Economic models for climate policy analysis: A critical discussion

Climate policy analysis has come to rely heavily on large‐scale numerical simulation models of increasing complexity, posing a challenge to policy‐makers and other non‐specialists who must interpret and apply the models. This paper provides a “user's guide” to economic models used in climate analysis. We review basic features, underlying design issues, and basic research questions bearing on the models' foundations. We also provide an overview of five such global or world models currently in use.     

Evaluating response surface designs for uncertainty analysis and prescriptive applications of a large-scale water quality model

Environmental models are often too large and cumbersome for effective use in regulatory decision making or in the characterization of uncertainty. This paper describes and compares four response surfaces that could complement a large-scale water quality model, the U.S. National Water Pollution Control Assessment Model (NWPCAM), in simulation and regulatory decision support applications. Results show that a physically based reduced-form model that exploits the mathematical structure of the underlying water quality model is a better predictor of policy-relevant outputs than the polynomial expansions that are frequently used in response surface studies.     

A review of EIAs on trade policy in China: Exploring the way for economic policy EIAs

During the discussion on the “Environmental Protection Law Amendment (draft)” in 2011, it was decided to drop the proposed clauses related to environmental impact assessments (EIAs) on policy, which means that there remained no provisions for policy EIAs, and China's strategic environmental assessment system stayed limited to the planning level. However, considering that economic policy making is causing significant direct and indirect environmental problems and that almost every aspect of governmental policy has an economic aspect, EIAs on economic policies are of the utmost urgency. The purpose of this study is to review the EIA work that has been carried out on trade policy in China through four case studies, and illustrate how trade policy EIAs can be helpful in achieving better environmental outcomes in the area of trade. Through the trade policy EIA case studies we try to argue for the feasibility of conducting EIAs on economic policies in China. We also discuss the implications of the case studies from the point of view of how to proceed with EIAs on economic policy and how to promote their practice.     

Estimating home energy decision parameters for a hybrid energy—economy policy model

Hybrid energy–economy models combine the advantages of a technologically explicit bottom–up model with the behavioral realism sought after by top–down models in order to help policymakers assess the likely technology-specific response and economy-wide impact of policies to induce technological change. We use a discrete choice survey to estimate key technology choice parameters for a hybrid model. Two choice experiments are conducted for household energy-related decisions about retrofitting home building structures and choosing a space heating and conditioning system. Based on a discrete choice survey of 625 householders, we estimate a discrete choice model and then demonstrate how its parameters translate into the behavioral parameters of a hybrid model. We then simulate household energy policies, including, individual subsidies and increased regulations.     

Avian collision risk models for wind energy impact assessments

With the increasing global development of wind energy, collision risk models (CRMs) are routinely used to assess the potential impacts of wind turbines on birds. We reviewed and compared the avian collision risk models currently available in the scientific literature, exploring aspects such as the calculation of a collision probability, inclusion of stationary components e.g. the tower, angle of approach and uncertainty. 10 models were cited in the literature and of these, all included a probability of collision of a single bird colliding with a wind turbine during passage through the rotor swept area, and the majority included a measure of the number of birds at risk. 7 out of the 10 models calculated the probability of birds colliding, whilst the remainder used a constant. We identified four approaches to calculate the probability of collision and these were used by others. 6 of the 10 models were deterministic and included the most frequently used models in the UK, with only 4 including variation or uncertainty in some way, the most recent using Bayesian methods. Despite their appeal, CRMs have their limitations and can be ‘data hungry’ as well as assuming much about bird movement and behaviour. As data become available, these assumptions should be tested to ensure that CRMs are functioning to adequately answer the questions posed by the wind energy sector.     

Advancing effects analysis for integrated, large-scale wildfire risk assessment

In this article, we describe the design and development of a quantitative, geospatial risk assessment tool intended to facilitate monitoring trends in wildfire risk over time and to provide information useful in prioritizing fuels treatments and mitigation measures. The research effort is designed to develop, from a strategic view, a first approximation of how both fire likelihood and intensity influence risk to social, economic, and ecological values at regional and national scales. Three main components are required to generate wildfire risk outputs: (1) burn probability maps generated from wildfire simulations, (2) spatially identified highly valued resources (HVRs), and (3) response functions that describe the effects of fire (beneficial or detrimental) on the HVR. Analyzing fire effects has to date presented a major challenge to integrated risk assessments, due to a limited understanding of the type and magnitude of changes wrought by wildfire to ecological and other nonmarket values. This work advances wildfire effects analysis, recognizing knowledge uncertainty and appropriately managing it through the use of an expert systems approach. Specifically, this work entailed consultation with 10 fire and fuels program management officials from federal agencies with fire management responsibilities in order to define quantitative resource response relationships as a function of fire intensity. Here, we demonstrate a proof-of-concept application of the wildland fire risk assessment tool, using the state of Oregon as a case study.     

