2. Reviews of models
What are the strengths and limitations of the models used in climate economics? How do the assumptions used in economic models shape their policy recommendations? Are there critical assumptions and relationships that should be added to standard models?
Limitations of integrated assessment models of climate change
Frank Ackerman, Stephen J. DeCanio, Richard B. Howarth and Kristen A. Sheeran
Climatic Change (2009) 95: 297-315.
Integrated assessment models (IAMs) used by economists to analyze climate change frequently suggest that the “optimal” policy is to go slowly and to do relatively little in the near term to reduce greenhouse gas emissions. This article traces this finding to contestable assumptions of IAMs, such as discounting future climate impacts at relatively high rates. IAMs also assign monetary values to the benefits of climate mitigation on the basis of incomplete information and sometimes speculative judgments concerning the monetary worth of human lives and ecosystems, while downplaying scientific uncertainty about the extent of expected damages. In addition, IAMs may exaggerate mitigation costs by failing to reflect the socially determined, path-dependent nature of technical change. A better approach to climate policy, drawing on recent research on the economics of uncertainty, would reframe the problem as buying insurance against catastrophic, low-probability events. Policy decisions should be based on a judgment concerning the maximum tolerable increase in temperature and/or carbon dioxide levels given the state of scientific understanding. The appropriate role for economists would then be to determine the least-cost global strategy to achieve that target. While this remains a demanding and complex problem, it is far more tractable and defensible than the cost-benefit comparisons attempted by most IAMs.
Energy policies avoiding a tipping point in the climate system
Olivier Bahn, Neil R. Edwards, Reto Knutti and Thomas F. Stocker
Energy Policy (2011) 39(1): 334-348.
Paleoclimate evidence and climate models indicate that certain elements of the climate system may exhibit thresholds, with small changes in greenhouse gas emissions resulting in non-linear and potentially irreversible regime shifts with serious consequences for socio-economic systems. Such thresholds or tipping points in the climate system are likely to depend on both the magnitude and rate of change of surface warming. The collapse of the Atlantic thermohaline circulation (THC) is one example of such a threshold. To evaluate mitigation policies that curb greenhouse gas emissions to levels that prevent such a climate threshold being reached, we use the MERGE model of Manne, Mendelsohn and Richels. Depending on assumptions on climate sensitivity and technological progress, our analysis shows that preserving the THC may require a fast and strong greenhouse gas emission reduction from today's level, with transition to nuclear and/or renewable energy, possibly combined with the use of carbon capture and sequestration systems.
Integrated modelling of climate control and air pollution: Methodology and results from one-way coupling of an energy-environment-economy (E3MG) and atmospheric chemistry model (p-TOMCAT) in decarbonising scenarios for Mexico to 2050
Terry Barker, Annela Anger, Olivier Dessens, Hector Pollitt, Helen Rogers, Serban Scrieciu, Rod Jones and John Pyle
Environmental Science & Policy (2010) 13(8): 661-670.
This paper reports the methodology and results of an one-way coupling of the E3 Model at the Global level (E3MG) model to the global atmospheric chemistry model, p-TOMCAT, to assess the effects on the concentrations of atmospheric gases over Mexico of a low-GHG scenario compared to an alternative reference case with higher use of fossil fuels. The paper covers the data and methods, changes in atmospheric gas concentrations, the macroeconomic effects of the policies, and the outcome for pollution. The results suggest that in the conditions of underemployment in Mexico, substantial investment in low-carbon technologies, such as electric vehicles, heat pumps and geo-thermal power, could improve employment prospects, maintain growth, as well as reduce some of the risks associated with prospective falls in oil revenues. The concentrations of low-level ozone, both for Mexico-only and global decarbonisation scenarios relative to the original reference case, show appreciable reductions, sufficient to bring concentrations close to the WHO guideline levels. An indication is given of the potential scale of the benefits on human health in Mexico City.
Psychohistory revisited: Fundamental issues in forecasting climate futures
Danny Cullenward, Lee Schipper, Anant Sudarshan and Richard B. Howarth
Climatic Change (2011)104(3-4): 457-472.
