Researching the Economic Impacts of Climate Change

Implications for monetary policy and financial stability

Introduction

The Bank of Canada has a mandate to “promote the economic and financial welfare of Canada,” primarily through the conduct of monetary policy and promotion of a safe, sound and efficient financial system. Understanding the macroeconomic and financial system impacts of climate change and the transition to a low-carbon economy is therefore a priority for the Bank. Below, we outline key economic questions on this topic, some of which will form the basis of the Bank’s medium-term climate change research agenda.

Climate change looms as a potentially large structural change affecting the economy and the financial system. This is in the context of scientific estimates that, through the emission of greenhouse gases, human activities have caused approximately 1.0 degree Celsius of global warming above pre-industrial levels and, if it continues to increase at the current rate, global warming is likely to reach 1.5 degrees Celsius between 2030 and 2052 (IPCC 2018). In the absence of mitigation policies, current quantitative estimates for physical effects on the macroeconomy between now and the end of the century indicate a risk of potentially large negative effects, ranging from 1.5 to 23 percent of global annual gross domestic product (GDP) per capita.1 The effects of widespread warming, including more frequent and severe extreme weather events, are projected to intensify. These climate changes pose physical risks to Canadians and the Canadian economy.

The 2015 Paris Agreement, signed by 195 countries, established a goal of holding the increase in global temperature within a range of 1.5 to 2.0 degrees Celsius above pre-industrial levels as well as a commitment to engage in adaptation planning and implementation. Achieving this goal implies a timely transition to a low-carbon economy. Such a transition involves implementing a range of climate policies, making significant technological progress, investing in green technologies and inducing major socio-economic changes.2 While this transition creates opportunities for innovation, investment and potential green growth, it also poses economic transition risks. Changes in climate policies, technology or market sentiment could lead to economic dislocation and a reassessment of the value of a variety of financial assets. In particular, climate change–driven alteration of projected earnings and expenses could affect the debt repayment capacity and collateral of borrowers and increase credit risk borne by banks and other financial institutions. The speed at which such asset repricing would occur is uncertain, but its impacts could be important for the safety and soundness of financial institutions and financial stability.

Maintaining the warming below 2.0 degrees Celsius implies that some of the existing fossil fuel reserves will become stranded assets, i.e., unusable, in the absence of potential cost-effective technologies for carbon dioxide capture and storage and carbon dioxide removal.3 The assets that could be affected are not limited to the oil and gas sector; they include other carbon-intensive sectors such as transportation (including aviation and shipping), real estate, electricity generation (e.g., coal plants), heavy industry and agriculture. These transition risks are of particular significance for Canada given its endowment of carbon-intensive commodities, the current importance of some of these carbon-intensive sectors for the Canadian economy, and the energy needs for cooling and heating.

Below, we describe the main issues, outstanding research questions and some promising directions of research along two main themes:

  • macroeconomic forecasting and monetary policy, and
  • financial system risk assessment and stability.

Macroeconomic forecasting and monetary policy

The objective of monetary policy is to preserve the value of money by keeping inflation low, stable and predictable. To maintain a stable price environment over the medium term, monetary policy relies on identifying the nature, persistence and magnitude of the shocks affecting the economy as well as on the forecast of potential output and, therefore, the output gap and inflationary pressures.

The physical risks of climate change will likely imply increases in the frequency and severity of negative supply shocks (e.g., destruction of capital stocks, disruptions to labour supply, disruptions to supply chains) and demand shocks (e.g., damage to household and corporate balance sheets that result in reduced consumption and investment). While demand shocks are typically manageable from a monetary policy perspective, supply shocks are generally more challenging because they generate a trade-off for central banks between stabilizing inflation and stabilizing output fluctuations. A rise in the frequency and severity of negative supply shocks makes it more difficult for central banks to accurately forecast output gaps and, by extension, inflation. In particular, changes in weather patterns could lead to increased volatility of headline inflation (e.g., food prices) and, in some circumstances, could affect inflation expectations.4 The associated increase in the volatility of inflation and output could also have important implications for the choice of monetary policy regime (e.g., inflation targeting, price-level targeting or nominal income/GDP targeting) because they differ in their balance of output and inflation goals and their ability to tie down inflationary expectations.

