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We propose a novel framework for the economic assessment of environmental policy. Our main point of departure from existing work is the adoption of a satisficing, as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different policies meet a set of goals at a specific future date instead of their performance vis-a-vis some intertemporal objective function. Consistent to the nature of environmental policymaking, our model takes explicit account of model uncertainty. To this end, the decision criterion we propose is an analog of the well-known success-probability criterion adapted to settings characterized by model uncertainty. We apply our criterion to the climate-change context and the probability distributions constructed by Drouet et al. (2015) linking carbon budgets to future consumption. Insights from computational geometry facilitate computations considerably and allow for the efficient application of the model in high-dimensional settings. [ABSTRACT FROM AUTHOR]

Integrated assessment models (IAMs) are computer-based instruments used to assess the implications of human activity on the human and earth system. They are simultaneously also used to explore possible response strategies to climate change. As IAMs operate simplified representations of real-world processes within their model structures, they have been frequently criticised to insufficiently represent the opportunities and challenges in future energy systems over time. To test whether projections by IAMs diverge in systematic ways from projections made by technology experts we elicited expert opinion on prospective change for two indicators and compared these with the outcomes of IAM studies. We specifically focused on five (energy) technology families (solar, wind, biomass, nuclear, and carbon capture and storage or CCS) and compared the considered implications of the presence or absence of climate policy on the growth and diffusion of these technologies over the short (2030) to medium (2050) term. IAMs and experts were found to be in relatively high agreement on system change in a business-as-usual scenario, albeit with significant differences in the estimated magnitude of technology deployment over time. Under stringent climate policy assumptions, such as the internationally agreed upon objective to limit global mean temperature increase to no more than 2 °C, we found that the differences in estimated magnitudes became smaller for some technologies and larger for others. Compared to experts, IAM simulations projected a greater reliance on nuclear power and CCS to meet a 2 °C climate target. In contrast, experts projected a stronger growth in renewable energy technologies, particularly solar power. We close by discussing several factors that are considered influential to the alignment of the IAM and expert perspectives in this study. [ABSTRACT FROM AUTHOR]

Mitigating climate change will require innovation in energy technologies. Policy makers are faced with the question of how to promote this innovation, and whether to focus on a few technologies or to spread their bets. We present results on the extent to which public R&D might shape the future cost of energy technologies by 2030. We bring together three major expert elicitation efforts carried out by researchers at UMass Amherst, Harvard, and FEEM, covering nuclear, solar, Carbon Capture and Storage (CCS), bioelectricity, and biofuels. The results show experts believe that there will be cost reductions resulting from R&D and report median cost reductions around 20 % for most of the technologies at the R&D budgets considered. Although the improvements associated to solar and CCS R&D show some promise, the lack of consensus across studies, and the larger magnitude of the R&D investment involved in these technologies, calls for caution when defining what technologies would benefit the most from additional public R&D. In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. We conclude with recommendations for future directions on energy expert elicitations. [ABSTRACT FROM AUTHOR]

How can a decision-maker assess the potential of environmental policies when a group of experts provides divergent estimates on their effectiveness? To address this question, we propose and analyze a variant of the well-studied $$\alpha $$ -maxmin model in decision theory. In our framework, and consistent to the paper's empirical focus on renewable-energy R&D investment, experts' subjective probability distributions are allowed to be action-dependent. In addition, the decision maker constrains the sets of priors to be considered via a parsimonious measure of their distance to a benchmark 'average' distribution that grants equal weight to all experts. While our model is formally rooted in the decision-theoretic framework of Olszewski (Rev Econ Stud 74:567-595, ), it may also be viewed as a structured form of sensitivity analysis. We apply our framework to original data from a recent expert elicitation survey on solar energy. The analysis suggests that more aggressive investment in solar energy R&D is likely to yield significant dividends even, or rather especially, after taking expert ambiguity into account. [ABSTRACT FROM AUTHOR]

Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results. [ABSTRACT FROM AUTHOR]

