1.

2.

3.

The direct engineering and financial costs of specific technical measures. Examples include the cost of switching from coal to gas in electric production, of improving the thermal efficiency of existing homes, or of planting trees in reforestation programmes. Costs are normally reported in present value terms and can represent the life-cycle cost of the technique used or of the project (the up-front cost of the measures considered plus annual energy and operating costs, all reduced to a net present value or levellized costs). Technical costs can show negative net costs because a given technology may yield enough energy cost savings to more than offset the costs of adopting and using the technology. These costs depend upon both technico-economic data and a given interest rate and can be used to construct technology cost curves of the kind described in Figure 8.1. They can be calculated in the absence of any global scenario but, as such, they do not provide macroeconomic cost assessment unless they are fed into coherent technical and economic frameworks. They are the only source of information available for mitigation measures in sectors for which no comprehensive sectoral model has so far been developed.

[Figure 8.1]

Economic costs for a given sector. Here sectoral models are used to integrate sets of measures to provide consistent pictures of a given sector, and to compare the relative costs of different scenarios. These sectoral scenarios take some macroeconomic indicators, such as the overall rate of growth, as input parameters. They provide what is referred to as "partial equilibrium" analysis, in the sense that these sectoral models do not capture the feedback effects between the behaviour of a sector and that of the overall economy. To date, most sectoral analyses of mitigation costs have used energy sector models and forestry models. Other sectoral models, such as transportation or agriculture models, exist but have not yet been used so extensively for analysis of greenhouse gas mitigation.

Macroeconomic costs. These measure the impact of a given

strategy on the level of the gross domestic product (GDP) and its components (household consumption, investment, etc.). This aggregate index measures the monetary value added of goods and services produced in a single year and provides an index of the scale of human activities that pass through markets plus, by convention, the imputed value of some nonmarket activities (such as the value of services provided by public administration). At this level of cost analysis one tries to account for the interrelationships between a specific sector and the overall economy. This requires the use of either pure macroeconomic models or modelling frameworks coupling sectoral models and macroeconomic models in order to capture the changes throughout an economy caused by policies in a given sector (what is commonly labelled the "general equilibrium" effects, which are to be distinguished from the partial equilibrium (sectoral) effects).

4.

Welfare costs. GDP variations do not provide direct measures of human welfare. There are many reasons for this. First a climate policy may change the composition of GDP in the direction of higher investments and lower consumption. These changes are invisible to an analysis looking only at the level of GDP. Second, human welfare may not increase linearly with consumption, so consumption changes do not necessarily indicate commensurate changes in welfare. Third, changes in the level of GDP do not account for the relationship between distribution of income and overall welfare. Finally, environmental degradation reduces welfare but does not result in a corresponding reduction in GDP. The result of these factors is that even GDP does not include all costs of interest, and even general equilibrium models that attempt to measure welfare costs do not include all costs that matter.

The four types of costs outlined here represent increasing levels of generality as one moves from direct financial costs to welfare costs. However, the different levels of cost cannot be aggregated or correlated in any systematic way. For example, ranking efficient technologies in terms of their individual price in the marketplace (direct engineering and financial costs) does not usually reveal the way these technologies will be actually adopted and combined in an economically consistent productive system. For example Thus, a given energy efficiency improvement may not be rationally selected if this improvement occurs in a period of time when the electric supply is in excess. Similarly, a sectoral optimization of a very capital-intensive sector may not give results consistent with some form of overall macroeconomic optimum. For example, the amount of money spent in optimized energy supply or transportation systems may prevent investment in other sectors such as education and health. On the other hand, aggregate macroeconomic analysis of costs may not capture important changes to the extent that these changes remain below the level of "noise" of analysis and are not captured by historical variation in the aggregate variables. This typically occurs with respect to the agricultural sector, for example, which represents a small part of overall GDP but often plays a decisive role in the social and spatial equilibrium of a society.

Existing studies use a variety of methodological approaches and definitions of cost to assess the costs of mitigating greenhouse gas emissions. No existing study provides a complete evaluation of full social costs. Instead, studies provide a range of cost estimates: some provide estimates of the direct financial costs of specific technological options; others provide estimates of the effect of broad policies on aggregate economic activity; still others attempt to estimate welfare costs. It is important to be clear about which type of cost is being estimated in any specific study.

Despite these differences, progress has been made in incorporating successively broader concepts of costs in greenhouse gas mitigation studies and in accounting for the possibility of significant technological and behavioural change. Two more general problems, however, remain.

The first lies in the fact that, in a number of developing countries and Central and Eastern European countries, the level of government intervention or market distortion (which exists also in OECD countries but not to the same degree) may interfere inwith the absolute and relative prices of goods and services. This results in distortions between observed market prices of technologies and their "shadow prices" assessed "at factor costs" which would reflect the actual balance between human capabilities, technical potentials, natural resources scarcity, and final needs within a given economy. Te use The use of market prices is relevant for assessing the likeliness of the adoption of some technical alternatives for a given institutional context, but if these costs are interpreted as capturing the overall social costs of a given measure, they conceal some intrinsic costs of goods and services and can be very misleading.

It is more difficult, empirically and theoretically, to pass from GDP costs to welfare costs. In most empirical models, welfare cost measures are calculated as the income required to leave a typical household no worse off after a tax than before. In models devoted to analyzing the short-term impact of taxation policies, welfare costs are calculated on the basis of the so-called "Harberger triangle," which demonstrates that welfare losses grow at a higher rate than increases in taxes. These results, however, are not complete measures of welfare costs. In the first place, they generally do not account for the dynamic effects of important policy measures on technology and consumer preferences. In the second place, they depend on market product calculations and do not account for the goods and services produced by nonmarket and informal economies.

