an emissions policy constraint of initially uncertain stringency. R&D expenditure increases the probability of advance. Optimal investment is determined by its relationship with success probability, which is assumed to exhibit decreasing returns to scale, relative to the value of success. While the numerical results are speculative, the paper offers insights into the nature of an optimal technology strategy for addressing climate change.     

Uncertainty modeling of CCS investment strategy in China’s power sector

The increasing pressure resulting from the need for CO₂ mitigation is in conflict with the predominance of coal in China’s energy structure. A possible solution to this tension between climate change and fossil fuel consumption fact could be the introduction of the carbon capture and storage (CCS) technology. However, high cost and other problems give rise to great uncertainty in R&D and popularization of carbon capture technology. This paper presents a real options model incorporating policy uncertainty described by carbon price scenarios (including stochasticity), allowing for possible technological change. This model is further used to determine the best strategy for investing in CCS technology in an uncertain environment in China and the effect of climate policy on the decision-making process of investment into carbon-saving technologies.     

Development of an Energy‐Economic Model with Endogenous Technological Progress and Feasibility Study of CCS Systems

The main objective of this research is to develop a bottom‐up energy‐economic model considering endogenous technological development. The designed model analyzes the feasibility of CCS technologies in the Japanese electricity market to derive an optimum carbon reduction scenario. Two factors, a learning curve based on learning‐by‐doing and public R&D investment, precede technological progress. The analysis is calculated with a set of scenarios, which is based on alternative assumptions for technological characteristics: chemical and physical carbon absorptive technology. From modeling estimation, we conclude that technological progress reduces the generation costs of conversion technologies with CCS, as a CCS system acquires an additional unit of installation. Generation cost with chemical absorption remarkably reduces its marginal unit cost through a learning mechanism. The supply fraction from a gas‐fired power plant increases over the analytical time period. The introduction of CCS reduces carbon emission level 17% compared to the baseline scenario in 2050. Technological progress has little impact on the total system costs; however, learning‐by‐doing pushes the introduction of CCS into the market rather than into a R&D activity. Research and development efforts in the private sector or knowledge spillover are not modeled in the study; however, they have the potential to contribute to the mitigation of carbon emission as well. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res, 43(4): 332–351, 2014; Published online 3 October 2013 in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.21078     

Cournot competition and “green” innovation: An inverted-U relationship

We examine the relationship between competition and innovation in an industry where production is polluting and R&D has the aim to reduce emissions (“green” innovation). We present an n-firm oligopoly where firms compete in quantities and decide their investment in “green” R&D. We analyse the case where the emission tax is set endogenously by a committed regulator and uncover an inverted-U relationship between innovation and competition that is mainly driven by the presence of R&D spillovers.     

Uncertain R&D,backstop technology and GHGs stabilization

This paper analyses optimal investments in innovation when dealing with a stringent climate target and with the uncertain effectiveness of R&D. The innovation needed to achieve the deep cut in emissions is modeled by a backstop carbon-free technology whose cost depends on R&D investments. To better represent the process of technological progress, we assume that R&D effectiveness is uncertain. By means of a simple analytical model, we show how accounting for the uncertainty that characterizes technological advancement yields higher investments in innovation and lower policy costs. We then confirm the results via a numerical analysis performed with a stochastic version of WITCH, an energy–economy–climate model. The results stress the importance of a correct specification of the technological change process in economy–climate models.     

Decision frameworks and the investment in R&D

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.     

Measuring the value of induced technological change

In this paper, we analyze the value of induced technological change (ITC) for cutting the costs of reaching climate stabilization targets using techniques from the tax burden literature. First, ITC is valuable as it increases the elasticity of emissions with respect to carbon prices, and thereby it decreases the burden associated with an enforced emission reduction. Second, under ITC, emission abatement may generate a positive learning dividend when the social value of the induced change in learning exceeds its costs. We discuss under which assumptions we expect ITC to turn out a valuable feature, or not. We also carry out a numerical analysis with two models, one focusing on energy savings, the other focusing on energy transition. The models suggest that both the decreased carbon tax burden and the learning dividend gain can be substantial, compared to the costs of abatement without ITC.     

