Working Group III: Mitigation

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Executive Summary

Using resources to mitigate greenhouse gases (GHGs) generates opportunity costs that should be considered to help guide reasonable policy decisions. Actions to abate GHG emissions or increase carbon sinks divert resources from other uses like health care and education. Assessing these costs should consider the total value that society attaches to the goods and services forgone because of the diversion of resources to climate protection. In some cases, the benefits of mitigation could exceed the costs, and thus society gains from mitigation.

This chapter addresses the methodological issues that arise in the estimation of the monetary costs of climate change. The focus is on the correct assessment of the costs of mitigation measures to reduce the emissions of GHGs. The assessment of costs and benefits should be based on a systematic analytical framework to ensure comparability of estimates and transparency of logic. One well-developed framework assesses costs as changes in social welfare based on individual values. These individual values are reflected by the willingness to pay (WTP) for environmental improvements or their willingness to accept (WTA) compensation. From these value measures can be derived measures such as the social surpluses gained or lost from a policy, the total resource costs, and opportunity costs.

While the underlying measures of welfare have limits and using monetary values remains controversial, the view is taken that the methods to “convert” non-market inputs into monetary terms provide useful information for policymakers. These methods should be pursued when and where appropriate. It is also considered useful to supplement this welfare-based cost methodology with a broader assessment that includes physical impacts when possible. In practice, the challenge is to develop a consistent and comprehensive definition of the key impacts to be measured. In this chapter the costing methodology is overviewed, and issues involved in using these methods addressed.

The costs of climate protection are affected by decisions on some key elements, the analytical structure, and the assumptions made. Among other key presumptions, these include the definition of the baseline, assumption about associated costs and benefits that arise in conjunction with GHG emission reduction policies, the flexibility available to find the carbon emissions of lowest cost, the possibility of no regret options, the discount rate, the assumption of the rate of autonomous technological change, and whether revenue is recycled.

First, defining the baseline is a key part of cost assessment. The baseline is the GHG emissions that would occur in the absence of climate change interventions. It helps determine how expensive GHG emissions reduction might be. The baseline rests on key assumptions about future economic policies at the macroeconomic and sectoral levels, including structure, resource intensity, relative prices, technology choice, and the rate of technology adoption. The baseline also depends on presumptions of future development patterns in the economy, like population growth, economic growth, and technological change.

Second, climate change policies may have a number of side-impacts on local and regional air pollution associated, and indirect effects on issues such as transportation, agriculture, land use practices, employment, and fuel security. These side-impacts can be negative as well as positive and the inclusion of the impacts then can tend to generate higher as well as lower climate change mitigation costs compared with studies that do not include such side-impacts.

Third, for a wide variety of options, the costs of mitigation depend on the regulatory framework adopted by national governments to reduce GHGs. The more flexibility allowed by the framework, the lower the costs of achieving a given reduction. More flexibility and more trading partners can reduce costs, as a firm can search out the lowest-cost alternative. The opposite is expected with inflexible rules and few trading partners.

Fourth, no regrets options are by definition actions to reduce GHG emissions that have negative net costs. Net costs are negative because these options generate direct or indirect benefits large enough to offset the costs to implement the options. The existence of no regrets potential implies that people choose not to exercise some carbon-reducing options because of relative prices and preferences, or that some markets and institutions do not behave perfectly. The presumption of effective policies that capture large no regrets options reduces costs.

Fifth, there are two approaches to discounting—an ethical or prescriptive approach based on what rates of discount should be applied, and a descriptive approach based on what rates of discount people (savers as well as investors) actually apply in their day-to-day decisions. For mitigation analysis, the country must base its decisions at least partly on discount rates that reflect the opportunity cost of capital. Rates that range from 4% to 6% would probably be justified in developed countries. The rate could be as high as 10%–12% in developing countries. It is more of a challenge to argue that climate change mitigation projects should face different rates, unless the mitigation project is of very long duration. Note that these rates do not reflect private rates of return, which typically must be greater to justify a project, at around 10%–25%.

Sixth, modellers account for the penetration of technological change over time through a technical coefficient called the “autonomous energy efficiency improvement” (AEEI). AEEI reflects the rate of change in the energy intensity (the ratio of energy to gross domestic product) holding energy prices constant. The presumed autonomous technological improvement in the energy intensity of an economy can lead to significant differences in the estimated costs of mitigation. As such, many observers view the choice of AEEI as crucial in setting the baseline in which to judge the costs of mitigation. The costs of mitigation are inversely related the AEEI–a greater AEEI the lower the costs to reach any given climate target. The costs decrease because people adopt low-carbon technology unrelated to changes in relative prices.

Other issues to be considered in the assessment of mitigation policies include the marginal cost of public funds, capital costs, and side effects. Policies such as carbon taxes or auctioned (tradable) carbon-emissions permits generate revenues that can be recycled to reduce other taxes that are likely to be distortionary. There has been considerable debate as to whether such revenue recycling might eliminate the economic costs of such mitigation policies. Theoretical studies indicate that this result can occur in economies with highly inefficient tax systems. Some empirical studies obtain the no-cost result, although many such studies do not. Tax recycling reflects several complicated assumptions in the baseline and policy case regarding the structure of the tax system and the overall policy framework, among others. Target setting and timing also affect cost estimates. Reduction targets defined as percentage reductions of future GHG emissions create significant uncertainty about GHG emission levels.

In addition, several issues on technology use in developing countries and economies in transition (EITs) warrant attention as critical determinants for climate change mitigation potential and related costs. These include current technological development levels, technology transfer issues, capacity for innovation and diffusion, barriers to efficient technology use, institutional structure, and human capacity aspects.

Equity is another issue in evaluating mitigation policies. The use of income weights is one approach to address equity. Under this system each dollar of costs imposed on a person with low income is given greater weight relative to the cost for a person with a high income. This method is, however, controversial and it is difficult to obtain agreement on the weights to be used. An alternative method is to report the distributional impacts separately. In this case it is important that all the key stakeholders are identified and the distributional effects on each reported. A third possibility is to use average damage estimates and apply these to all those impacted, irrespective of their actual WTP.

Given these presumptions on structure, the costs of climate protection can be modelled and assessed at three levels:

  • Project level analysis estimates costs using “stand-alone” investments assumed to have minor secondary impacts on markets.
  • Sector level analysis estimates costs using a “partial-equilibrium” model, in which other variables are presumed as given.
  • Macroeconomic analysis estimates costs by considering how policies affect all sectors and markets, using various macroeconomic and general equilibrium models. The modeller confronts the trade-off between the level of detail in the cost assessment and complexity of the system. For example, a macroeconomic system tries to capture all direct and indirect impacts, with little detail on the impacts of specific smaller scale projects.

Modelling climate mitigation strategies can be done using several techniques, including input–output models, macroeconomic models, computable general equilibrium models, and models based on the energy sector. Hybrid models have also been developed to provide more detail on the structure of the economy and the energy sector. Two broad classes of integrated assessment models can be identified: policy optimization models and policy evaluation models. The appropriate use of these models depends on the subject of the evaluation and the availability of data.

Finally, the main categories of climate change mitigation policies include market-oriented, technology-oriented, voluntary, and research and development (R&D) policies. Climate change mitigation policies can include elements of two or more policy options. Economic models, for example, mainly assess market-oriented policies and in some cases technology policies, primarily those related to energy supply options. In contrast, engineering approaches mainly focus on supply and demand-side technology policies. Both approaches are relatively weak in the representation of R&D policies.

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