Along the transition to a low-carbon economy, as relative prices adjust, there will likely be significant economic dislocation as the economy goes through a period of restructuring and adaptation. Clear, timely and gradual climate policies, accompanied by policies that support the structural reform of the economy (e.g., that make labour markets more adaptable and responsive, promote innovation and improve the business environment), can mitigate the negative impacts of the transition. Changes in the global demand for fossil fuels, as well as carbon pricing policies and technological innovation, could lead to long-term movements in oil and gas prices and in the exchange rate of the Canadian dollar against the US dollar and other currencies. In turn, this could affect inflation (through import prices and changes in the demand for exports) and medium-term inflation expectations.

Gradual global warming and the transition to a low-carbon economy, and the uncertainty associated with their paths and effects, also pose significant challenges to the forecast of potential output and long-run economic growth. The rise of global temperatures and adaptation to it could have important impacts on labour and total factor productivity. Equally, migration, disruption and conflict resulting from climate change could affect both social and organizational capital and the productive capacity of the economy.

There is a high degree of uncertainty regarding the future path of climate change, climate policies, technological innovation and socio-economic changes. Climate-economy models must therefore be used to develop a range of plausible macrofinancial scenarios to assess possible outcomes. The Bank of Canada, as a member of the Central Banks and Supervisors Network for Greening the Financial System (NGFS), has been working with regulators and other central banks to develop common macrofinancial scenarios as a reference point.

Below, we describe the main research questions, and briefly discuss some useful approaches and methodologies to address them, along core areas of economic interest to the Bank:

  1. impacts of more frequent and severe extreme weather events on short-term macroeconomic forecasting and inflation,
  2. sectoral, regional and macroeconomic effects of the transition to a low-carbon economy, and
  3. long-term structural effects of global warming.

Impacts of more frequent and severe extreme weather events on short-term macroeconomic forecasting and inflation

Over the past 40 years there has been an increase in the frequency and severity of extreme weather events around the world. According to the Insurance Bureau of Canada, insurers in Canada have also reported larger catastrophic weather events per year across the country since 1983, including a big jump in the number of events since 2011. The extent to which price dynamics and the output gap are affected by these events will be determined by how they affect the balance of demand and supply within the economy and how persistent these effects are.

A short-term research priority for the Bank is to leverage weather data, spatial analysis and data science to improve the forecast accuracy of our policy models. Using weather data, we plan to examine the effect of weather events on key Canadian macroeconomic variables such as growth and inflation. Some of the effects might be predictable and could be incorporated in the Bank’s forecasting models, while others might be less predictable, giving rise to economic shocks. Empirical work and case studies on specific regions and sectors can also be useful to quantify near-term weather effects related to climate and inform the choice of model inputs, including the correlation and variance/co-variance structure of the shocks affecting the economy.

In the longer term the Bank might also consider incorporating climate-related shocks and policies explicitly into our monetary policy models, including natural disasters, labour supply effects, and disruptions to supply chains and international trade. Despite a few exceptions, dynamic stochastic general-equilibrium (DSGE) models, often used by central banks in macroeconomic and monetary policy analysis, normally abstract from climate change and related policies. These models could be augmented to account for these elements. Similarly, semi-structural macro-modelling approaches could be augmented with climate-related natural disasters.

Finally, the planned comparison of monetary policy rules for the review of the inflation-control target should allow us to shed light on the efficacy of different rules in the face of more frequent and severe supply shocks.5

Sectoral, regional and macroeconomic effects of the transition to a low-carbon economy

The oil and gas sector and other carbon-intensive sectors are important to the current structure of the Canadian economy. Changes in preferences, technology and policies along the transition path, including climate policy, are expected to lead to significant changes in relative prices. These price changes could lead to the reallocation of resources across sectors and alteration in cross-country comparative advantages, patterns of trade and specialization, balance of payments and exchange rates. When applied regionally, the economic impact of climate policies depends strongly on interactions with other regions in the world. Lasting shifts in the energy mix are also expected to persistently change energy prices, which could feed into inflation expectations and wages, creating inflationary pressures.6

To fully understand the regional and sectoral impacts of the transition to a low-carbon economy, multi-regional and multi-sectoral dynamic general-equilibrium models will be used by the Bank in combination with different transition scenarios. Computational general-equilibrium (CGE) models based on national accounts and international trade flows at the sectoral level are traditionally well-suited to this type of analysis and can account for potential border carbon adjustments and carbon leakage effects.7 The Bank has recently brought in a climate-economy CGE model to explore the sectoral and macroeconomic implications of transitioning to a low-carbon economy, including the implications for inflation and stranded assets. Preliminary work identifies several channels of transition risks to the global and Canadian economies.