The case for a new energy research,development and promotion policy for the UK

This paper is a critical assessment of the current balance of efforts towards energy research and development (R&D) and the promotion of low-carbon electricity technologies in the UK. We review the UK's main technological options and their estimated cost ranges in the medium term. We contrast the energy R&D spending with the current and expected future cost of renewable promotion policies and point out the high cost of carbon saving through existing renewable promotion arrangements. We also note that liberalisation of the electricity sector has had significant implications for the landscape of energy R&D in the UK. We argue that there is a need for reappraisal of the soundness and balance of the energy R&D and renewable capacity deployment efforts towards new energy technologies. We suggest that the cost-effectiveness of UK deployment policies needs to be more closely analysed as associated costs are non-trivial and expected to rise. We also make a case for considering increasing the current low level of energy R&D expenditure. Much of energy R&D is a public good and we should consider whether the current organisation of R&D effort is fit for purpose. We argue that it is important to build and maintain the research capability in the UK in order to absorb spillovers of technological progress elsewhere in the world. Against this background, the recent signs that an energy R&D renaissance could be underway are therefore positive and welcome.     

In-depth analysis on R&D investment and strategy on PV in South Korea

Photovoltaics (PV) is an eco-friendly and green technology, as a renewable energy source, with the aim of minimizing carbon dioxide emission into the atmosphere. The Korean government has financed various domestic installations as well as research and development (R&D) programs to enter and develop a lead in the worldwide PV market. In this study, R&D investments in the area of PV are analyzed in terms of the respective ministry, performer, research characteristics, PV materials and output levels in detail. The Korean government in the Fiscal year (FY) 2010 provided $178 million dollars from R&D funds for PV development. 74% of the R&D funds in the context of PV has been invested by the Ministry of Knowledge Economy (MKE). Expenditures for R&D programs in terms of PV are mainly funded by small-medium companies (40%), and the portion of the R&D investment in crystalline silicon solar cells is the highest in terms of materials. In spite of the high levels of R&D investment in PV, the output for commercialization was relatively lower compared to the R&D input in FY 2009–2010. With these results, we suggested to develop various solutions to improve the R&D investment efficiency for PV technology in Korea.     

Biomass and CCS: The influence of technical change

The combination of bioenergy production and carbon capture and storage technologies (BECCS) provides an opportunity to create negative emissions of CO₂ in biofuel production. However, high capture costs reduce profitability. This paper investigates carbon price uncertainty and technological uncertainty through a real option approach. We compare the cases of early and delayed CCS deployments. An early technological progress may arise from aggressive R&D and pilot project programs, but the expected cost reduction remains uncertain. We show that this approach results in lower emissions and more rapid investment returns although these returns will not fully materialise until after 2030. In a second set of simulations, we apply an incentive that prioritises sequestered emissions rather than avoided emissions. In other words, this economic instrument does not account for CO₂ emissions from the CCS implementation itself, but rewards all the sequestered emissions. In contrast with technological innovations, this subsidy is certain for the investor. The resulting investment level is higher, and the project may become profitable before 2030. Negative emission in bioethanol production does not seem to be a short-term solution in our framework, whatever the carbon price drift.     

Evaluating the development of carbon capture and storage technologies in the United States

Carbon capture and storage (CCS) is seen as an important solution to solve the twin challenge of reducing GHG emissions, while utilizing fossil fuel reserves to meet future energy requirements. In this study an innovation systems perspective is applied to review the development of CCS technologies in the US between 2000 and 2009 and to come up with policy recommendations for technology managers that wish to accelerate the deployment of CCS. The analysis describes the successful built-up of an innovation system around CCS and pinpoints the key determinants for this achievement. However, the evaluation of the system's performance also indicates that America's leading role in the development of CCS should not be taken for granted. It shows that the large CCS R&D networks, as well as the extensive CCS knowledge base, which have been accumulated over the past decade, have not yet been valorized by entrepreneurs to explore the market for integrated CCS concepts linked to power generation. Therefore, it is argued that the build-up of the innovation system has entered a critical phase that is decisive for a further thriving development of CCS technologies in the US. This study provides a clear understanding of the current barriers to the technology's future deployment and outlines a policy strategy that (1) stimulates technological learning; (2) facilitates collaboration and coordination in CCS actor networks; (3) creates financial and market incentives for the technology; and (4) provides supportive regulation and sound communication on CCS.     

