11.4.4.1 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 3.3.5.4) 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. The figure is in 3 parts, showing (a) the carbon prices in US$(2000) by 2030 (typically a rising trend) and their effects on CO2 emissions, (b) the effects of CO2 abatement on GDP, and (c) the relationship between carbon prices and gross world output (GDP). All data are differences from the baseline projections for 2030. The studies are grouped around two of the stabilization categories set out in Chapter 3 (Table 3.5), with corresponding insights.
Category IV stabilization trajectories from 25 scenarios: In most models (24 of the 25 scenarios) the ‘optimal’ trajectory towards stabilization at 4.5W/m2 (EMF21 studies), or the near-equivalent 550 ppm CO2-only (IMCP and EMF19), requires abatement at less than 20% CO2 compared to baseline by 2030, with correspondingly low-carbon prices (mostly below 20 US$/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$/tCO2.
Category III stabilization trajectories from 12 scenarios: In 11 of the 12 post-TAR scenarios, abatement is less than 40% of CO2 by 2030. Costs are below 1% GDP, consistent with the median of 0.6% and the 10–90 percentile range 0 to 2.5% for the full set in Chapter 3, which also has a range of 18–79 US$/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. 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).