In fact, much work remains to be done in attempting to incorporate broader conceptions of human welfare (such as those that are suggested in the United Nations Development Programme's Human Development Index), and most of the models reported hereafter ignore such factors. The consequence is that the cost figures provided by current economic modelling studies must be strictly interpreted as estimates of losses (or gains) in the value of new final goods and services foregone as a consequence of the policy, not as estimates of impacts on overall welfare.

Of course, the different kinds of cost estimates discussed here are of great value; the point is simply that, before drawing policy-relevant conclusions from even the most general analyses of macroeconomic costs, it is important also to examine other indicators (e.g., unemployment, distribution of income, security, and political stability).

8.2.2.1 Gross Costs, Net Costs, and the Overall Cost-Benefit Balance of Mitigation Strategies

In assessing the costs of mitigation, it is first important to make a distinction between what economists call the gross costs and the net costs of mitigation strategies. The two are different to the extent that there are possible positive side effects of mitigation strategies that would offset some of the gross costs. These positive side effects can be divided into three categories:

1.

2.

3.

the negative cost potential, namely mitigation caused by technologies whose costs are lower than the technologies currently in use. As discussed further in Section 8.4 below, this issue is controversial, since it implies that there are cost-effective mitigation strategies that are not now in use and that will not be adopted in the absence of new policies. Such measures would have a negative net cost and obviously lower the gross cost of greenhouse gas mitigation for a given target;

an economic double dividend, such as the possible positive effects on growth or employment of the recycling of carbon tax revenues or of the technological externalities (i.e., side effects) associated with fostering research and development programmes;

an environmental double dividend, namely the synergy between greenhouse gas mitigation strategies and the mitigation of other environmental nuisances such as local air pollution, urban congestion, or land and natural resource degradation, such that greenhouse gas mitigation also contributes to reducing these other problems.

The existence of such positive side effects within a suite of mitigation measures would result in lowering the gross cost of these measures. To the extent that such positive side effects may totally offset the gross costs of a specific emission strategy, then-they represent what has been called a "no-regrets potential": measures that are worth undertaking whether or not there are climate-related reasons for doing so. However, as discussed below, there is much controversy about the existence and magnitude of these positive side effects. The point here is simply that, from the point of view of greenhouse gas mitigation policy, what matters is the net costs of mitigation strategies, that is, gross costs minus any positive side effects.

To avoid any possible misunderstanding, it must be emphasized that the double dividend positive side effects described here are not the same as, and should not be mistaken for, the benefits of mitigation policies (or costs of climate change), which are discussed in Chapter 6 above. Instead, these positive side effects represent items that lower the total cost of mitigation policies, and it is the resulting net cost figure (gross cost minus positive side effects) which is to be compared with the benefits of mitigation policies (whether these benefits are accounted for in terms of explicit monetary values or purely normative mitigation targets)."

Many current economic models account for the first and/or the second category of positive side effects; very few account for positive environmental externalities. This is mainly due to practical reasons, and one can expect quick improvement in this direction in the near future. In the meantime, it is useful to remember that the studies discussed in this chapter do not include this category of secondary benefit.

8.23 Key Factors Affecting the Magnitude of Costs: Costs as a Function of Baselines and Policy Strategies

The above taxonomy suggests that assessing the costs of greenhouse gas mitigation strategies is not equivalent to adding up the direct costs of individual measures or policies. The cost of mitigation is always a net incremental cost (or a marginal cost) relative to a given scenario - usually called a baseline scenario. This means that the calculation of these net costs is determined in large part by both the assumptions underlying such baseline scenarios and the assumptions about mitigation policies.

8.2.3.1 Baselines and magnitude of the "no-regret" potentials

The most sensitive issue in the debates about how to interpret the results of the models is the way assumptions about the existence and the size of potentials for so-called "noregret strategies" are conveyed in specific modelling frameworks and baseline scenarios.

The discussion of "no-regrets" potential has triggered a sensitive policy debate which can be summarized rather simply, though rather abstractly, in graphical form (see Figure 8.2). To begin, we represent the whole economy as producing two sets of goods and services: (1) a composite good Q, namely an aggregate of all existing goods and services, and (2) a given level of environmental quality E, represented in this case by a certain amount of emission reductions. Given such an assumption, it is possible to construct a curve F(Q,E), called a theoretical production frontier by economists, which represents the trade-off between economic activity (Q) and emission reduction (E). For a given economy at a given time, each point on this curve shows the maximum size of the economy for each level of emission reduction; put another way, it shows the maximum emission reduction for each level of economic activity. If the economy is at a size and level of emission reduction that is below and to the left of this curve (e.g., point O in Figure 8.2), it is possible for that economy to move upwards (e.g., from O to B), producing more goods without increased emissions, or to move rightwards (e.g., from O to A), reducing emissions without reducing the size of the economy, or to move somewhere in between, increasing both economic activity and emissions reduction.

[Figure 8.2]

From the point of view of cost analysis, a key consideration is what is assumed about the location of the reference or baseline scenario with respect to this curve. If the baseline scenario assumes the economy to be located somewhere on the theoretical production frontier (curve F), it is clear that there is a direct and unavoidable trade-off between economic activity and the level of emissions. In effect, all increases in emission reduction (moving down the surface of the curve to the right) will decrease economic activity (i.e., increase costs). That is, there is no no-regrets potential: moving up to the left on the curve will increase economic activity but also increase emissions. In such a