Did the Stern Review underestimate US and global climate damages?

The Stern Review received widespread attention for its innovative approach to the economics of climate change when it appeared in 2006, and generated controversies that have continued to this day. One key controversy concerns the magnitude of the expected impacts of climate change. Stern's estimates, based on results from the PAGE2002 model, sounded substantially greater than those produced by many other models, leading several critics to suggest that Stern had inflated his damage figures.     

On the sources of technological change: Assessing the evidence

This paper uses a selective review of the economic literature on technological change to support four points that are important for interpreting and incorporating technological change into formal models of energy and the environment. The review (1) supports the notion that no single source dominates the process of technological change. It supports roles for R&D and learning-by-doing within an industry, as well as for spillovers from other industries engaged in both of these activities. The literature also (2) supports a strong role for spillovers; (3) indicates that these spillovers are often indirect, requiring own-industry activities to utilize; and (4) indicates that simple experience curve calibrations often used in formal models likely include a range of sources of technological change in addition to learning-by-doing, some of which might not be induced by the sorts of policies typically considered in the climate context.     

Vulnerability of wind power resources to climate change in the continental United States

Renewable energy resources will play a key role in meeting the world's energy demand over the coming decades. Unfortunately, these resources are all susceptible to variations in climate, and hence vulnerable to climate change. Recent findings in the atmospheric science literature suggest that the impacts of greenhouse gas induced warming are likely to significantly alter climate patterns in the future. In this paper we investigate the potential impacts of climate change on wind speeds and hence on wind power, across the continental US. General Circulation Model output from the Canadian Climate Center and the Hadley Center were used to provide a range of possible variations in seasonal mean wind magnitude. These projections were used to investigate the vulnerability of current and potential wind power generation regions. The models were generally consistent in predicting that the US will see reduced wind speeds of 1.0 to 3.2% in the next 50 years, and 1.4 to 4.5% over the next 100 years. In both cases the Canadian model predicted larger decreases in wind speeds. At regional scales the two models showed some similarities in early years of simulations (e.g. 2050), but diverged significantly in their predictions for 2100. Hence, there is still a great deal of uncertainty regarding how wind fields will change in the future. Nevertheless, the two models investigated here are used as possible scenarios for use in investigating regional wind power vulnerabilities, and point to the need to consider climate variability and long term climate change in citing wind power facilities.     

Production functions for climate policy modeling: An empirical analysis

Quantitative models for climate policy modeling differ in the production structure used and in the sizes of the elasticities of substitution. The empirical foundation for both is generally lacking. This paper estimates the parameters of 2-level CES production functions with capital, labour and energy as inputs, and is the first to systematically compare all nesting structures. Using industry-level data from 12 OECD countries, we find that the nesting structure where capital and labour are combined first, fits the data best, but for most countries and industries we cannot reject that all three inputs can be put into one single nest. These two nesting structures are used by most climate models. However, while several climate policy models use a Cobb–Douglas function for (part of the) production function, we reject elasticities equal to one, in favour of considerably smaller values. Finally we find evidence for factor-specific technological change. With lower elasticities and with factor-specific technological change, some climate policy models may find a bigger effect of endogenous technological change on mitigating the costs of climate policy.     

The impact of climate change on the European energy system

Climate change can affect the economy via many different channels in many different sectors. The POLES global energy model has been modified to widen the coverage of climate change impacts on the European energy system. The impacts considered are changes in heating and cooling demand in the residential and services sector, changes in the efficiency of thermal power plants, and changes in hydro, wind (both on- and off-shore) and solar PV electricity output. Results of the impacts of six scenarios on the European energy system are presented, and the implications for European energy security and energy imports are presented.Main findings include: demand side impacts (heating and cooling in the residential and services sector) are larger than supply side impacts; power generation from fossil-fuel and nuclear sources decreases and renewable energy increases; and impacts are larger in Southern Europe than in Northern Europe.There remain many more climate change impacts on the energy sector that cannot currently be captured due to a variety of issues including: lack of climate data, difficulties translating climate data into energy-system-relevant data, lack of detail in energy system models where climate impacts act. This paper does not attempt to provide an exhaustive analysis of climate change impacts in the energy sector, it is rather another step towards an increasing coverage of possible impacts.     

Derivation of an index for evaluating economics of cogeneration systems and its applications

In this paper, a simple index for evaluating the economics of cogeneration systems (CGS) is first derived. Second, various strategies to improve the economics of a CGS is generally discussed. Finally, the impacts of the change in various factors determining the economics of a CGS are investigated, by taking a CGS composed of gas turbines and a waste heat boiler for district heating and cooling as an example. It has been shown that the index derived makes it possible to easily evaluate not only the economic feasibility of the CGS, but also the degree of the impacts of improvement in the following economic and technological factors on its economics: (i) rise of the unit selling price of electricity and heat, (ii) decrease of the fuel cost, (iii) reduction in the annual cost rate for the construction cost of the CGS, (iv) increase in the capacity factor of the CGS, (v) improvements in efficiencies of generating power and heat, and (vi) decrease in the construction cost of the CGS.     

