The Distribution of the Major Economies' Effort in the Durban Platform Scenarios

Abstract

The feasibility of achieving climate stabilization consistent with the objective of 2°C is heavily influenced by how the effort in terms of mitigation and economic resources will be distributed among the major economies. This paper provides a multi-model quantification of the mitigation commitment in 10 major regions of the world for a diversity of allocation schemes. Our results indicate that a policy with uniform carbon pricing and no transfer payments would yield an uneven distribution of policy costs, which would be lower than the global average for OECD countries, higher for developing economies and the highest, for energy exporters. We show that a resource sharing scheme based on long-term convergence of per capita emissions would not resolve the issue of cost distribution. An effort sharing scheme which equalizes regional policy costs would yield an allocation of allowances comparable with the ones proposed by the Major Economies. Under such a scheme, emissions would peak between 2030 and 2045 for China and remain rather flat for India. In all cases, a very large international carbon market would be required.

Post-2020 climate agreements in the major economies assessed in the light of global models

“…Figure 4 shows that for Europe and North America actual emissions and allowances in the per capita case would be similar and lower than the ones announced in the major economies forum meeting of 2009 (80-95% reductions). A per capita burden-sharing scheme would require a significant mitigation effort from China and some other regions such as the Middle East (in line with previous modeling studies 14,37,[62][63][64] ). The opposite would hold for India (and Africa, not shown), because of its low per capita emissions.…”

“…Even if global mitigation costs were low, policymakers care and argue about the regional distribution of policy costs, since it impacts economic development, competitiveness and even political stability. The scenarios indicate that the costs of mitigation will vary significantly across countries 1,14,[66][67][68][69][70][71] . Figure 5 portrays this finding for the LIMITS models, showing that -in a cost effective framework with uniform carbon pricing but without carbon trading and compensatory transfers-mitigation costs in the OECD would be lower than global average, and the opposite would hold for developing economies, and especially for energy exporting regions, which would face adverse terms of trade effects 1,37,[71][72][73] .…”

“…This ranking is rather robust across climate targets, mitigation cost metrics and IAMs 14,74 , though the ranges are considerably larger for developing economies. The regressivity of regional costs can be attributed to several factors, but especially to emission intensity, abatement potential and international trade effects 14,[75][76][77] . Using data from the EMF22 model comparison study, a higher ratio of emissions to GDP -the so called emission intensity-in the BAU has been shown to lead to lower marginal abatement costs but to higher total costs for a common carbon price 75 .…”

Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

“…14 These differences reflect alternative model implementations of heterogeneity and behavior within 15 the MESSAGE-Transport framework. 16 In two of these cases, disutility costs deriving from the MA 3 T model are brought into MESSAGE- 17 Transport, in order to capture non-monetary behavioral preferences through monetization. The 18 empirical evidence suggests that the disutility costs should approach zero over time (i.e., the levels 19 of conventional gasoline/diesel vehicles) as AFVs become more commonplace and their requisite 20 refueling/recharging availability expands (see Table 2 and Table 3).…”

“…Furthermore, the vehicle adoption 15 decisions are found to vary quite markedly by world region, due, at least partly, to differences in 16 non-monetary preferences for consumers in different countries (as evidenced by the empirical base 17 and implemented in the modeling through the regionally differentiated disutility costs). This is 18…”