On the empirical side, trade data at the sectoral level can be used to analyze the structural response of the economy to changes in climate policies. In the medium term, the Bank can also explore case studies of historical oil price shocks and their origin (demand versus supply) to inform the analysis of the macroeconomic impacts.

Long-term structural effects of global warming

Long-term modelling of potential productive capacity and economic growth is essential for monetary policy. To that end, it is important to capture the impact of global warming and the transition to a low-carbon economy on physical, natural and human capital stock, labour supply and productivity. The Bank has begun to assess the channels through which climate change could impact Canadian and global potential output and the neutral rate of interest. In the medium term, the Bank will seek to devote some research to modelling how global warming affects total factor productivity (TFP) through diverting resources to adapting and rebuilding physical capital and to climate-related migration.

Assessing the long-term macroeconomic consequences of climate change has mostly relied on integrated assessment models (IAMs) that seek to capture the complex interactions between the physical and economic dimensions of climate change, including endogenous feedback loops between temperature and GDP.8 Many IAMs are being used by intergovernmental organizations and national governments to support the development of climate policy. However, these models are still evolving, and several criticisms have been raised, including:

  • They rely on damage functions to capture the effects of climate change on the level of GDP.9
  • They ignore the endogenous dynamic effects through which climate change potentially affects economic growth.
  • They ignore uncertainty regarding the increase in temperature and the non-linear impacts of climate change.
  • They ignore the distributional consequences of climate change.10

To address some of these criticisms, IAMs that account for endogenous growth effects of climate change can be developed.11 These models could also consider the effects of green growth associated with structural reforms related to climate change and incorporate uncertainty (e.g., DSGE models) and imperfect foresight directly.12 For tractability, IAMs also rely on the representative agent assumption, making these models poorly suited for analyzing the distributional consequences of climate change. Heterogeneous agent DSGE models and agent-based models might be better alternatives for such analysis. The Bank will collaborate with the academic community and other central banks to enhance the climate-economy modelling tool kit.

Assessing climate-related risks to the financial system

More frequent or severe extreme weather events and/or a late and abrupt transition to a low-carbon economy could have significant impacts on the Canadian financial system, with potential systemic consequences.

Extreme weather events could cause damage to physical assets, including real estate, capital and infrastructure, and loss of life with consequent property and casualty (P&C) insurance losses, damage to balance sheets of both households and firms, increases in defaults, and potential financial sector distress.

A late and abrupt transition to a low-carbon economy could lead to a sudden repricing of climate-related risks and stranded assets, which could negatively affect the balance sheets of financial market participants, with potential consequences to financial stability. Given the Canadian economy’s reliance on carbon-intensive activities, its financial system could be particularly vulnerable to transition risks under some adverse scenarios. Clear climate policy, a smooth and steady transition and financial disclosure of climate-related risks could contribute to the correct pricing of risks and assets and a more efficient allocation of capital, mitigating the risks to the macroeconomy and the financial system.

Assessing the impacts of physical and transition risks of climate change on the financial system is one of the most urgent and prominent issues. However, uncertainties around the course of climate change itself, the breadth and complexity of the transmission channels, the direct and indirect impacts, and the need to consider, in aggregate, some combination of both physical and transition risks make it particularly challenging. Given the sensitivity of results to these underlying assumptions, hypothetical climate and transition scenarios can be used to explore the direction and broad scale of outcomes. Sector- and country-specific scenarios based on current national climate policy can be developed to create realistic gradual and abrupt transition scenarios to assess the impacts on multiple levels (individual firms, the real economy, financial institutions and the larger financial system), taking into account feedback loops and spillover effects. Much of the work on the effects of transition risk on financial stability uses a combination of scenario analysis, energy models, IAMs and network models to assess the potential for stranded assets and value to create credit and market risk. Stock-flow consistent models and agent-based models might also provide a valuable alternative for a complex adaptive system in which heterogeneity, non-linearities and disequilibrium phenomena play a key role.

