Elsevier

Energy Policy

Volume 37, Issue 4, April 2009, Pages 1395-1403
Energy Policy

Marginal abatement costs of greenhouse gas emissions: A meta-analysis

https://doi.org/10.1016/j.enpol.2008.11.040Get rights and content

Abstract

In this paper, we carry out a meta-analysis of recent studies into the costs of greenhouse gas mitigation policies that aim at the long-term stabilisation of these gases in the atmosphere. We find the cost estimates of the studies to be sensitive to the stringency of the stabilisation target, the assumed emissions baseline, the way in which the time profile of emissions is determined in the model, the choice of control variable (CO2 only versus multigas), the number of regions and energy sources in the model and, to a lesser degree, the scientific “forum” in which the study was developed. We find that marginal abatement costs of the stringent long-term targets that are currently considered by the European Commission are still very uncertain but might exceed the costs that have been suggested by recent policy assessments.

Introduction

Climate change continues to be high on the political agenda, and politicians sometimes seem to be engaged in a bidding war about who dares to propose the most ambitious target. Although in the public debate much emphasis is placed on the potential damage costs of unchecked climate change, a policy to mitigate climate change by reducing the emissions of greenhouse gases also bears costs. The study of abatement costs can be confusing to the uninitiated because many studies have produced a wide range of estimates and these estimates are dependent on a number of key assumptions that are not always well documented. Therefore, this paper seeks to clarify the assessment of marginal cost of greenhouse gas emission reduction by means of a meta-analysis of recent estimates.

In recent years, many research teams have developed computer-based economic models that have computed marginal abatement costs (MAC) of greenhouse gas (GHG) emissions that are consistent with long-term climate policy targets, in terms of maximum concentrations or temperature increases. It is possible to interpret these MAC as carbon permit prices in an idealised global emissions trading system that allows the participants maximum “where” flexibility, and in some models also “what” and “when” flexibility. This means that MAC are equalised across all sources (“where” flexibility), and that in some models MAC change over time according to some intertemporal optimisation rule (“when” flexibility), and MAC of abating different greenhouse gases are equalised, taking into account their relative warming potentials and different lifetimes (“what” flexibility).

We collected information from 26 different models that were presented in three so-called modelling fora in 2006. A modelling forum is a meeting or a series of meetings of modelling groups that address a common research question, and that use a commonly agreed set of assumptions and a common reporting format. One of the oldest of such fora is the Energy Modeling Forum (EMF) that was established at Stanford University in 1976 to provide a structured forum for discussing important energy and environmental issues. For this study, we used the results of the models that participated in EMF-21 that specifically addressed “what” flexibility (i.e., trade-offs between different greenhouse gases) (Weyant et al., 2006). We also used results of the models that participated in the Innovation Modeling Comparison Project (IMCP) that specifically addressed the potential impact of the induced technical change on long-term abatement and abatement costs (Edenhofer et al., 2006), and the US Climate Change Science Program (USCCSP) that addressed all these issues (Clarke et al., 2006).

The different assessment models produce varying estimates of MAC. The first aim of the analysis presented in this paper examines the sensitivity of MAC estimates to the specifications and assumptions underlying these models. Among other factors, we examine the influence on MAC of stabilisation targets, baseline emissions, the inclusion of other GHGs in addition to CO2 in the emissions target, and induced technological change.

By conducting a meta-analysis of model results we aim to identify the key factors that drive the results. In addition to providing a statistical synthesis of model outcomes, the meta-regression function can also be used to predict MAC given specific values for explanatory variables included in the regression. Thus, the second aim of this paper is to predict MAC (or MAC ranges) for alternative stabilisation targets for greenhouse gas concentrations.

A number of existing studies provide syntheses of MAC estimates and analyse the influence of modelling assumptions. The meta-analysis in this paper uses more up-to-date model results than previous research (Barker et al., 2002; Fischer and Morgenstern, 2005; Repetto and Austin, 1997). This paper uses the same model results as Barker et al. (2006b), but many more in addition. Where useful, we compare our results with those of earlier studies.

The structure of this paper is as follows. Section 2 introduces the concept of long-term stabilisation targets for greenhouse gas emissions in the atmosphere. Section 3 presents the meta-analysis research methodology used in this paper. Section 4 describes the data. Section 5 presents the results of the meta-analysis, while Section 6 concludes.

Section snippets

Stabilisation targets

The ultimate objective of the United Nations Framework Convention on Climate Change (UNFCCC) is the “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved within a time-frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner”

Research approach: meta-analysis

Meta-analysis is a statistical technique to combine the results of several studies that address a set of related research hypotheses. Meta-analysis extends beyond a standard literature review by analysing and synthesising the results of multiple studies in a statistical manner (Nelson and Kennedy, 2008; Stanley, 2001).

