Thermodynamic constraints and the use of energy-dependent CES-production functions A cautionary comment

Particularly in the context of energy and climate policy models, CES production functions are used as a basis for deriving sustainable development paths. Of crucial importance here is the reduction of the energy intensity of production processes with the help of substitution processes away from energy to other inputs. The modeling of these substitution processes must, of course, comply with the laws of physics. Therefore, the CES function is often used because it is supposed to satisfy thermodynamic laws. This is assumed to be met if the elasticity of substitution between energy inputs and other non-energy inputs is less than 1. The following commentary is meant to show that this specification is only a necessary pre-condition for fulfilling the thermodynamic laws. The permissible values of the other parameters of the CES- production function are subject to additional restrictions. Using an empirical example, the thermodynamic parameter restriction space for an aggregated production function of the English economy are presented. The consideration of thermodynamic limits can also be included directly into the design of production functions. An analysis of the linear-exponential production function derives various characteristics relevant to policy analysis. It is a priori not possible to decide which approach is preferable. Future empirical studies can help to clarify this question.     

Analyzing carbon pricing policies using a general equilibrium model with production parameters estimated using firm data

Policy simulation results of Computable General Equilibrium (CGE) models largely hinge on the choices of substitution elasticities among key input factors. Currently, most CGE models rely on the common elasticities estimated from aggregated data, such as the GTAP model elasticity parameters. Using firm level data, we apply the control function method to estimate CES production functions with capital, labor and energy inputs and find significant heterogeneity in substitution elasticities across different industries. Our capital-labor substitution elasticities are much lower than the GTAP values while our energy elasticities are higher. We then incorporate these estimated elasticities into a CGE model to simulate China's carbon pricing policies and compare with the results using GTAP parameters. Our less elastic K-L substitution leads to lower base case GDP growth, but our more elastic energy substitution lead to lower coal use and carbon emissions. In the carbon tax policy exercises, we find that our elasticities lead to easier reductions in coal use and carbon emissions.     

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.     

Alternative policy impacts on US GHG emissions and energy security: A hybrid modeling approach

This study addresses the possible impacts of energy and climate policies, namely corporate average fleet efficiency (CAFE) standard, renewable fuel standard (RFS) and clean energy standard (CES), and an economy wide equivalent carbon tax on GHG emissions in the US to the year 2045. Bottom–up and top–down modeling approaches find widespread use in energy economic modeling and policy analysis, in which they differ mainly with respect to the emphasis placed on technology of the energy system and/or the comprehensiveness of endogenous market adjustments. For this study, we use a hybrid energy modeling approach, MARKAL–Macro, that combines the characteristics of two divergent approaches, in order to investigate and quantify the cost of climate policies for the US and an equivalent carbon tax. The approach incorporates Macro-economic feedbacks through a single sector neoclassical growth model while maintaining sectoral and technological detail of the bottom–up optimization framework with endogenous aggregated energy demand. Our analysis is done for two important objectives of the US energy policy: GHG reduction and increased energy security. Our results suggest that the emission tax achieves results quite similar to the CES policy but very different results in the transportation sector. The CAFE standard and RFS are more expensive than a carbon tax for emission reductions. However, the CAFE standard and RFS are much more efficient at achieving crude oil import reductions. The GDP losses are 2.0% and 1.2% relative to the base case for the policy case and carbon tax. That difference may be perceived as being small given the increased energy security gained from the CAFE and RFS policy measures and the uncertainty inherent in this type of analysis.     