Sensitivity of modeling results to technological and regional details: The case of Italy's carbon mitigation policy

Model differences in technological and geographical scales are common, but their contributions to uncertainties have not been systematically quantified in the climate policy literature. This paper carries out a systematic assessment on the sensitivity of Computable General Equilibrium models to technological and geographical scales in evaluating the economic impacts of carbon mitigation policies. In particular, we examine the impacts of sub-national details and technological details of power generation on the estimate of carbon price and economic cost. Taking Italy as an example, we find that the estimation for carbon price and the economic cost of a de-carbonization pathway by means of a model with technological and regional details can be lower than a model without such details by up to 40%. Additionally, the effect of representing regional details appears to be far more important than the effect of representing the details of electricity technology in both the estimated carbon prices and the estimated economic impacts. Our results for Italy highlight the importance of modeling uncertainties of these two key assumptions, which should be appropriately acknowledged when applying CGE models for policy impact assessment. Our conclusions can be generalized to different countries and policy scenarios not in terms of absolute numbers but in terms of economic explanations. In particular, intra-national trade and the sub-national sectoral/technological specialization are important variables for understanding the economic dynamics behind these outcomes.     

Multiple equilibria in a stochastic implementation of DICE with abrupt climate change

Integrated assessment modeling of global climate change has focused primarily on gradually occurring changes in the climate system. However, atmospheric and earth scientists have become increasingly concerned that the climate system may be subject to abrupt, discontinuous changes on short time scales, and that anthropogenic greenhouse-gas emissions could trigger such shifts. Incorporating this type of climate dynamics into economic or integrated assessment models can result in model non-convexity and multiple equilibria, and thus complicate policy analysis relative to models with unique, globally optimal policies. Using a version of the Nordhaus DICE model amended in previous research by Keller et al. (2004) [Keller, Klaus, Benjamin M. Bolker, David F. Bradford, 2004. Uncertain climate thresholds and optimal economic growth. Journal of environmental economics and management 48 (1), 723–741], in conjunction with a stochastic global optimization algorithm, we generate “level sets” of solutions, which helps identify multiple equilibria resulting from the potential abrupt cessation of the North Atlantic Thermohaline Circulation. We discuss the implications of this model geometry for formulating greenhouse-gas abatement policy under uncertainty and suggest that this general approach may be useful for addressing a wide range of model non-convexities including those related to endogenous technological change.     

Advanced solar R&D: Combining economic analysis with expert elicitations to inform climate policy

The relationship between R&D investments and technical change is inherently uncertain. In this paper we combine economics and decision analysis to incorporate the uncertainty of technical change into climate change policy analysis. We present the results of an expert elicitation on the prospects for technical change in advanced solar photovoltaics. We then use the results of the expert elicitations as inputs to the MiniCAM integrated assessment model, to derive probabilistic information about the impacts of R&D investments on the costs of emissions abatement.     

The economics of climate change and the change of climate in economics

Economics is an unavoidable decision-making tool in the field of climate policy. At the same time, traditional economics is being challenged both empirically and theoretically by scholars in different fields. Its non-neutrality in dealing with climate-related issues—which is illustrated by the controversy over the “no-regret potential”—would thus call for an opening of economics to insights from other disciplines. Within that context, we show that an evolutionary-inspired line of thought coupled with a systemic and historical perspective of technological change provides a very insightful alternative to traditional economics. More particularly, it follows from that framework that the picture of the climate challenge ahead looks very different from what traditional economic analyses would suggest. For instance, the lock-in process makes it unlikely that traditional cost-efficient measures (such as carbon taxation or tradable emission rights) will be sufficient to bring about the required radical changes in the field of energy as they fail to address structural barriers highlighted in our approach.     

Uncertainty and endogenous technical change in climate policy models

Until recently endogenous technical change and uncertainty have been modeled separately in climate policy models. In this paper, we review the emerging literature that considers both these elements together. Taken as a whole the literature indicates that explicitly including uncertainty has important quantitative and qualitative impacts on optimal climate change technology policy.     

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.     

How to accelerate green technology diffusion? Directed technological change in the presence of coevolving absorptive capacity

The time window for effective climate change mitigation is closing. Technological change needs to be accelerated to limit global warming to a manageable level. Path dependence of technological change is one explanation for sluggish diffusion of green technologies. Firms acquire capital that differs by technology type and build up type-specific technological know-how needed to use capital efficiently. Path dependence emerges from cumulative knowledge stocks manifested in the productivity of supplied capital and firms’ capabilities. Increasing returns arise from induced innovation feedbacks and learning by doing. Relatively lower endowments with technological knowledge are a barrier to diffusion for new technologies. This paper shows how the evolution of relative stocks of technological knowledge explains different shapes of diffusion curves. Using an eco-technology extension of the macroeconomic agent-based model Eurace@unibi, it is shown how the effectiveness of different climate policies depends on the type and strength of diffusion barriers. Environmental taxes can outweigh lower productivity and subsidies perform better if lacking capabilities hinder firms to adopt a sufficiently mature technology.     

