Assessing climate change mitigation involves a comparison between a policy case and a non-policy case, otherwise referred to as a baseline case. The two should, as far as possible, be defined in a way that the assessment can include all major economic and social impacts of the policies, spillovers, and leakages, as well as GHG emission implications. In other words, the cases should be assessed in the context of a “system boundary” that include all major impacts. The system boundary can be a specific project, include one or more sectors, or the whole economy.

The project, sector, and macroeconomic levels can be defined as follows:

• Project. A project level analysis considers a “stand-alone” investment that is assumed not to have significant impacts on markets (both demand and supply) beyond the activity itself. The activity can be the implementation of specific technical facilities, infrastructure, demand-side regulations, information efforts, technical standards, etc. Methodological frameworks to assess the project level impacts include cost–benefit analysis, cost-effectiveness analysis, and lifecycle analysis.
  
• Sector. Sector level analysis considers sectoral policies in a “partial-equilibrium” context, for which other sectors and the macroeconomic variables are assumed to be as given. The policies can include economic instruments related to prices, trade, and financing, specific large-scale investment projects, and demand-side regulation efforts. Methodological frameworks for sectoral assessments include various partial equilibrium models and technical simulation models for the energy sector, agriculture, forestry, and the transportation sector.
  
• Macroeconomic. A macroeconomic analysis considers the impacts of policies across all sectors and markets. The policies include all sorts of economic policies, such as taxes, subsidies, monetary policies, specific investment projects, and technology and innovation policies. Methodological frameworks include various sorts of macroeconomic models such as general equilibrium models, Keynesian models, and Integrated Assessment Models (IAMs), among others.

A “trade-off” is expected between the details in the assessment and the complexity of the system considered. For example a project system boundary allows a rather detailed assessment of GHG emissions and economic and social impacts generated by a specific project or policy, but excludes sectoral and economy-wide impacts. Conversely, an economy-wide system boundary, in principle, allows all direct and indirect impacts to be included, but has little detail on the impacts of implementing specific projects.

The system boundaries may be selected on the basis of the specific scope of the study and the availability of analytical tools, such as models. Many studies have been organized, in practice, on the basis of the scope and structure of the modelling tools applied. For example, climate change mitigation studies for the energy sector were frequently structured according to traditional modelling approaches used in that sector, which are often rich in detail on technologies, but do not include market behaviour. In contrast, macroeconomic models are often rich in detail on market behaviour and price relationships, but do not explicitly include major GHG emitting sources and related technologies.

Project assessment methodologies are generally very rich in detail and include an assessment of various direct and indirect costs and benefits of the GHG reduction policy considered. The assessments are often conducted as very data-intensive exercises, in which various project assessment tools and expert judgements are combined. They require rather strong technical skills of the experts in the collection of data, to ensure consistency in the structure and results of the analysis.

A combination of different modelling approaches is required for an effective assessment of the options. For example, detailed project assessment has been combined with a more general analysis of sectoral impacts, and macroeconomic carbon tax studies have been combined with the sectoral modelling of larger technology investment programmes.

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