Political orientation,environmental values,and climate change beliefs and attitudes: An empirical cross country analysis

Based on unique data from representative computer-based surveys among more than 3400 citizens, this paper empirically examines the determinants of several climate change beliefs and attitudes in three countries which are key players in international climate policy, namely the USA, Germany (as the largest country in the European Union), and China. Our econometric analysis implies that political orientation in the USA is by far more relevant for general climate change beliefs and beliefs in anthropogenic climate change than in Germany and China. Furthermore, US and German citizens with a conservative, but not green identification significantly less often support publicly financed climate policy, while US and German respondents with a social–green identification and Chinese respondents belonging to the Communist Party have a significantly higher willingness to pay a price premium for climate-friendly products. However, our econometric analysis overall reveals that environmental values, which are measured by a New Ecological Paradigm (NEP) scale, are the major factors for climate change beliefs and attitudes in all three countries and thus play an even more dominant role than political orientation. In addition, environmental values weaken the differences in several climate change beliefs and attitudes between a right-wing and a left-wing identification. These interaction effects between political orientation and the NEP scale are especially strong in the USA, only relevant for the support of publicly financed climate policy in Germany, and negligible in China. Our estimation results suggest alternative strategies such as specific communication campaigns in order to reduce the climate change skepticism in conservative and right-wing circles in the USA and to increase the support of climate policies among such population groups.     

Projecting India's energy requirements for policy formulation

Energy policy has to have a long-term perspective. To formulate it one needs to know the contours of energy requirements and options. Different approaches have been followed in literature, each with their own problems. A top down econometric approach provides little guidance on policies, while a bottom up approval requires too much knowledge and too many assumptions. Using top-down econometric approach for aggregate overall benchmarking and a detailed activity analysis model, Integrated Energy System Model, for a few large sectors, provides a unique combination for easing the difficulties of policy formulation. The model is described in this paper. Eleven alternate scenarios are built, designed to map out extreme points of feasible options. Results show that even after employing all domestic energy resource to their full potential, there will be a continued rise of fossil fuel use, continued importance of coal, and continued rise of import dependence. Energy efficiency emerges as a major option with a potential to reduce energy requirement by as much as 17%. Scenario results point towards pushing for development of alternative sources.     

Engineering estimates versus impact evaluation of energy efficiency projects: Regression discontinuity evidence from a case study

Energy efficiency upgrades have been gaining widespread attention across global channels as a cost-effective approach to addressing energy challenges. The cost-effectiveness of these projects is generally predicted using engineering estimates pre-implementation, often with little ex post analysis of project success. In this paper, for a suite of energy efficiency projects, we directly compare ex ante engineering estimates of energy savings to ex post econometric estimates that use 15-min interval, building-level energy consumption data. In contrast to most prior literature, our econometric results confirm the engineering estimates, even suggesting the engineering estimates were too modest. Further, we find heterogeneous efficiency impacts by time of day, suggesting select efficiency projects can be useful in reducing peak load.     

Validating energy-oriented CGE models

Although CGE models have received heavy usage — particularly in the analysis of broad-based policies relating to energy, climate and trade, they are often criticized as being insufficiently validated. Key parameters are often not econometrically estimated, and the performance of the model as a whole is rarely checked against historical outcomes. As a consequence, questions frequently arise as to how much faith one can put in CGE results. In this paper, we employ a novel approach to the validation of a widely utilized global CGE model — GTAP-E. By comparing the variance of model-generated petroleum price distributions – driven by historical demand and supply shocks to the model – with observed five-year moving average price distributions, we conclude that energy demand in GTAP-E is far too price-elastic over this medium run time frame. After incorporating the latest econometric estimates of energy demand and supply elasticities, we revisit the validation question and find the model to perform more satisfactorily. As a further check, we compare a deterministic global general equilibrium simulation, based on historical realizations over the five year period: 2001–2006, during which petroleum prices rose sharply, along with growing global energy demands. As anticipated by the stochastic simulations, the revised model parameters perform much better than the original GTAP-E parameters in this global, general equilibrium context.     