Is there a relationship between public expenditures in energy R&D and carbon emissions per GDP? An empirical investigation

Energy innovation plays a crucial role in the reduction of carbon emissions. In order to design climate and energy policies that promote the development, deployment and diffusion of new energy technologies, policy makers not only require a theoretical understanding of the energy innovation system, but also empirical evidence of the effects that policy actions have had. This paper focuses on public energy R&D, a traditional and controversial option among the various climate technology policies, and empirically analyses its relationship with carbon emissions per GDP (i.e. carbon intensity) and its two components: energy intensity and the carbon factor. Evidence of the causality links that have prevailed in 13 advanced economies over the 1980–2004 period has been obtained through dynamic panel models. Our findings confirm that government R&D spending is not sufficient by itself to boost the energy innovation process. Public energy R&D has been successful in improving energy efficiency at country level, but it has failed to have a significant impact on the carbon factor and carbon intensity. At the same time the formation of energy R&D budgets is found to be significantly affected by carbon trends.     

Role of endogenous energy efficiency improvement in global climate change mitigation

Improving the energy efficiency of conventional energy services is an essential way to cope with global CO₂ emissions mitigation. To date, energy efficiency improvement (EEI) has been broadly introduced exogenously in integrated assessment models (IAMs) by virtue of the autonomous energy efficiency improvement (AEEI) coefficient; however, it is usually good at capturing the EEI driven by non-price factors, while weak in describing the EEI induced by policy incentives. In this paper, we introduce an endogenous EEI (EEEI) mechanism in an IAM, called E3METL, to explore the impacts of EEEI on the global macro-economy, CO₂ emission paths, and timing of carbon mitigations. The results reveal that (1) introducing EEEI significantly improves gross world product (GWP) gains, and this positive effect is partly offset when carbon restriction policies are implemented; (2) R&D investment dedicated to enhance energy efficiency limits R&D expenditures for other alternative technologies, and this effect will impede the development of non-fossil technologies; (3) EEEI may perform as one of supporting factors to delay the actions of carbon reduction; moreover, the introduction of EEEI lowers the optimal carbon tax level by 7.8 % on average, as compared to the no EEEI case.     

Optimal policy of energy innovation in developing countries: Development of solar PV in Iran

The purpose of this study is to apply managerial economics and methods of decision analysis to study the optimal pattern of innovation activities for development of new energy technologies in developing countries. For this purpose, a model of energy research and development (R&D) planning is developed and it is then linked to a bottom-up energy-systems model. The set of interlinked models provide a comprehensive analytical tool for assessment of energy technologies and innovation planning taking into account the specific conditions of developing countries. An energy-system model is used as a tool for the assessment and prioritization of new energy technologies. Based on the results of the technology assessment model, the optimal R&D resources allocation for new energy technologies is estimated with the help of the R&D planning model. The R&D planning model is based on maximization of the total net present value of resulting R&D benefits taking into account the dynamics of technological progress, knowledge and experience spillovers from advanced economies, technology adoption and R&D constraints. Application of the set of interlinked models is explained through the analysis of the development of solar PV in Iranian electricity supply system and then some important policy insights are concluded.     

