IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group III: Mitigation of Climate Change A comparison of the macro-economic costs of mitigation to 2030 from modelling studies

Since the TAR, groups of modellers have found a reduction in expected macro-economic costs as a result of the use of multigas options (EMF21, Weyant et al., 2006) (see Section and because carbon prices affect technological change in the models (EMF19, IMCP) (see Section 11.5). Figure 11.7 summarizes the 2030 data brought together in these studies as well in as other post-TAR Category III (stabilization at around 550ppm CO2-eq) studies covered in Chapter 3.[11] The figure is in 3 parts, showing (a) the carbon prices in US$(2000) by 2030 (typically a rising trend) and their effects on CO2 emissions, (b) the effects of CO2 abatement on GDP, and (c) the relationship between carbon prices and gross world output (GDP). All data are differences from the baseline projections for 2030. The studies are grouped around two of the stabilization categories set out in Chapter 3 (Table 3.5), with corresponding insights.

Figure 11.7

Figure 11.7: Year 2030 estimated carbon prices and gross-world-product (GDP) costs of various pathways to stabilization targets

Notes: Figure 11.7 shows, for 2030, the carbon price, CO2 abatement relative to the baseline, and global GDP differences from baseline for five different sets of stabilization studies: EMF21 radiative forcing at 4.5 W/m2 (multigas); IMCP at 550 and 450ppm (CO2-only with induced technological change); EMF19 at 550ppm (CO2-only with induced technological change) and 6 studies in category III included in Figure 3.24. The results as shown exclude incomplete sets (i.e. data have to be available for all three variables shown). The EMF21 results exclude studies unsuitable for near-term analysis (e.g. substantial effects for a past year). The IMCP results exclude those from two experimental/partial studies. The breakdown into Category III and IV scenarios treats CO2-only studies as if they also allow for cost-effective non-CO2 multigas GHG mitigation (see Table 3.14). Note that prices and outputs are based on various definitions, so the figures are indicative only. The price bases in the original studies vary and have been converted to 2000 US$.

Sources: Weyant, 2004; Masui et al., 2005; Edenhofer et al., 2006b, Weyant et al., 2006 and Chapter 3.

Category IV stabilization trajectories from 25 scenarios: In most models (24 of the 25 scenarios[12]) the ‘optimal’ trajectory towards stabilization at 4.5W/m2 (EMF21 studies), or the near-equivalent 550 ppm CO2-only (IMCP and EMF19), requires abatement at less than 20% CO2 compared to baseline by 2030, with correspondingly low-carbon prices (mostly below 20 US$/tCO2-eq, all prices in 2000 US$). Costs are less than 0.7% global GDP, consistent with the median of 0.2% and the 10–90 percentile range –0.6 to 1.2% for the full set of scenarios given in Chapter 3 (see Figure 3.14). Carbon prices in the EMF21 multigas studies for 4.5W/m2 by 2030 average 18 US$/tCO2-eq, and span 1.2–26 US$/tCO2-eq, except one at 110 US$/tCO2-eq. Carbon prices in the corresponding 550 ppm CO2-only studies in EMF19 average 14 US$/tCO2 and span 3-19 US$/ tCO2-eq, except one at 50 US$/tCO2. Six of the IMCP 550 ppm CO2-only models have 2030 prices in the range 7–12 US$/tCO2, but four have low to zero prices in 2030, bringing the average to only 6 US$/tCO2.

Category III stabilization trajectories from 12 scenarios: In 11 of the 12 post-TAR scenarios,[13] abatement is less than 40% of CO2 by 2030. Costs are below 1% GDP, consistent with the median of 0.6% and the 10–90 percentile range 0 to 2.5% for the full set in Chapter 3, which also has a range of 18–79 US$/tCO2-eq for carbon prices (see Figure 3.14). The largest comparable dataset available in this category is the IMCP 450ppm CO2-only studies. Most of these produce a carbon price by 2030 in the range 20–45 US$/tCO2, with one higher outlier, and a mean of 31 US$/tCO2 (just over 110 US$/tC). The other Category III models nearly all give higher prices.

The lower estimates of costs and carbon prices for studies assessed here, in comparison with the full set of studies reported in Chapter 3, are mainly caused by a larger share of studies that allow for enhanced technological innovation triggered by climate policies; see 11.5 below. The impact of endogenous technological change is greater for more stringent mitigation scenarios.

Figures 11.7 (a) and (c) show how the carbon prices affect CO2 and global GDP in the models. Note that carbon prices are rising (not shown in Figure 11.7) – sharply for some of the higher numbers – from lower levels in 2020 and also after 2030. Most models considered in this analysis therefore suggest that the 20–50 US$/tCO2 cost category of the sector studies is the carbon price level which, if reached globally by 2020–2030, delivers trajectories compatible with subsequent stabilization at mid-category III levels. The corresponding CO2 reduction by 2030 is 5–40% relative to baseline (which varies between studies, with higher baselines giving higher reduction percentages in 2030).

Figure 11.7 (b) shows the CO2 abatement plotted against world GDP. In most studies, higher abatement is associated with higher loss of GDP. The relationships vary, and two models in particular stand out as radically different from others (E3MG and FUND). Three models in the IMCP predict GDP gains under different assumptions.[14] These prices and costs are largely determined by the approaches and assumptions adopted by the modellers, with GDP outcomes being strongly affected by assumptions about technology costs and change processes (see 11.5 below), the use of revenues from permits and taxes (see above), and capital stock and inertia (considered in 11.6) (Barker et al., 2006a; Fischer and Morgenstern, 2006).

  1. ^  These include three scenarios in the U.S. Climate Change Science Program (US CCSP, 2006). Note that the cost assessment presented here is based on a smaller set of scenarios than the assessment in Chapter 3. While Chapter 3 uses the full set of scenarios, including the post-SRES of the TAR, the assessment here relies on post-TAR studies that report information for macro-economic costs. In other words, modelling studies that do not give integrated GDP results are excluded from Figure 11.7 and the associated discussion in this chapter. While Chapter 3 focuses primarily on the assessment of representative cost ranges covering a larger sample, this chapter focuses on the comparative analysis of different post-TAR studies exploring the relationship between the cost indicators and their determinants in the models.
  2. ^  The excluded scenario is also an outlier in that FUND is the only EMF21 model to show a declining path for carbon prices, which fall to near zero by 2100 (Weyant et al, 2006, p. 25).
  3. ^  These scenarios exclude post-SRES results, which did not report carbon prices; see footnote 11. The Category III outlier scenario comes from the CCSP-IGSM model. The price rises to 1651 US$/tCO2 by 2100. This high price is partly due to the assumption of the limited substitution of fossil fuels by electricity as an energy source for transportation: ‘In the IGSM scenarios, fuel demand for transportation, where electricity is not an option and for which biofuels supply is insufficient, continues to be a substantial source of emissions.’ (US CCSP, 2006, p. 4–21).
  4. ^  E3MG (Barker et al., 2006b) takes a Post Keynesian approach, allowing under-used resources in the global economy to be taken up for the extra low-carbon investment induced by climate policies when permit/tax revenues are recycled by reducing indirect taxes. Such a response to revenue recyling is a feature of regional studies reported in the TAR (p. 518). FEEM-RICE (Bosetti et al., 2006) allows international cooperation in climate policies to increase the productivity of R&D investment. ENTICE-BR (Popp, 2006a), in a scenario which assumes a high elasticity of substitution between backstop and fossil fuels, shows increasing global output above baseline with more stringent stabilization targets (p. 173).