A new robustness analysis for climate policy evaluations: A CGE application for the EU 2020 targets

This paper introduces a new method for stochastic sensitivity analysis for computable general equilibrium (CGE) model based on Gauss Quadrature and applies it to check the robustness of a large-scale climate policy evaluation. The revised version of the Gauss-quadrature approach to sensitivity analysis reduces computations considerably vis-à-vis the commonly applied Monte-Carlo methods; this allows for a stochastic sensitivity analysis also for large scale models and multi-dimensional changes of parameters. In the application, an impact assessment of EU2020 climate policy, we focus on sectoral elasticities that are part of the basic parameters of the model and have been recently determined by econometric estimation, alongside with standard errors. The impact assessment is based on the large scale CGE model PACE. We show the applicability of the Gauss-quadrature approach and confirm the robustness of the impact assessment with the PACE model. The variance of the central model outcomes is smaller than their mean by order four to eight, depending on the aggregation level (i.e. aggregate variables such as GDP show a smaller variance than sectoral output).     

Modelling the impacts of bioenergy markets on the forest industry in the southern United States

The main objective of this article was to analyse the impacts of emerging bioenergy markets on traditional forest product sector markets in the USA. An econometric model was developed to obtain the equilibrium estimates for the bioenergy and traditional forest markets. The results from the econometric model, using data-set for the state of Florida, suggested that biomass for bioenergy and pulpwood and biomass for bioenergy and sawtimber act as substitutes while sawtimber and pulpwood act as complements to each other. A price subsidy policy scenario was considered to simulate a 30% increase in the demand for biomass for bioenergy. The simulation results suggested that inclusion of this policy scenario might generate additional benefits to forest landowners and bioenergy sector, while sawmill and pulpmill sectors might face adverse financial impacts.     

Wide-range estimation of various substitution elasticities for CES production functions at the sectoral level

This paper provides a broad range of various substitution elasticity values for sectoral nested constant elasticity of substitution (CES) production functions, estimated through panel data techniques and using the World Input-Output Database (WIOD) as the main data source. Although the related empirical literature has been growing over the recent years, there is still no single study focused on a large-scale estimation of various, both product- and industry-specific, elasticities with the use of an internally consistent database and a common methodology for all the production function nests. This paper constitutes an attempt to fill this gap. The obtained estimates may subsequently be used by computable general equilibrium (CGE) modellers in their applied research – covering fiscal, labour market, trade, energy or environmental topics. Significant heterogeneity in the estimated elasticity values is observed between various industries/products as well as between various nests of the production function. This constitutes a strong argument against the arbitrary use of Leontief and/or Cobb-Douglas specifications in multi-sector CGE models.     

Prospective analysis of beyond Kyoto climate policy: a sequential game framework

This article proposes a sequential game methodology to analyse the long-term climate policy prospects. Players can sequentially choose the best policy, among a series of policy options, while reacting to past moves of the other players. In order to illustrate the game methodology, a numerical optimisation exercise is made, based on a simple integrated assessment model. The non-cooperative equilibrium arising from a five-stage sequential game with two large players (Annex B and non-Annex B regions), which tries to replicate the Kyoto and beyond Kyoto scenarios, is studied.     

Modelling the redirection of technical change: The pitfalls of incorporeal visions of the economy

This paper discusses attempts to represent the role of R&D in the transition towards a low carbon economy through models with no meaningful granularity to inform the studied phenomenon. By means of a critical analysis of (Acemoglu et al., 2012), we show that the advantage of these models, their analytical tractability, does not make up for their disadvantages, lack of control over policy implications and questionable numerical results. On the one hand, a comprehensive analysis of the results of Acemoglu et al. (2012) shows that even research subsidies do not pave the way for ambitious climate policies with low transitory costs, thus contradicting their policy message. On the other hand, critical parameters such as the elasticity of substitution between clean and dirty technologies, carbon sinks, or the productivity of researchers are not in accordance with existing scientific knowledge. We show that using more realistic parameters leads to even more pessimistic conclusions and that their model provides no leeway for overcoming them. We suggest that a too highly aggregated model can only describe an incorporeal economy and comes to a deadlock. We propose a more promising route for economic research in order to break this deadlock.     