The effects of environmental sustainability and R&D on corporate risk-taking: International evidence

In this paper, we ask an important question: can firm-level environmentally sustainable practices and research and development (R&D) intensity individually and jointly affect corporate risk-taking? Using firm-level data from 41 countries spanning 2002–2013, we find environmentally sustainable practices and R&D intensity enhance the risk-taking of firms. Voluntary sustainable practices generate a positive and significant effect on corporate risk-taking. We also find that country-level determinants play a complementary role. Firms operating in countries with better intellectual property rights protection and overall infrastructure benefit more from environment-friendly practices and R&D intensity. Further, we find that ESI has a positive effect on risk taking in countries with higher CO₂ emissions per capita, energy usages per capita and more stringent environmental policies. These results are robust after correcting for potential endogeneity, alternative measures of R&D intensity or ESI score. Overall, our findings provide key insights on policy recommendations at the national and international levels.     

A model-based assessment of the impact of revitalised R&D investments on the European power sector

This paper presents an analysis of the effect of enhanced research and development (R&D) efforts for a set of low-carbon power technologies on the development of the European energy sector. It applies a methodology using the concept of Two-Factor-Learning, which quantitatively links trends in technology cost to both accumulated R&D investments and production volumes. The impacts of the latter on the energy sector are then simulated in a consistent manner with the POLES global energy model. On this basis, it compares the total system costs of an assumed increase in worldwide R&D investments that for the EU are in line with proposals made in its European Strategic Energy Technology Plan to a baseline development. It finds that an increase in research efforts at a global level will contribute to reducing the costs of currently less mature low-carbon technologies, thus accelerating their market entry. When comparing two scenarios that both fulfil the EU's 2020 energy and climate objectives and differing only in their R&D investment levels, the reduced technology costs allow EU support policies for renewables and carbon values to be reduced, and the cumulative (discounted) benefit of the accelerated research efforts is positive in the long term.     

Green electricity market development: Lessons from Europe and the US

This study compares the development and implementation of green electricity policies in Germany, the Netherlands, Sweden, and the United States, a set of countries applying a range of policy instruments to encourage electricity from renewable energy sources. A general tendency is identified that policies shift emphasis from R&D stimulation towards dissemination and market application of renewable energy technologies. We argue that in light of the long term nature of policy goals on energy security, mitigation of climate change, and environmental protection, the applied range of policy instruments may be lacking in providing incentives for the long term development of new technologies. Clarifying policy objectives would allow careful selection of policy instruments, including support for R&D. Improved capacity building for policy implementation is also important.     

The impact of government subsidies and enterprises’ R&D investment: A panel data study from renewable energy in China

In this research, we aim to understand the influence of government subsidies on enterprises’ research and development (R&D) investment behavior, particularly in China’s renewable energy sector. We are also interested in examining how the attributes of enterprise ownership act as a moderating variable for the relationship between government subsidies and R&D investment behavior. Three classical panel data analysis models including the pooled ordinary least squares (OLS) model, the fixed effect model and the random effect model are employed. We find that government subsidies have a significant crowding out influence on enterprises’ R&D investment behavior and that the influence is further moderated by the attributes of enterprise ownership. Moreover, a panel threshold regression model is used to demonstrate how the influence of government subsidies on enterprises’ R&D investment behavior will change when government subsidies increase. Two thresholds, 0.6% and 10.1%, are identified. We recommend that relevant government departments should motivate enterprise R&D investment behavioral intention by increasing subsidies within a certain range. Different attributes of enterprise ownership should also be considered as part of policy reform and re-structuring relating to government subsidies.     

A MERGE model with endogenous technological change and the cost of carbon stabilization

Two stylized backstop systems with endogenous technological learning (ETL) are introduced in the “model for evaluating regional and global effects” (MERGE): one for the electric and the other for the non-electric markets. Then the model is applied to analyze the impacts of ETL on carbon-mitigation policy, contrasting the resulting impacts with the situation without ETL. We model research and development (R&D) spending and learning subsidies for the demonstration and deployment stage as control variables, and we investigate the ability of this extra spending to create path-dependent experience and knowledge to aid in the implementation of carbon-free technologies. Based on model estimations and sensitivity analyses, we conclude that increased commitments for the development of new technologies to advance along their learning curves has a potential for substantial reductions in the cost of mitigating climate change and thereby helping to reach safe concentrations of carbon in the atmosphere.