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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?

A coopetitive model for the green economy
Carfì, D. & Schilirò, D.
Economic Modelling, 2012, 29, 1215 – 1219
The paper proposes a coopetitive model for the Green Economy. It addresses the issue of the climate change policy and the creation and diffusion of low-carbon technologies. In the present paper the complex construct of coopetition is applied at macroeconomic level. The model, based on Game Theory, enables us to offer a set of possible solutions in a coopetitive context, allowing to find a Pareto solution in a win/win scenario. The model, which is based on the assumption that each country produces a level of output which is determined in a non-cooperative game of Cournot-type and that considers at the same time a coopetitive strategy regarding the low technologies, will suggest a solution that shows the convenience for each country to participate actively to a program of low carbon technologies within a coopetitive framework to address a policy of climate change, thus aiming at balancing the environmental imbalances.

Cutting costs of catching carbon-Intertemporal effects under imperfect climate policy
Hoel, M. & Jensen, S.
Resource and Energy Economics, 2012, 34, 680 - 695
We use a two-period model to investigate intertemporal effects of cost reductions in climate change mitigation technologies for the power sector. The effect of cost reductions for CCS depends on how carbon taxes are set. If there is no carbon tax in period 1, but an optimally set carbon tax in period 2, a CCS cost reduction may reduce early emissions. Such an innovation may therefore be more desirable than comparable cost cuts related to renewable energy. The finding rests on the incentives fossil fuel owners face. If future profitability is reduced, they speed up extraction (the "green paradox"), and vice versa.

A choice modelling case study on climate change involving two-way interactions
Riera, P., Giergiczny, M., Peñuelas, J. & Mahieu, P.-A.
Journal of Forest Economics, 2012, 18, 345 - 354
Choice Modelling applications can be designed to estimate main effects only or multiple-way interactions between attributes. It has been reported that higher order effects generally account for less than 10% of the choice explanation. Nevertheless, the amount of applications testing for interactions among attributes in environmental valuation is very limited. This paper reports a Choice Modelling exercise valuing climate change impacts on plant cover, land erosion and fire risk in Spanish shrublands. Two out of three two-way interactions were found significant and to account for more than 20% of the choice model explanation. Their contribution to the log-likelihood value was comparable to the one of the main effects variables. Moreover, accounting for second order interactions significantly altered the estimates of the implicit prices of attributes compared to the main effects specifications.

Sectoral linking of carbon markets: A trade-theory analysis
Marschinski, R.; Flachsland, C. & Jakob, M.
Resource and Energy Economics, 2012, 34, 585 - 606
The linking of emission trading systems (ETS) is a widely discussed policy option for future international cooperation on climate change. Benefits are expected from efficiency gains and the alleviation of concerns over competitiveness. However, from trade-theory it is known that due to general equilibrium effects and market distortions, linking may not always be beneficial for all participating countries. Following-up on this debate, we use a Ricardo-Viner type general equilibrium model to study the implications of sectoral linking on carbon emissions ("leakage"), competitiveness, and welfare. By comparing pre- and post-linking equilibria, we show analytically how global emissions can increase if one of the "linked" countries lacks an economy-wide emissions cap, although in case of a link across idiosyncratic sectors a decrease of emissions ("anti-leakage") is also possible. If -- as a way to address concerns about competitiveness -- a link between the EU ETS and a hypothetical US system is established, the partial emission coverage of the EU ETS can lead to the creation of new distortions between the non-covered domestic and international sector. Finally, we show how the welfare effect from linking can be decomposed into gains-from-trade and terms-of-trade contributions, and how the latter can make the overall effect ambiguous.

Climate damages in the FUND model: A disaggregated analysis
Ackerman, F. & Munitz, C.
Ecological Economics, 2012, 77, 219 - 224
We examine the treatment of climate damages in the FUND model. By inserting software switches to turn individual features on and off, we obtain FUND's estimates for 15 categories of damages, and for components of the agricultural category. FUND, as used by the U.S. government to estimate the social cost of carbon, projects a net benefit of climate change in agriculture, offset by a slightly larger estimate of all other damages. Within agriculture there is a large benefit from CO2 fertilization, a moderate cost from the effect of temperature on yields, and a much smaller impact of the rate of change. In FUND's agricultural modeling, the temperature-yield equation comes close to dividing by zero for high-probability values of a Monte Carlo parameter. The range of variation of the optimal temperature exceeds physically plausible limits, with 95% confidence intervals extending to 17°C above and below current temperatures. Moreover, FUND's agricultural estimates are calibrated to research published in 1996 or earlier. Use of estimates from such models is arguably inappropriate for setting public policy. But as long as such models are being used in the policymaking process, an update to reflect newer research and correct modeling errors is needed before FUND's damage estimates can be relied on.

