Select Committee on Economic Affairs Minutes of Evidence

Annex 3

Costs of Mitigation

  Economic analyses tend to produce differing estimates on the economic implications of policies aimed at greenhouse gas (GHG) mitigation. The main reasons appear to relate to differences in underlying modelling approaches, in specific assumptions being adopted and in policy scenarios being simulated.

  There are broadly three types of modelling approach that have been used to consider the costs of emission reductions. They are:

    (i)  Macroeconomic. These models are generally very country specific. They may allow for supply and demand to be out of balance (for markets not to clear). Hence, they are probably best suited to the consideration of the dynamics of transition towards lower carbon futures and for applications in the short to medium term. Results, in terms of GDP response, show considerable variation across models—they can be very model-dependent, according to the particular assumptions employed.

    (ii)  General equilibrium. These models assume that markets clear (ie that demand always equals supply). They cannot address transitional costs, but are better suited to long run estimates, on the basis that in the long-run resources are re-deployed and the economy reverts towards long-run trends.

    (iii)  Bottom-up. These models will tend to represent technology and energy efficiency from a detailed set of choices. The model will choose the technologies to deploy depending, in particular, on their costs and the costs of energy inputs. Depending on the particular model it may be possible to constrain the choices in some way. But in general, like general equilibrium models, this type of approach is better suited to consideration of long-run impacts than transitional costs. The MARKAL model we have used is one version of a bottom-up model.

  It is generally considered that models of types (i) and (ii), may overestimate costs. They start from a position that deployment of resources in the base case is optimal. Such an approach is criticised for underestimating the potential for low cost efficiency improvement and ignoring gains that may be tapped by non-price policy change. Worst case results come from models using macro-economic models, with lump sum recycling of revenues, no emission trading and no non-carbon backstop technology.

  Bottom up models of type (iii), on the other hand, assume that there is a lot of low or nil cost technology or energy efficiency potential. Estimates from such models can be criticised for under-estimating costs on the basis that they ignore various hidden costs, transaction costs or other constraints that in practice limit the take-up of what are, otherwise, cost-effective technologies.

  In terms of specific assumptions and policy scenarios, there are several factors that help explain differences in cost estimates, including:

    —    Choice of baseline emission scenarios;

    —    Different estimates/assumptions on the elasticity of substitution between different fuels and technologies;

    —    Scope for international permit trading; which help drive down costs by allowing firms to reduce emissions in the most efficient way; [21]

    —    If/how revenues from carbon taxes are used to reduce distortionary taxes elsewhere in the economic system, for example, reducing social security payments or if the revenues are used to provide consumers with lump-sum repayments;

    —    The time horizon over which mitigation targets may be achieved;

    —    The possibility of win-win policies and low cost outcomes through increased energy efficiency uptake;

    —    The role of further ancillary benefits (for example, improvements in air quality and subsequent reduction in health related illnesses).

  In spite of these drivers of variation, we have a relatively good idea of at least the order of magnitude of economy-wide costs of mitigation action. Both IPCC's assessment and analysis by the UK Government for the Energy White Paper suggest that the deep cuts needed to put us on a path to stabilisation compatible with limiting eventual temperature rise to 2ºC at around 500 ppm need not be large—of the order 0.5 to 2 per cent GDP over 50 years—a delay of a few months in reaching a particular level of GDP.

  It should be clarified that although economy-wide costs are unlikely to be prohibitive this does not mean that reducing emissions is going to be easy: industry will face great engineering challenges as a wide range of technologies (from renewables, to energy conservation, carbon capture and storage, hydrogen production and decentralised energy networks) need to be developed further.

  Keeping the cost manageable depends on the steady introduction of measures, starting from now, which is why the UK has a long-term policy. If we tried to get say 60 per cent cuts in CO2 over a few years rather than the period to 2050, costs would become much larger. Also, the risk if no early action is taken is one of "lock-in" into an energy system that is highly reliant on fossil fuels, which would make the transition to a low carbon economy at a later stage (when the most worrying climate change scenarios may well have been confirmed) extremely expensive or even impossible.

  A further caveat is that manageable economy-wide costs can disguise higher costs for some sectors of the economy—energy intensive industries for example. Careful policy design ensures that the costs of taking action are fairly distributed across the economy, taking account of what particular sectors can achieve, given the technologies available. UK policy seeks to achieve this, eg by flexible mechanisms such as emissions trading.

  Finally, an important issue that has only recently begun to be addressed by the economic models of climate change policy is the role of the technological change that may be induced by the adoption of mitigation policies (as opposed to models assuming cost-reduction purely following precedents). According to several models policy-induced technological change can make a significant difference to cost estimates. For example, a recent literature review by the Pew Center[22] concluded that technological change induced by early action aimed at reducing emissions may significantly reduce the ultimate costs of mitigation policies. The Pew Center report goes on to recommend that the level of abatement should then increase over time following the cumulative nature of technological change. Defra is currently sponsoring a Cambridge-led Innovation Modelling Comparison project on this issue, involving a large group of modelling teams from Europe and beyond. Preliminary results should be available in the spring.


  There are numerous examples from business that suggest that significant reductions in emissions can be achieved at zero or negative cost. Since 1990, through its aggressive actions to save energy IBM has avoided 8.45 million tonnes of CO2 emissions and achieved operating cost savings of $791.4 million. IBM reduced global GHG emissions associated with energy consumption by 65.8 per cent between 1990 and 2003 (35.4 per cent due to energy conservation. In 1998, BP set itself the target of reducing its greenhouse gas emissions by 10 per cent within 12 years. It achieved this goal inside just three years (Absolute reduction 18 per cent). The company integrated emissions targets into its senior managers' performance contracts. It also introduced an innovative emissions trading scheme to minimise cost. The programme cost the company $20 million to implement, but saved it $650 million over the three year period. Executives are confident that there is at least another $650 million in value to be realised.


  Many economists would agree that in theory decision-making frameworks that look at climate policy choices as a problem of sequential decision-making under uncertainty are preferable to deterministic cost-benefit analyses. Typically these decision-making frameworks allow for "learning", ie the possibility of acquiring new information on the climate change problem, which tends to reduce uncertainty over time. Some have argued that the benefit of acquiring new, better information is an argument for delaying irreversible investment to reduce greenhouse gas emissions. But the risk of committing resources to irreversible investment in low carbon technology should be compared and contrasted to the symmetrical risk of a "lock-in effect" into an energy-economy system that relies excessively on fossil fuels. Also, a strategy of waiting to learn more on the risks of climate change is likely to reduce the opportunity of "learning by doing" through investment in low-carbon technology.

  A good review of the relevant theoretical empirical literature is provided by Alistair Ulph and Alan Ingham (Ulph and Ingham, 2003). [23]Most of the studies reviewed by Ulph and Ingham suggested that the prospect of getting better information at some point in the future should lead to a small reduction in current mitigation efforts. However, Ulph and Ingham stress that these results are very much dependent on specific model assumptions. Furthermore, none of the empirical studies led to the recommendation of "doing nothing" as a short-term strategy.

21   The EU ETS is a tangible illustration of using such flexible mechanisms in order to allow firms to meet their emission reduction commitments in the most cost effective and efficient way. Back

22   LH Goulder, "Induced technological change and climate policy". Prepared for The Pew Center on Global Climate Change, October 2004. Back

23   see Back

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