Representing induced technological change in models for climate policy analysis

Induced technological change (ITC), whereby the relative price effects of reducing greenhouse gas emissions stimulate innovation that mitigates the cost of abatement, is both tantalizing to decision makers and challenging to represent in the computational economic and engineering models used to analyze climate change policy. This overview reconciles the divergent views of technology and technological change within different types of models, elucidates the theoretical underpinnings of ITC, introduces the reader to the techniques of their practical implementation, and evaluates the implications for models' results.     

气候变化的责任与中国的努力

气候变化问题是全球共同面临的挑战,事关社会发展和人类生存,对于各国的能源发展、经济竞争力、科技创新以及生活方式都将产生重大的影响。近年来,随着中国经济的快速发展,有人在制造和散布"中国威胁论"的同时,又以各种不同形式抛出所谓"中国环境威胁论"、"中国环境责任论"等,说中国二氧化碳排放的快速增长抵消了国际社会在减排方面所作的努力,中国应承担与温室气体排放大国相称的国际责任等,这些言论显然是不客观的,也是有失公允的。中国过去已经为全球应对气候变化做出了积极的贡献,未来仍将是保护全球气候的中坚力量。     

Integrated assessment of global climate change with learning-by-doing and energy-related research and development

This paper presents a small-scale version of an Integrated Assessment Model (IAM) of global climate change, which is based on a global, regionally differentiated computable general equilibrium (CGE) model with endogenous technological change. This model can be viewed as a basic framework for analyzing a broad range of economic issues related to climate change, in particular since technological change is represented in two ways: on the one hand, there is learning-by-doing (LbD) in non-fossil energy supply technologies, and on the other hand there is research and development (R&D)-driven energy-saving technical progress in production. Computational experiments are added for illustrating the role of technological innovation in a world both with and without cooperation in the solution of the global climate problem.     

A conceptual framework for estimating the climate impacts of land-use change due to energy crop programs

In this paper I discuss general conceptual issues in the estimation of the impacts of CO₂ emissions from soils and biomass, over time, as a result of land-use change (LUC) due to increased demand for energy crops. The effect of LUC on climate depends generally on the magnitude and timing of changes in soil and plant carbon, and in particular on the timing and extent of the reversion of land to original ecosystems at the end of the bioenergy program. Depending on whether one counts the climate impacts of any reversion of land uses, and how one values future climate-change impacts relative to present impacts, one can estimate anywhere from zero to very large climate impacts due to land-use change (LUC). I argue that the best method is to estimate the net present value (NPV) of the impacts of climate change due to LUC. With this approach, one counts the reversion impacts at the end of the program and applies a continuous discounting function to future impacts to express them in present terms. In this case, the impacts of CO₂ emissions from the initial LUC then are at least partially offset by the impacts of CO₂ sequestration from reversion.     

Endogenizing technological change: Matching empirical evidence to modeling needs

Given that technologies to significantly reduce fossil fuel emissions are currently unavailable or only available at high cost, technological change will be a key component of any long-term strategy to reduce greenhouse gas emissions. In light of this, the amount of research on the pace, direction, and benefits of environmentally-friendly technological change has grown dramatically in recent years. This research includes empirical work estimating the magnitude of these effects, and modeling exercises designed to simulate the importance of endogenous technological change in response to climate policy.Unfortunately, few attempts have been made to connect these two streams of research. This paper attempts to bridge that gap. We review both the empirical and modeling literature on technological change. Our focus includes the research and development process, learning by doing, the role of public versus private research, and technology diffusion.Our goal is to provide an agenda for how both empirical and modeling research in these areas can move forward in a complementary fashion. In doing so, we discuss both how models used for policy evaluation can better capture empirical phenomena, and how empirical research can better address the needs of models used for policy evaluation.     

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.     

Beyond technology-push and demand-pull: Lessons from California's solar policy

The scale of the technological transformation required to reduce greenhouse gas emissions to “safe” levels while minimizing economic impacts necessitates an emphasis on designing climate policy to foster, or at least not impede, environmental innovation. There is only a weak empirical base for policy-makers to stand on regarding the comparative innovation effects of various climate policy options, however. Empirical scholarship in environmental innovation is hindered by the complexity of both the innovation process and the interactions between the dual market failures of pollution and innovation that are in play, and it appears that the field would benefit from the structure provided by a common lexicon. This paper focuses on the issues related to policy categorization in this field; these issues have received little attention in the literature despite their importance to making insights gained from empirical studies generalizable. The paper reviews the origins, strengths, and weaknesses of the dominant policy typology of technology-push versus demand-pull instruments. Its primary contribution, however, is to assemble a comprehensive chronology of solar policy in California and its impacts on innovation, where known, and then use this as a basis for building a new policy categorization that takes advantage of the intuitive resonance of the dominant typology, while encompassing the broader range of policy instruments that are employed in practice in order to stimulate environmental innovation. The most noteworthy aspect of the new categorization is that it introduces a third category of environmental innovation policy instrument that focuses on improving the interface between technology suppliers and users. This reflects developments in the economics of innovation literature as well as considerable evidence in the domain of distributed solar energy technologies that opportunism by some of the actors that work at this interface can be a barrier to innovation.