In this paper, meta-analysis is used to examine whether modelled estimates of MAC are dependent upon some key modelling assumptions and structural characteristics of the models.

Description of the database

The 26 models in our database provided “observations” of MAC for different points in time. We collected 62 observations of MAC for the years 2025 and 2050. We normalised these observations that are expressed in different dimensions and currencies into 2005 Euros per tonne of CO2 (€2005/tCO2-eq). For normalisation, we used consumer price indices (CPI) from the OECD to convert all prices to a common year (2005), market exchange rates from OECD to convert all currencies to a common currency (Euro,

Meta-regression and prediction

We estimated double-log regression equations for the years 2025 and 2050. In both equations, the log of MAC is the dependent variable that is regressed on the logs of stabilisation target (Target), baseline emissions (Baseline), regions (Regions) and energy sources (Energysources), and dummies for multigas (Multigas), induced technical change (ITC), Top-Down (TopDown), intertemporal dynamic optimisation (IDO), Carbon Capture and Storage (CCS), and the fora “IMCP” (IMCP) and “USCCSP” (USCCSP).

Conclusions and discussion

We have analysed information on MAC from 62 recent studies that assessed the economic impacts of meeting long-term stabilisation targets of greenhouse gases in the atmosphere. All the studies computed a least-cost trajectory of global abatement efforts to meet such a target. The MAC assessed by these studies were shown to depend on the stringency of the stabilisation target, the emissions baseline, the time profile of the emissions reductions (intertemporal dynamic optimisation), the choice of

References (48)

  • C. Böhringer et al.

    Efficiency gains from “what”-flexibility in climate policy

    An Integrated CGE Assessment. The Energy Journal Special Issue on Multi-Greenhouse Gas Mitigation and Climate Policy

    (2006)
  • V. Bosetti et al.

    The dynamics of carbon and energy intensity in a model of endogenous technical change

    The Energy Journal Special Issue on Endogenous Technological Change and the Economics of Atmospheric Stabilisation

    (2006)
  • Clarke, L.E., Edmonds, J.A., Jacoby, H., Pitcher, H., Reilly, J.M., Richels, R.G., 2006. CCSP synthesis and assessment...
  • R. Crassous et al.

    Endogenous structural change and climate targets modeling experiments with Imaclim-R

    The Energy Journal Special Issue on Endogenous Technological Change and the Economics of Atmospheric Stabilisation

    (2006)
  • EC, 2007. Limiting global climate change to 2°C. The way ahead for 2020 and beyond. Impact Assessment Summary,...
  • O. Edenhofer et al.

    Induced technical change: exploring its implications for the economics of atmospheric stabilization: synthesis report from the innovation modeling comparison project

    The Energy Journal: Endogenous Technical Change and the Economics of Atmospheric Stabilisation

    (2006)
  • M.G.J.d. Elzen et al.

    Exploring European Countries’ Emission Reduction Targets, Abatement Costs and Measures Needed Under the 2007 EU Reduction Objectives

    (2007)
  • A.A. Fawcett et al.

    Non-CO2 greenhouse gases in the second generation model

    The Energy Journal Special Issue on Multi-Greenhouse Gas Mitigation and Climate Policy

    (2006)
  • C. Fischer et al.

    Carbon Abatement Costs: Why the Wide Range of Estimates?

    (2005)
  • B.S. Fisher et al.

    Issues related to mitigation in the long term context

  • J. Fujino et al.

    Multi-gas mitigation analysis on stabilization scenarios using aim global model

    The Energy Journal Special Issue on Multi-Greenhouse Gas Mitigation and Climate Policy

    (2006)
  • R. Gerlagh

    ITC in a global growth-climate model with CCS: the value of induced technical change for climate stabilization

    The Energy Journal Special Issue on Endogenous Technological Change and the Economics of Atmospheric Stabilisation

    (2006)
  • D.A. Hanson et al.

    Technology policy and world greenhouse gas emissions in the Amiga modeling system

    The Energy Journal Special Issue on Multi-Greenhouse Gas Mitigation and Climate Policy

    (2006)
  • F. Hedenus et al.

    Induced technical change in a limited foresight optimization model

    The Energy Journal Special Issue on Endogenous Technological Change and the Economics of Atmospheric Stabilisation

    (2006)
  • Cited by (100)

    • Considering environmental costs of greenhouse gas emissions for setting a CO<inf>2</inf> tax: A review

      2020, Science of the Total Environment
      Citation Excerpt :

      At the EU level, not only is there a target for 2050, but an interim target also exists. Without further analyses, however, it cannot be concluded whether the value by Kuik et al. (2009) for 2025 corresponds to the EU's medium-term target. Due to lack of alternative data, it is adopted below.

    • Cost-benefit analysis

      2020, Advances in Transport Policy and Planning
    View all citing articles on Scopus
    View full text