Climate change and its policy responses cause both transitory and permanent shocks to the economy. Some of these shocks are gradual, such as the impact of increased temperatures on productivity, and others are sudden, such as natural disasters. Analysts expect these shocks to increase over time, both in intensity and frequency. Understanding and forecasting the potentially disastrous effects of these shocks can guide policy. Governments can use various models to analyze the impact of climate change and climate change policies on the economy.

What are the key policy instruments?

Analysts have developed a number of models that can support policy-making in understanding and predicting the macroeconomic effects of climate change and climate-related policies. Two main classes of models used in these analyses are Computable General Equilibrium (CGE) and Integrated Assessment Models (IAM).

CGE models: are used to identify the influence of climate change on productivity, households demand, and production factors such as labor and land. These models can also be used to determine the effect of policy changes on macro-relevant variables, such as employment in a sector and the distribution of resources within a society. There are various types of CGE models, and a key difference exists between static and dynamic ones:

  • Static CGE: these models compare the state of the economy before and after the occurrence of an event, such as a temperature increase or an environmental tax reform. These models can identify winners and losers from an economic shock but can result in inaccurate estimates because they fail to capture some of the costs and of the benefits linked to the transition from before and after the shock. 
  • Dynamic CGE: these models capture changes in time of the variables of interest. Dynamic CGE models study the forces that lead to an equilibrium after a shock has occurred, the behavior of some variable across time (e.g., unemployment), as well as the time needed to reach the equilibrium. A particular type of dynamic CGE is the Recursive Dynamic CGE. Here, the analysis is multi-period, meaning that solutions are obtained for each period (e.g., year).

The analytical capability of CGE models is improving as they develop. For instance, the 2016’s Integrated Economic-Environmental Modelling (IEEM), allows for more comprehensive study of economic and environmental impacts of policies or investment decisions compared to traditional CGEs.

IAMs models: are used to study the interaction between the biophysical system and the economy. These models can provide analyses of the economic impact of a temperature rise at the regional or the global level; obtain estimates of the social cost of carbon, or study optimal adaptation/mitigation policies. There are various types of IAMs. Commonly used IAMs are:

  • Dynamic Integrated Climate-Economy (DICE): the DICE is a global model for dynamic analysis of CO2 emissions, global temperature variations, and the economy in the long term (100 years or more). This model also allows considering future green innovation.  A separate model (AD-DICE) has been developed to account also for adaptation policies and tradeoffs between adaptation and mitigation investments.
  • Regional Integrated model of Climate and the Economy (RICE): it's an expansion of the DICE model that disaggregates the analysis into several regions. Each region has specific features in terms, for instance, of CO2 emissions and output, and has its own welfare function to be maximized. 

The sophistication of IAMs is increasing. A recent extension is the General Monetary and Multisectoral Macrodynamics for the Ecological Shift (GEMMES), which allows studying the interaction of the Earth and economic systems, while accounting also for the role of finance and private debt.

What are the challenges and opportunities ahead?

Understanding and forecasting the macroeconomic effects of climate change and climate change policy is far from easy. Existing models are not necessarily easy to use, and even when used correctly they have limitations. While likely large, there is uncertainty on the projected economic impacts of climate change. Uncertainty exists, for instance, regarding the temperature rise, its impact on the Earth system and its economic effects. Current estimates likely underestimate the effect of climate change because often they do not consider for instance the tipping points in climate dynamics, such as the thawing of permafrost.

The macroeconomics of climate change is increasingly sophisticated and modeling choices can influence the results and the ensuing policies. For instance, in using IAMs, decisions have to be made on whether to account for the risk of natural disasters at the regional level or for the indirect impacts of climate change on the economy, such as increased migration flows.

What are good practices and what can be learned from them?

As climate change becomes increasingly featured in macroeconomic forecasting, good practice is emerging. Many policy advisory bodies offer support to include climate change into macroeconomic analysis.

  • Agence Française de Développement (AFD): the AFD’s GEMMES has been applied to Brazil and Vietnam. Applications to Côte d’Ivoire and Colombia are under study.
  • Inter-America Development Bank (IADB): the IEEM model was applied to, for instance, Guatemala, to study the impact of fuelwood scarcity and forest degradation on economic growth projections.  This model has been applied also to Colombia and Zambia.
  • International Monetary Fund (IMF): the IMF’s Fiscal Affairs Department has developed a model to study the effects of carbon pricing on emissions abatements, national public health, the fiscal situation of a country, and energy prices as well as the economic costs of carbon pricing. The model has been applied to the case of China, and further applications to G20 countries are expected.
  • The Organisation for Economic Co-operation and Development (OECD): the OECD has developed the ENV-Growth model to forecast long-term national income pathways for 184 countries, explicitly taking into account energy, oil, and gas as productive inputs.  
  • United Nation Environment Programme (UNEP): the UNEP has developed the Integrated Green Economy Modelling (IGEM) model that integrates three modeling approaches (System Dynamics, CGE, and Input-Output Social Accounting Matrix) to improve the impact analysis of green policies. The model has been applied, for instance, to study the welfare effects of different revenue uses of Mexico's carbon tax. 
  • World Bank Group (WBG): the WBG has provided client countries with advisory services on the use of various CGE models. The Partnership for Market Readiness (PMR), a donor supported program in the World Bank, has built substantial experience in this respect, for instance, by analyzing the macroeconomic effects of Peru’s 2030 mitigation strategy.

Peer exchange among Finance Ministries offers an opportunity to have a constructive debate on how to best incorporate climate change into macroeconomic modeling.