Uncertainty in the trajectories of the global energy and economic systems vexes the climate science community. While it is tempting to reduce uncertainty by searching for deterministic rules governing the link between energy consumption and economic output, this article discusses some of the problems that follow from such an approach. We argue that the theoretical and empirical evidence supports the view that energy and economic systems are dynamic, and unlikely to be predictable via the application of simple rules. Encouraging more research seeking to reduce uncertainty in forecasting would likely be valuable, but any results should reflect the tentative and exploratory nature of the subject matter.
Descriptive or conceptual models? Contributions of economics to the climate policy debate
Stephen J. DeCanio
International Environmental Agreements (2005) 5: 415-427.
Economists have brought two distinct modeling styles to the debate on climate policy. Some attempt to forecast the effects of policy decisions by constructing models that purport to be “descriptive” of the global economic system, while others offer a “conceptual” focus on particular economic or environmental issues. The descriptive models typically offer numerical comparisons of policy scenarios to a baseline, while the conceptual modelers often seek to provide insight into the ethical foundations or implications of different assumptions. These different modeling styles exhibit both contrasts and areas of overlap in their policy implications.
Induced technological change: Exploring its implications for the economics of atmospheric stabilization: Synthesis report from the Innovation Modeling Comparison Project
Ottmar Edenhofer, Kai Lessmann, Claudia Kemfert, Michael Grubb and Jonathan Köhler
The Energy Journal (2006) Special Issue 1 (2006): 207-222..
This paper summarizes results from ten global economy-energy-environment models implementing mechanisms of endogenous technological change. Different CO2 stabilization goals are imposed, and the contribution of induced technological change to meeting the goals is assessed. Climate policy induces additional technological change, in some models substantially. Its effect is a reduction of abatement costs in all participating models. Most models calculate abatement costs below 1 percent of aggregate gross world product for the period 2000–2100. The models predict different dynamics for carbon costs, with some showing a decline in carbon costs toward the end of the century. There are four major drivers of differences in results between models. First, the extent of the necessary CO2 reduction, which depends mainly on predicted baseline emissions, determines how much a model is challenged to comply with climate policy. Second, when climate policy can offset market distortions, some models show that not costs but benefits accrue from climate policy. Third, assumptions about long-term investment behavior, e.g. foresight of actors and number of available investment options, exert a major influence. Finally, whether and how options for carbon-free energy are implemented (backstop and end-of-the-pipe technologies) strongly affects both the mitigation strategy and the abatement costs.
Beyond the Stern Review: Lessons from a risky venture at the limits of the cost–benefit analysis
Jean-Charles Hourcade, Philippe Ambrosi and Patrice Dumas
Ecological Economics (2009) 68(10): 2479-2484.
This paper argues that debates amongst economists triggered by the Stern Review are partly relevant, focusing on key parameters translating real ethical issues, and partly misplaced in that they do not consider enough other determinants of climate change damages: i) the specifications of the utility function used for the assessments (preference for the environment, preference for smooth growth paths), ii) the interplay between uncertainty and the sequentiality of the decision, and iii) whether the growth engines behind the integrated assessment models can account for transient disequilibrium and sub-optimality. We derive some suggestions for any future research agenda in integrated assessment modelling, whatever the position of the analysts about the relevance of the intertemporal optimisation framework and the Bayesian approach to uncertainty in the climate affair.
Technological learning in energy-environment-economy modelling: A survey
Sondes Kahouli-Brahmi
Energy Policy (2008) 36(1): 138-162.
This paper aims at providing an overview and a critical analysis of the technological learning concept and its incorporation in energy-environment-economy models. A special emphasis is put on surveying and discussing, through the so-called learning curve, both studies estimating learning rates in the energy field and studies incorporating endogenous technological learning in bottom-up and top-down models. The survey of learning rate estimations gives special attention to interpreting and explaining the sources of variability of estimated rates, which is shown to be mainly inherent in R&D expenditures, the problem of omitted variable bias, the endogeneity relationship and the role of spillovers. Large-scale models survey show that, despite some methodological and computational complexity related to the non-linearity and the non-convexity associated with the learning curve incorporation, results of the numerous modelling experiments give several new insights with regard to the analysis of the prospects of specific technological options and their cost decrease potential (bottom-up models), and with regard to the analysis of strategic considerations, especially inherent in the innovation and energy diffusion process, in particular the energy sector's endogenous responses to environment policy instruments (top-down models).
