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2. Integrating climate into macroeconomic modelling: Why does it matter?

Climate policies are key to achieving the ambitious commitments of all of the Nordic countries to become carbon neutral in the next two to three decades. The potential macroeconomic impacts of climate change, and the costs and benefits of different policies to address it, underline the importance of incorporating climate into macroeconomic models. The information provided by integrated climate-finance models empowers policy makers and businesses to make informed decisions on specific strategies, trade-offs between different policy options - costs and benefits, and potential pathways to achieving the carbon neutrality goals and transitioning to a more sustainable and resilient economy (Braendle, 2021).
Taxation and public expenditure are two key tools to reaching the climate targets. Taxing emissions should reduce polluting activities while public investment supports the introduction of cleaner and more efficient technologies. However, assessing the environmental impacts of budgetary policies, evaluating their coherence when considering national and international climate commitments, and agreeing on the right policy mixes, are difficult to attain. 
CGE models provide a comprehensive representation of the dynamic interactions between different economic agents, namely firms, factors of production, households, the government, investors, and international trade. CGE models are, in short, “equilibrium tools that seek to explain the behaviour of supply, demand and relative prices in the whole economy with many markets” (Krook-Riekkola et al., 2017, p. 803). CGE models are used across the Nordic Region, as well as in international organizations such as the International Monetary Fund (IMF), World Bank, the World Trade Organisation (WTO), OECD, and the European Commission (EC). They have been widely used since the 1980s to assess the long-term impacts of climate change and climate mitigation policies (e.g. energy market regulation and taxation) on industries, households, international trade, etc. In this context integrated economic and climate modelling frameworks have been developed in, order to produce sensitive results on input substitution and technology innovation effects. Such integrated frameworks link energy or climate impact models to a CGE model to better capture the interactions between different sectors, policies and regions, often leading to more detailed and policy-relevant results (Böhringer, 1998; Krook-Riekkola et al., 2017; Wilson and Swisher, 1993). Generally speaking, two broad types of linking approaches can be defined, namely soft-links versus hard-links – see Table 1.
Type of link
Main characteristics
Key advantages
Iterative process, between the contributing models: The CGE model and the model intended to be linked operate together until convergence in specific parameters (like prices and quantities) is achieved.
  • Takes advantage of the strengths of all models being linked.
  • Can potentially have a higher degree of precision and granularity.
  • Modular design components are functional on their own.
  • More easily tailored to specific policy needs
  • Practical at a national level when existing models need to be kept as is.
Implies a large effort and coordination in terms of:
  • matching different aggregations and units
  • selecting and calibrating parameters in the models
  • intense communication between engineers, natural scientists, climatologists, engineers and economists and their different perspectives.
The models are integrated and solved simultaneously to produce an economic equilibrium that is consistent over both models through nested production functions (unlike the iterative process of soft-links).
  • Data requirements tend to be lower.
  • Suitable when focusing on a global overview for which the regional details are subordinate.
  • More control and transparency over modelling assumptions.
  • Model results are easier to understand and communicate to end users.
  • As opposed to soft-linking, where procedures need to be repeated for every project, integrating the bottom-up information is done only once.
  • Limitation concerning data transparency as frequently it involves a simplified description of the contributing models and often also aggregation of one of the data bases.
Table 1 – Main characteristics of types of modelling techniques
Source: Table inspired by Böhringer (1998), Böhringer and Rutherford (2009), Krook-Riekkola et al. (2017), Martinsen(2011) and the ICMM workshops.
Both soft-link and hard-link CGE models enable an analysis of the input substitution and technological innovation effects of outcome-based regulations and, thereby, both models may contribute to the understanding of the territorial and distributional impacts of climate policies.