Combining policy instruments for sustainable energy systems: An assessment with the GMM model

An assessment of the impact of an illustrative portfolio of policy instruments that address different sustainability concerns in the global energy system in areas of climate change, air pollution and introduction of renewable-energy resources is conducted. The effects of a policy set containing three instruments, implemented either individually or in combination, were examined. The policy instruments under examination in this work include: Cap-and-Trade policies imposing a CO₂ emission reduction target on the global energy system, a renewable portfolio standard that forces a minimum share of renewable electricity generation, and the internalisation of external costs of power generation associated with local pollution. Implementation of these policy instruments significantly changes the structure and environmental performance of the energy sector, and particularly the structure of the electric-generation sector. The positive effects are amplified when the policy instruments are simultaneously applied, illustrating the potential for synergies between these energy-policy domains. The analysis has been conducted with the multi-regional, energy-system Global MARKAL Model (GMM), a “bottom-up” partial-equilibrium model that provides a detailed representation of energy technologies and endogenizes technology learning. ^★A preliminary version of this paper has been presented at the 6th IAEE European Energy Conference on “Modelling in Energy Economics and Policy”, 1–3 September 2004, ETH Zürich, Switzerland.     

Near term mitigation policy for global change under uncertainty: Minimizing the expected cost of meeting unknown concentration thresholds

An aggregate integrated assessment model is used to investigate the relative merits of hedging over the near term against the chance that atmospheric concentrations of carbon dioxide will be limited as a matter of global policy. Hedging strategies are evaluated given near term uncertainty about the targeted level of limited concentrationsand the trajectory of future carbon emissions. All uncertainty is resolved in the year 2020, and strategies that minimize the expected discounted value of the long term cost of abatement, including the extra cost of adjusting downstream to meet unexpected concentration limits along unanticipated emission trajectories, are identified. Even with uncertainties that span current wisdom on emission futures and restriction thresholds that run from 550 ppm through 850 ppm, the results offer support for at most modest abatement response over the next several decades to the threat of global change.     

An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models

This paper presents a study on the effect of topographic variability on grid-based empirical estimation of soil erosion and sediment transport with raster geographic information systems (GIS). An original digital elevation model (DEM) of 10 m resolution for a case watershed is resampled to six realizations of greater grid sizes for a comparative examination. The Universal Soil Loss Equation (USLE) and a distance-based sediment delivery equation are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams, respectively. The results suggest that the selection of the DEM gird size has considerable influence on the soil loss estimation with the empirical models. The estimate of total soil loss from the watershed decreases significantly with the increasing DEM cell size as the spatial variability is reduced by the cell aggregation. The empirical modeling approach is a useful tool for qualitative assessment of soil erosion, provided that spatial variability can be adequately represented by applied DEMs. However, discretion is suggested for its applications to quantitative estimation of soil loss concerning the sensitivity to the grid size selection.     

An approach to deal with uncertainty in energy and environmental planning: the MARKAL case

This paper presents a new concept to include uncertainty management in energy and environmental planning models developed in algebraic modeling languages. SETSTOCH is a tool for linking algebraic modeling languages with specialized stochastic programming solvers. Its main role is to retrieve from the modeling language a dynamically ordered core model (baseline scenario) that is sent automatically to the stochastic solver. The case presented herein concerns such a study realized with the IEAMARKAL model used by many research teams around the world.     

Issues in modeling induced technological change in energy, environmental, and climate policy

This paper addresses the objective of including Induced Technological Change (ITC) in research and policy models of energy, environment, and climate change. Theoretical foundations, fundamentals, and current methodologies for ITC models are reviewed. In addition, limitations and possible extensions to ITC models are explored. Current approaches to energy-environmental modeling that neglect technological characteristics such as heterogeneity, uncertainty, and path-dependence are likely to underestimate both the impact and the lags in the effectiveness of policy options.     

Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.     