Integrating bioenergy into computable general equilibrium models: A survey
Bettina Kretschmera and Sonja Peterson
Energy Economics (2010) 32(3): 673-686.
In the past years biofuels have received increased attention since they were believed to contribute to rural development, energy security and to fight global warming. It became clear, though, that bioenergy cannot be evaluated independently of the rest of the economy and that national and international feedback effects are important. Computable general equilibrium (CGE) models have been widely employed in order to study the effects of international climate policies. The main characteristic of these models is their encompassing scope: Global models cover the whole world economy disaggregated into regions and countries as well as diverse sectors of economic activity. Such a modelling framework unveils direct and indirect feedback effects of certain policies or shocks across sectors and countries. CGE models are thus well suited for the study of bioenergy/biofuel policies. One can currently find various approaches in the literature of incorporating bioenergy into a CGE framework. This paper gives an overview of existing approaches, critically assesses their respective power and discusses the advantages of CGE models compared to partial equilibrium models. Grouping different approaches into categories and highlighting their advantages and disadvantages is important for giving a structure to this rather recent and rapidly growing research area and to provide a guidepost for future work.
Room for improvement: increasing the value of energy modeling for policy analysis
J.A. Laitner, S.J. DeCanio, J.G. Koomey and A.H. Sanstad
Utilities Policy (2003) 11: 87-94.
There are expanding national discussions on energy-related issues ranging from the importance of reducing air pollution and greenhouse gas emissions to enhancing the nation’s energy security and moving toward a competitive electric utility industry. These issues have motivated the development of many energy-economic models to assist policy makers in framing appropriate policy directions. But how much do these models really inform the debate? The record of U.S. model-based energy forecasting shows that such models provide biased estimates that tend to reinforce the status quo, inadequately inform policy-makers about new market potential, and serve to constrain the development of innovative policies. This paper reviews some of the reasons for this conclusion and explores the extent to which energy-economic models may reflect a more dynamic technological diffusion process that encourages new policy development.
Inside the integrated assessment models: Four issues in climate economics
Elizabeth A. Stanton, Frank Ackerman and Sivan Kartha
Climate and Development (2009) 1(2): 166-184.
Good climate policy requires the best possible understanding of how climatic change will impact on human lives and livelihoods in both industrialized and developing counties. Our review of the recent climate-economics literature assesses 30 existing integrated assessment models in terms of four key aspects of the nexus of climate and the economy: the connection between the model structure and the type of results produced; uncertainty in climate outcomes and the projection of future damages; equity across time and space; and abatement costs and the endogeneity of technological change. Differences in treatment of these issues are substantial, and directly affect model results and their implied policy prescriptions. Much can be learned about climate economics and modeling technique from the best practices in these areas; there is unfortunately no existing model that incorporates the best practices on all or most of the questions we examine.
How well do integrated assessment models simulate climate change?
Detlef P. van Vuuren, Jason Lowe, Elke Stehfest, Laila Gohar, Andries F. Hof, Chris Hope, Rachel Warren, Malte Meinshausen and Gian-Kasper Plattner
Climatic Change (2011) 104(2): 255-285.
Integrated assessment models (IAMs) are regularly used to evaluate different policies of future emissions reductions. Since the global costs associated with these policies are immense, it is vital that the uncertainties in IAMs are quantified and understood. We first demonstrate the significant spread in the climate system and carbon cycle components of several contemporary IAMs. We then examine these components in more detail to understand the causes of differences, comparing the results with more complex climate models and earth system models (ESMs), where available. Our results show that in most cases the outcomes of IAMs are within the range of the outcomes of complex models, but differences are large enough to matter for policy advice. There are areas where IAMs would benefit from improvements (e.g. climate sensitivity, inertia in climate response, carbon cycle feedbacks). In some cases, additional climate model experiments are needed to be able to tune some of these improvements. This will require better communication between the IAM and ESM development communities.