The global climate is changing, and the release of greenhouse gases (GHGs) from human activity has contributed to global warming. While there is significant uncertainty about the costs of inaction, it is generally agreed that failing to tackle climate change will have significant implications for the world economy, especially in developing countries, where reduced agricultural yields, sea level rise, extreme weather events and the greater prevalence of some infectious diseases are likely to be particularly disruptive (OECD, 2008a). Furthermore, there are significant risks of unpredictable, potentially large and irreversible, damage worldwide. The exact economic and welfare costs of policy inaction could equate to as much as a permanent 14.4% loss in average world consumption per capita (Stern, 2007), when both market and non-market impacts are included.

This chapter describes past trends in greenhouse gas emissions, and future projections. It presents the potential consequences of climate change when no action is taken, and discusses the associated risks and uncertainties. The chapter assesses four different scenarios for stabilising greenhouse gas concentrations, and examines how differences in the stabilisation target, peaking year and level of overshooting of the target affect the costs of action. These scenarios all assume that mitigation policies are cost-effective, i.e. that all carbon emission sources can be priced globally, to provide a benchmark for more realistic scenarios examined in later chapters.

This chapter presents analysis of the various national and international policy instruments for tackling climate change, their respective pros and cons, and how they can best be integrated into a coherent policy framework. It assesses carbon taxes, emissions trading schemes (including cap-and-trade), standards, and technologysupport policies (R&D and clean technology deployment) according to three broad cost-effectiveness criteria: i) Static efficiency, i.e. does the instrument help fully exploit existing low-cost abatement opportunities, ii) Dynamic efficiency, i.e. does it encourage innovation in order to lower future abatement costs? iii) Ability to cope effectively with climate and economic uncertainties. The chapter concludes with a discussion of potential complementarities and overlap across policy instruments.

This chapter identifies a number of issues that arise when carbon pricing coverage is incomplete. These include unexploited cheap options for GHG emissions reduction, carbon leakage and competitiveness concerns. A number of policies that have been suggested to address these issues, such as countervailing duties on imports or border tax adjustments and free allocation of permits (‘grandfathering’), are closely examined. The chapter also assesses the role that Reducing Emissions from Deforestation and forest Degradation (REDD) can play, and discusses the main implementation issues and options for financing mechanisms for REDD.

This chapter examines ways in which a global carbon price can be built up gradually to achieve broad-based international pricing of carbon. Important steps include removal of environmentally harmful fossil fuel energy subsidies and increasing the use of emissions trading schemes while linking them together. The chapter investigates the global and regional gains from linking regional emissions trading schemes, and the harmonisation issues that need to be addressed in the case of direct linking. It examines indirect linking, for instance through the Clean Development Mechanism (CDM) or possible sectoral crediting approaches. It concludes with a discussion of market regulatory issues and the role of financial markets.

This chapter explores the impact of various policy instruments to stimulate R&D and technology deployment, using a model that incorporates the process of technological change and innovation, i.e. induced technological change. It starts with a review of spending trends in energy-related R&D, followed by an assessment of the impact of R&D policies and spending on innovation and technology deployment. The chapter continues with an analysis of the effects of carbon pricing and technology policies on the costs of mitigating climate change. Finally, it addresses the question of whether technology policies will work in the absence of carbon pricing.

This chapter investigates which countries are needed to achieve an ambitious GHG stabilisation target, and identifies the economic incentives that countries have to participate in global action. It identifies the size of the so-called free-rider incentives, whereby countries have a greater incentive to stay outside a global mitigation coalition and benefit from the mitigation actions of others than to participate. It assesses the possibilities to enhance participation incentives by taking co-benefits of mitigation policies (e.g. reduced local air pollution and improved energy security) into account. Finally, the role of financial transfers, specifically the allocation of emission reduction targets across countries, is highlighted as an instrument to stimulate participation.

This chapter reviews the climate policy instruments that are already in use or that are planned to start in the near future. This provides a basis for investigating how political support can be built up for global action. It compares mitigation costs and emission reductions (comparability of effort) across countries for a wide range of carbon price levels. It investigates whether the emission reduction targets for 2020 that have been declared or suggested by different countries are sufficient to achieve a pathway consistent with an ambitious GHG stabilisation target. It discusses options for international support, such as financial support for mitigation action in developing countries, technology transfer and support for adapting to a changing climate.

This annex applies a simple “conditional growth” framework to long-term GDP projections for the world economy that serves as a baseline for the examination of policy scenarios.1 Baseline economic scenarios have proliferated in recent years in the context of climate change projections, such as those developed by the Intergovernmental Panel on Climate Change (IPCC), which typically assumes a convergence process whereby the income levels of less-developed countries gradually, and at least partially, catch-up to those of more developed economies.2 The vast majority of projections focus on convergence at the macroeconomic level, in terms of GDP per capita or GDP per worker (the “top-down” approach) while a few others assume some gradual catch-up at the sectoral level (the “bottom-up” approach).3 In both cases, climate modellers have typically relied on simple assumptions regarding the form and the speed of convergence, without explicitly specifying the policy assumptions underlying their scenarios. This, and the fact that in the IPCC’s Special Report on Emission Scenarios (SRES) a large number of possible outcomes are presented as being equally likely, may have contributed to strengthening the impression of uncertainty that is inherent to any long-run world economic projections.

The OECD ENV-Linkages General Equilibrium (GE) model is the successor to the OECD GREEN model for environmental studies, which was initially developed by the OECD Economics Department (Burniaux, et al. 1992) and is now hosted at the OECD Environment Directorate. GREEN was originally used for studying climate change mitigation policy and culminated in Burniaux (2000). It was developed into the Linkages model, and subsequently became the JOBS/Polestar modelling platform that was used to help underpin the OECD Environmental Outlook to 2020. A version of that model is also currently in use at the World Bank for research in global economic development issues. Previous work using the model includes development of a baseline to 2030 and a study of the consequence of structural change (including some environmental implications) associated with economic growth. Much of the applied work with the model is reported in various chapters of the OECD Environmental Outlook to 2030 (2008). Exploration of the model’s properties and some sensitivity analysis is reported in OECD (2006).