基于CGE模型的东北亚能源互联网经济效益量化分析

东北亚地区的能源基础设施合作引起了很多学者的关注.大多数研究专注于该地区电网互联、可再生能源开发的技术可行性,而忽略了能源基础设施合作带来的社会和经济效益的定量分析.本研究使用可计算一般均衡模型来评估构建东北亚能源互联网的经济社会效益.主要模型工作包括 1)构建新的嵌套结构,2)通过计量模型估计化石和非化石能源发电替代...     

Inducing low-carbon investment in the electric power industry through a price floor for emissions trading

Uncertainty about long-term climate policy is a major driving force in the evolution of the carbon market price. Since this price enters the investment decision process of regulated firms, this uncertainty increases the cost of capital for investors and might deter investments into new technologies at the company level. We apply a real options-based approach to assess the impact of climate change policy in the form of a constant or growing price floor on investment decisions of a single firm in a competitive environment. This firm has the opportunity to switch from a high-carbon “dirty” technology to a low-carbon “clean” technology. Using Monte Carlo simulation and dynamic programming techniques for real data, we determine the optimal CO₂ price floor level and growth rate in order to induce investments into the low-carbon technology. We find that a carbon price floor can be used to induce earlier low-carbon technology investment and show this result to be robust to a large variety of input parameter settings.     

Economic and climate impacts of reducing China's renewable electricity curtailment: A comparison between CGE models with alternative nesting structures of electricity

To mitigate climate change impacts and achieve low-carbon transformation, China has accelerated the development of renewable energy, which is severely challenged by the curtailment of renewable electricity. This study uses a dynamic multi-sectoral CGE model with alternative nesting structures and substitution elasticities for electricity with different power sources to capture the economic and environmental feasibility of reducing renewable electricity curtailment across all economic sectors in China. The reduction of renewable electricity curtailment is simulated during 2021–2030 from the curtailment rates of 2015–2017. We found that the reduction of renewable electricity curtailment would lead to a significant expansion in the output of renewable electricity and a moderate decrease in non-renewable electricity production. Among the renewable electricity, wind power has the most significant output gain (over 9%), with solar power and hydropower outputs rising by over 5% and 1.5%, respectively. However, without the cost-neutrality assumption, the impacts of reducing electricity curtailment would be largely over-estimated with CGE models simulated by improved technology. The disparity between results from the models with alternative nesting constant elasticity of substitution (CES) functions for electricity sectors is highly dependent on the difference between their substitution elasticities. Accompanying the changes in electricity generation, the reduction of renewable electricity curtailment would bring multiple green co-benefits like significantly reducing CO2 and air pollutants emitted from electricity sectors, and improvements in real GDP and employment.     

Climate policy instruments and industry—effects and potential responses in the Swedish context

Efficient policy instruments for reducing the emission of greenhouse gases are essential for the realisation of a successful climate policy. General economic policy instruments have the potential for providing efficient emission reduction as they equalise marginal costs for emission reduction between different actors. They also provide incentives for a great variety of responses such as energy efficiency improvements, fuel substitution and reduced consumption of carbon intensive products. However, as a result of the fact that it has so far been impossible to implement policy instruments on a global scale, these instruments are often adapted in such a way that some of their potential advantages are eliminated.     

A model for sustainable land use in biofuel production: An application to the state of Alabama

The Renewable Fuel Standard aims to increase the production of biofuels to improve energy efficiency and decrease carbon dioxide emissions in the US. The effectiveness of this regulation is being debated by the scientific community regarding carbon emissions from direct and indirect land-use change. A valid alternative may be to design policies that stimulate sustainable land use in biofuel production. This article develops a model that simulates a voluntary program to increase the land use efficiency in production of biofuels. This stochastic dynamic model optimizes the sustainability of biofuels producible by including climate information and participatory decisions on land use. The model is parameterized using the Maximum Entropy econometric technique to present a simulation of the program in the State of Alabama. The results of this simulation show that participatory decisions on land-use may increase the net energy value of produced biofuel up to 215.68% and reduce the carbon emissions by 19.67% towards the state energy goals.