A proposal for a new scenario framework to support research and assessment in different climate research communities
van Vuuren, D. P.; Riahi, K.; Moss, R.; Edmonds, J.; Thomson, A.; Nakicenovic, N.; Kram, T.; Berkhout, F.; Swart, R.; Janetos, A.; Rose, S. K. & Arnell, N.
Global Environmental Change, 2012, 22, 21 - 35
In this paper, we propose a scenario framework that could provide a scenario “threadâ€? through the different climate research communities (climate change â€" vulnerability, impact, and adaptation - and mitigation) in order to support assessment of mitigation and adaptation strategies and climate impacts. The scenario framework is organized around a matrix with two main axes: radiative forcing levels and socio-economic conditions. The radiative forcing levels (and the associated climate signal) are described by the new Representative Concentration Pathways. The second axis, socio-economic developments comprises elements that affect the capacity for mitigation and adaptation, as well as the exposure to climate impacts. The proposed scenarios derived from this framework are limited in number, allow for comparison across various mitigation and adaptation levels, address a range of vulnerability characteristics, provide information across climate forcing and vulnerability states and span a full century time scale. Assessments based on the proposed scenario framework would strengthen cooperation between integrated-assessment modelers, climate modelers and vulnerability, impact and adaptation researchers, and most importantly, facilitate the development of more consistent and comparable research within and across these research communities.

Validation and forecasting accuracy in models of climate change
Fildes, R. & Kourentzes, N.
International Journal of Forecasting, 2011, 27, 968 - 995
Forecasting researchers, with few exceptions, have ignored the current major forecasting controversy: global warming and the role of climate modelling in resolving this challenging topic. In this paper, we take a forecaster’s perspective in reviewing established principles for validating the atmospheric-ocean general circulation models (AOGCMs) used in most climate forecasting, and in particular by the Intergovernmental Panel on Climate Change (IPCC). Such models should reproduce the behaviours characterising key model outputs, such as global and regional temperature changes. We develop various time series models and compare them with forecasts based on one well-established AOGCM from the UK Hadley Centre. Time series models perform strongly, and structural deficiencies in the AOGCM forecasts are identified using encompassing tests. Regional forecasts from various GCMs had even more deficiencies. We conclude that combining standard time series methods with the structure of AOGCMs may result in a higher forecasting accuracy. The methodology described here has implications for improving AOGCMs and for the effectiveness of environmental control policies which are focussed on carbon dioxide emissions alone. Critically, the forecast accuracy in decadal prediction has important consequences for environmental planning, so its improvement through this multiple modelling approach should be a priority.

DICER: A tool for analyzing climate policies
Ortiz, Ramon A.; Golub, Alexander; Lugovoy, leg.; Markandya, Anil & Wang, James
Energy Economics, 2011, 33, Supplement 1, S41 - S49
Modeling the economy and the planet's climate involves a great number of variables and parameters, some of them very uncertain given the current stage of knowledge regarding technology and the science of climate. The DICER model (or DICE-Regional) is a recently constructed Integrated Assessment Model (IAM), based on the structure of the DICE family of models, which was developed as an instrument for the analysis of uncertainties in climate policy. This paper aims to describe the basic version of DICER on which future developments addressing uncertainty in climate policy analysis will be based. Our results suggest a few interesting conclusions when compared to other IAMs: (i) under a plausible set of assumptions and parameters DICER indicates that an optimal global climate policy would imply higher costs of climate change in the short run but a faster (and more expensive) decarbonization process in all regions, resulting in a faster stabilization of the climate; (ii) lower peak temperatures that occur earlier in time; (iii) considerable sensitivity of results to key parameters such as climate sensitivity, but lower than expected sensitivity to the social discount rate.

Economic analysis of the climate pledges of the Copenhagen Accord for the EU and other major countries
Saveyn, B.; Regemorter, D. V. & Ciscar, J. C.
Energy Economics, 2011, 33, Supplement 1, S34 - S40
This article uses the world GEM-E3 computable general equilibrium model to assess the economic consequences of the climate ˜Copenhagen Accord". The model allows analyzing the macroeconomic costs in terms of GDP, the change in employment, as well as the impacts on production of specific energy-intensive sectors. Various 2020 climate scenarios are evaluated depending on the GHG mitigation pledges. We find that the cost for the developed countries is around 0.5% of GDP in 2020 for the more ambitious pledges, whereas the GDP effects are more heterogeneous across developing countries and Russia, reflecting the different pledges and the assumptions in the reference scenario across these countries. Further, the article explores whether there is a form of double dividend in the EU when the revenues from auctioning or taxation of GHG emissions are used to reduce the social security contributions of employees. We conclude that GDP and employment perform better compared to the free allocation of permits when more sectors are subject to auctioning or GHG taxes and the additional government revenues are used to reduce the cost of labour.

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.

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.

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.

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.

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.

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.

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.

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).

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: 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.

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.

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 US 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.