Quantitative economic models (QEMs) are essential tools for systematic economic analysis, for identifying scenarios, and for constructing narratives that can support Ministries of Finance in answering critical climate questions.
MoFs need to understand the macroeconomic impacts of decarbonization on GDP and beyond. To this end, MoFs should become adept at using a range of complementary QEMs.
- No single model is universally superior. Model selection depends on: the climate policy question and objective at hand; a model’s purpose, outputs, theoretical framework, data requirements, and construction time; and available national and international capacity.
- Broadly speaking, aggregate, global models such as integrated assessment models (IAMs) help MoFs to prepare for international debates and to understand economic consequences; microeconomic models help to assess distributional impacts; input-output (IO) (and thereby computable general equilibrium [CGE]) models help to consider the relations of production between sectors; and Geographic Information System (GIS)-based models help to identify geographic differences and the distributional impacts of climate change.
- Deploying models effectively can help ensure fiscal policy fosters sustainable development, builds resilience against climate shocks, and mitigates climate change.
- Models built and run in collaboration with MoFs have the greatest chances of being maintained and used effectively, as this ensures models are tailored, fosters a sense of ownership, and helps build in-house capacity.
The most common model types in the national context are general equilibrium models, IAMs, and policy appraisal tools. At the WRI, system dynamics models are used most frequently, followed by policy appraisal and ecosystem and land-use models. This shows there is scope for MoFs across the board to move toward more holistic modeling frameworks than they use at present.
Recommendations from the WRI to MoFs include developing an in-house model ecosystem that aims to be consistent and comprehensive, based on the latest evidence of climate science. This can include integrating models with different foci and adopting system dynamics models (rarely used by MoFs) that can capture complex and dynamic interactions, feedback loops, and time-delays associated with the climate system and system interactions. Analysis should include metrics beyond GDP and help construct positive narratives around the wider benefits and opportunities of the transition. Finally, models should be continuously monitored, updated, and refined based on new data to ensure their sustained relevance and effectiveness.
Keywords
capacity buildingmodel selectionmodelssystem dynamicstransition