Given the degree of interconnectedness in the economy and the financial system, it is important to assess both the direct impacts of physical and transition risks and the indirect and second-round effects. This implies accounting for exposures along the whole production chain, the transmission of shocks through financial linkages and feedback loops between the macroeconomy and the financial sector.

Below, we discuss some of the key research questions in this area, including:

  1. The identification of the transmission channels of climate-related risks to the financial system
  2. The extent to which markets and investors internalize carbon risks
  3. The assessment of exposure of financial market participants to climate-related risk and the resilience of the financial system to hypothetical climate and transition scenarios

Direct and indirect transmission channels for physical and transition risk

First, it would be useful to identify which risks are most pressing, so research could be more concretely focused on specific short-term impacts for particular sectors, geographies and asset classes as well as the macroeconomic and financial stability implications. Real estate, agriculture and transportation are sectors that are both important and immediately exposed to physical impacts of climate change, which could affect banks and insurers exposed to these sectors on both the assets and liabilities sides of their balance sheets. Similarly, the oil and gas sector and other carbon-intensive sectors, such as transportation, electricity generation, infrastructure and carbon-intensive industrial technologies, could be vulnerable to transition risks under some adverse transition scenarios. The Bank will leverage existing research and analysis by other institutions, as well as its own research, to inform the identification of risks and deepen our understanding of the transmission channels of physical and transition risks. Important issues to explore are the longer-term climate change implications for the profitability and viability of particular sectors (e.g., insurance and reinsurance) and their macrofinancial consequences.

The extent to which markets and investors internalize carbon risks

Some recent literature has assessed the extent to which investors and markets are internalizing risks related to climate change. Using standard event methodology, it is possible to examine the market reaction to specific events, which could be associated with a change in market expectations about the profitability in investing in carbon-intensive activities. To date, the literature has found evidence that there is a limited but growing sensitivity to carbon risks. The Bank is partnering with academic researchers to further explore this question.

The climate-related risk exposures of financial market participants and the resilience of the financial system to hypothetical climate and transition scenarios

Understanding the climate-related risk exposures (business, credit, underwriting, market and legal risk) of P&C insurers and re-insurers, banks, pension funds, investment funds and real estate investment trusts is a priority for central banks and financial regulators. Several central banks and supervisors have, for example, compared geographic distribution of insurance coverage and retail lending activity with that of extreme weather events (e.g., hurricanes and floods). Others have looked to quantify the exposure of financial portfolios to transition risk by identifying the proportion of assets (e.g., equities and corporate bonds) held in sectors most at risk from the transition to a low-carbon economy. While these approaches capture first-round effects, they may not fully incorporate the wider risks of financial contagion from an unanticipated economic transition. As a first step, the Bank intends to evaluate direct and indirect exposures of Canadian financial institutions to climate-related risks based on available data.

Some studies have combined exposure data and scenario analysis using network models to account for second-round effects.13 These are current state-of-the-art frameworks in climate stress testing. An ultimate goal of the Bank is to develop climate stress-testing frameworks to assess the resilience of the financial system to hypothetical extreme but plausible scenarios. One of the key barriers to assessing climate-related exposures is the availability of data to support granular, bottom-up, quantitative analysis. To address this gap, central banks and regulatory authorities must co-operate and combine standard macroeconomic, financial market and supervisory reporting data with new climate databases.

References

Battiston, S., A. Mandel, I. Monasterolo, F. Schütze and G. Visentin. 2017. “A Climate Stress-Test of the Financial System.” Nature Climate Change 7: 283–288.

Dietz, S. and N. Stern. 2015. “Endogenous Growth, Convexity of Damages and Climate Risk: How Nordhaus’ Framework Supports Deep Cuts in Carbon Emissions.” Economic Journal 125 (583): 574–620.