In this paper we argue that when a subgroup of countries cooperate on emission reduction, the optimal response of non-signatory countries reflects the interaction between three potentially opposing factors, the incentive to free-ride on the environmental benefits of cooperation, the incentive to expand energy consumption, and the incentive to adopt the cleaner technologies introduced by the coalition. Using an Integrated Assessment Model with a game-theoretic structure we find that the equilibrium abatement of the coalition composed by OECD countries would be moderate, in line with the Pledges subscribed in Copenhagen, but increasing. The mitigation strategy would consist of investments in energy R&D and deployment of cleaner technologies with high learning potentials. International knowledge and technology externalities would facilitate the diffusion of cleaner technologies in non-signatory countries, offsetting the free-riding incentive and reducing their emissions. If the OECD group curbs emissions beyond the optimal equilibrium level, reaching reduction rates between 40 and 45 % below 2005 levels in 2050, the benefits of technology externalities would no longer compensate the effect of lower fossil fuel prices. Our results suggest that a moderate unilateral climate policy could induce a virtuous behaviour in non-signatory countries and that policies promoting the international transfer of technologies and knowledge could represent an effective complement to mitigation targets. [ABSTRACT FROM AUTHOR]

This paper examines the dynamics of innovation in low-carbon energy technologies distinguishing between research and development and technology diffusion as a response to alternative climate policies. We assess the implications of second-best policies that depart from the assumption of immediate and global participation and of full technology availability. The analysis highlights the heterogeneous effects of climate policy on different energy R&D programs and discusses the contribution of important determinants such as carbon price and policy stringency, policy credibility, policy and technological spillovers and absorptive capacity. [ABSTRACT FROM AUTHOR]

There is a new international policy focus on reducing emissions from deforestation and forest degradation (REDD), as well as promoting forest conservation, the sustainable management of forests and the enhancement of forest carbon stocks (REDD-plus). The recent Conference of Parties meeting of 196 countries of the United Nations Framework Convention on Climate Change (UNFCCC) in Cancun, Mexico (December 2010) was able to advance initiatives on REDD-plus even while there was limited progress on fossil fuel related aspects of an international climate change agreement. The Cancun meeting recognised that there was strong and broad support for REDD-plus and was able to agree to the development of a formal Mechanism under the UNFCCC for incentivizing REDD-plus activities. Implementing the Mechanism is another matter, and will require the development and coordination of country REDD-plus readiness and financing, including detailed consideration of country reference levels, measurement, reporting and verification methodologies, and sub-national and national program coordination. [ABSTRACT FROM AUTHOR]

The need for a better understanding of future energy scenarios, of their compatibility with the objective of stabilizing greenhouse gas concentrations, and of their links with climate policy, calls for the development of hybrid models. Hybrid because both the technological detail typical of Bottom Up (BU) models and the long run dynamics typical of Top Down (TD) models are crucially necessary. We present WITCH- World Induced Technical Change Hybrid model - a neoclassical optimal growth model (TD) with energy input detail (BU). The model endogenously accounts for technological progress, both through learning curves affecting prices of new vintages of capital and through R&D investments. In addition, the model captures the main economic interrelationships between world regions and is designed to analyze the optimal economic and environment policies in each world region as the outcome of a dynamic game. This paper provides a detailed description of the WITCH model, of its Baseline, and of the model calibration procedure. [ABSTRACT FROM AUTHOR]

In this paper we are concerned with modelling techniques for evaluating development and conservation opportunities when dealing with investment decisions involving environmental resources management. In this context, highly characterized by both environmental and economic uncertainty, we emphasize the importance of capturing the flexibility of different investment strategies. In particular, we discuss a discrete model that includes both environmental and economic uncertainty treated using an integrated approach. Decision analysis techniques and option pricing theory are jointly applied to evaluate development versus conservation opportunities. In our analysis, we take into account how uncertainty interacts with two types of irreversibility: sunk costs associated with investment in developing decisions, including environmental and social costs, as well as sunk costs associated with environmental regulation and conservation. The Quasi Option Value. QOV, is used to derive decision rules that account for different levels of flexibility of land allocation possibilities. [ABSTRACT FROM AUTHOR]