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

Regulation of pesticide discharge into surface and groundwater under uncertainty: A model for environmental risk‐profitability tradeoffs and policy selection

The presence of contaminants in environmental media as well as the desire to maintain a high level of economic activity has led to an important and difficult decision‐making problem for both public policy decision makers and the general public. In one sense, all of the interested parties are likely to be concerned about the potential health risks posed by the presence of contaminants in environmental media and the need to design/implement policies for their mitigation and/or removal. At the same time, however, there also appear to be concerns about the cost of these policies. These costs could be measured in terms of the potential losses in economic activity that are likely to occur when a policy is adopted. The policy can be selected from a range of alternatives, with the choice being driven in part by the stakeholders represented in the policy decision problem. In this case, two general goals might be considered: minimizing environmental risk and minimizing the economic impact of the policy considered. These two objectives are likely to be viewed as conflicting goals, and the nature of the tradeoffs between them must be taken into account in the policy selection process. This paper presents the development of a zero–one weighted goal programming model that can be used to select a preferred policy that minimizes surface and groundwater contamination as well as the economic costs of environmental policy selection. A safety rule model is developed first and then extended to the zero–one weighted goal programming formulation. The stochastic aspects of these structures are emphasized throughout. The paper also addresses a number of issues related to implementation of the model.     

WARM: a European model for energy and environmental analysis

This paper describes the structure of a newly developed econometric, imperfectly competitive, general equilibrium model for the medium term study of energy and environmental problems. The geographical coverage of the model regards twelve European countries as well as the European Union as a whole. Compared to existing quantitative E3 (economy-energy-environment) models, the WARM model is characterized by a few novel and relevant features Firstly, in contrast to multicountry interlinked models, it copes with the international dimension by integrating differences from a common European denominator within a unified and homogeneously designed framework. A panel data estimation approach is used to achieve this objective. Secondly, in contrast to the traditional market-based philosophy of many econometric models, it adopts a perspective focused upon economic agents' decisions. Thirdly, in contrast with the practice of modelling technical progress as an exogenous and deterministic phenomenon, it incorporates an explicit attempt of modelling the sources and effects of endogenous technical change. A Kalman filter latent variable approach is the methodology from which statistical information on the dynamics of technical progress can be obtained. Finally, all markets in the model are imperfectly competitive, including the labour market where the wage bargaining process is explicitly modelled and estimated. This last feature is especially important in view of the European unemployment problem.     

Decomposition of energy consumption and its decoupling with economic growth in the global agricultural industry

The development of mechanization and technology has triggered the growing energy consumption in the agricultural industry. Energy saving in the agriculture industry becomes equally essential with that in the manufacturing, building, and transportation industries. The implementation of reducing energy consumption should be without costing the agricultural production, which is closely related to the food security of human beings. Strong decoupling between energy consumption and economic growth indicates the former decreases while the latter grows, which should be pursued by nations. Therefore, as the first research objective, this study analyzed the decoupling statuses between energy consumption and economic growth in the agricultural industry of 89 countries whose data exist across the period of 2000 to 2016. As a result, only 18 countries have reached strong decoupling. Secondly, this study decomposed agricultural energy consumption in the 89 countries to the effects of a driving factor (i.e., agricultural economic output) and three inhibiting factors (i.e., agricultural land, labor intensity, and energy intensity in descending order). With the identified decoupling statuses, this study provides a substantial understanding of the relationship between agricultural energy consumption and production from a global perspective. Meanwhile, the decomposed factors and corresponding policy implications provide evidence for decision makers of each nation to tailor energy-saving strategies in its agricultural industry.     

Renewable energy from gasification of manure: an innovative technology in search of fertile policy

After describing an innovative technology, the close-coupled gasification and cyclonic combustor, this article explores the policy issues that inhibit a superior sustainable solution fromflourishing. Discussion of technology includes defining biomass,explaining what biomass to energy means, what the advantages of biomass to energy are, and why gasification is a superior biomassto energy technology. Specifically the environmental benefits ofalternatives to landspreading of traditional manure management arediscussed, as well as the advantages of gasification versus traditional combustion techniques for high nitrogen fuels. The policy environment is explored, particularly regarding sustainability, manure management, and renewable energy. Artificial, non-sustainable barriers to renewable energy, and the impact of wide jurisdictional variability are discussed. North Carolina is identified as a unique jurisdiction to monitor because of its high volume of livestock manure, and laggard position in renewable energy advocacy. The authors contend that these two positions are unsustainable, and that pressures can beexpected to force the state to modify its renewable energy policies or risk losing market share in livestock production tomore pro-sustainable policy oriented states.     

Insights for climate policy in Europe

In this paper, the following key issues are addressed: the so-called “South” – the Group of 77 and China – and how to engage their interest and commitment; the purported savings if the flexible mechanisms are availed of, and the macro-economic impacts of meeting the Kyoto objectives; the associated issues of narrowing the extent and scope for such trading by setting a limit on how much can be traded, and “hot air” – the surplus quota above their own projected needs which Russia and most of the old Soviet Union have to offer; operational issues, including units to be traded, monitoring and enforcement, allocation of permits, competitiveness and risk management; in the case of emissions trading, the initial allocation of permits. This revised version was published online in July 2006 with corrections to the Cover Date.