Gillingham, K., W. Nordhaus, D. Anthoff, G. Blanford, V. Bosetti, P. Christensen, H. McJeon, J. Reilly and P. Sztorc. 2015. “Modeling Uncertainty in Climate Change: A Multi-Model Comparison.” Cowles Foundation Discussion Paper No. 2022.

Intergovernmental Panel on Climate Change (IPCC). 2018. “Summary for Policymakers.” In Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C Above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty.

McGlade, C. and P. Ekins. 2015. “The Geographic Distribution of Fossil Fuels Unused when Limiting Global Warming to 2°C.” Nature 517: 187–190.

McKibbin, W., A. Morris, A. J. Panton and P. J. Wilcoxen. 2017. “Climate Change and Monetary Policy: Dealing with Disruption.” CAMA Working Paper No. 77/2017. Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, Australian National University.

Network for Greening the Financial System (NGFS). 2019. Macroeconomic and Financial Stability: Implications of Climate Change. Technical supplement to the first comprehensive report.

Nordhaus, W. D. 1994. Managing the Global Commons: The Economics of Climate Change . Cambridge: MIT Press.

Pindyck, R. S. 2013. “Climate Change Policy: What Do the Models Tell Us?” Journal of Economic Literature 51 (3): 860–872.

Roncoroni, A., S. Battiston, L. O. L. Escobar Farfàn and S. Martinez Jaramillo. 2019. “Climate Risk and Financial Stability in the Network of Banks and Investment Funds.”

  1. 1. See NGFS (2019) for a discussion on the range of estimates for physical impacts on the macroeconomy, their underlying assumptions and their geographic distribution.[]
  2. 2. The presence of externalities and other market failures prevents an appropriate market response to the challenge of mitigating climate change and justifies the use of climate policies.[]
  3. 3. For example, McGlade and Etkins (2015) estimate that, without carbon dioxide capture and storage, 35 percent of oil, 52 percent of gas and 88 percent of coal reserves in known global reserves will be unburnable before 2050 to achieve the 2.0 degrees Celsius target.[]
  4. 4. If the shocks and their effects were short-lived, monetary policy would usually look through them without de-anchoring inflation expectations, given a credible monetary policy framework. However, persistent sectoral price shocks risk de-anchoring inflation expectations and triggering second-round effects that increase inflationary pressures in the medium term.[]
  5. 5. See, for example, McKibbin et al. (2017) for a discussion on the interactions of monetary policy and climate change.[]
  6. 6. The direction of such changes depends on the timing and speed of transition, including the paths of policies on carbon pricing and the pace of technological breakthroughs and adaptation.[]
  7. 7. Given that our main interest is to model the macroeconomic impacts of climate change without attempting to design the optimal climate policy, policies can be treated as exogenous (part of climate scenarios) and the analysis considerably simplified. This allows for more granular CGE models that can then be used for analysis of the impacts of climate change at the sectoral level.[]
  8. 8. Several IAMs are capable of examining endogenous changes within a multi-region, multi-sectoral setting, enabling an investigation of the distributional impacts of climate change. See Gillingham et al. (2015).[]
  9. 9. Nordhaus’s Dynamic Integrated Climate-Economy (DICE) model (Nordhaus 1994) and many of its successors assume a quadratic damage function that would require an unrealistic increase of 18.0 degrees Celsius in average global temperature to generate a 50 percent reduction in global GDP.[]
  10. 10. For a discussion of some of these criticisms, see Pindyck (2013) and Dietz and Stern (2015).[]
  11. 11. DICE and many subsequent IAMs build on the exogenous Ramsey-Cass-Koopmans growth model, where growth is driven by exogenous productivity growth. In these models, climate change affects only the level of GDP. Dietz and Stern (2015) and others suggest that climate change might have long-lasting effects on growth and propose models of endogenous growth with knowledge spillovers, endogenous TFP and damage to TFP. These models imply much larger costs of climate change.[]
  12. 12. Instead of explicitly modelling uncertainty, IAMs typically rely on sensitivity analysis. However, this approach does not reflect the impact of uncertainty on decision making.[]
  13. 13. See Battiston et al. (2017) and Roncoroni et al. (2019).[]

Content Type(s): Staff research, Other
Topic(s): Climate change