Central banks, financial stability and policy coordination in the age of climate uncertainty: a three-layered analytical and operational framework

ABSTRACT

This paper explores how climate change and the transition to a low-carbon economy pose new systemic financial risks (so-called Green Swans), and the role of central banks in addressing them within their financial stability mandate. It does so by developing a three-layered analytical framework that central banks could use to shape their climate-related monetary and financial policies. First, central banks have already started to revisit their backward-looking risk models for the purpose of integrating forward-looking climate-related risks. Second, given the limitations of existing climate-economy models in a context of radical uncertainty, we argue that future climate scenario analysis should rely on systems-based approaches such as non-equilibrium models and more qualitative tools such as those provided by a socio-technical perspective. However, even these new approaches will not suffice from the perspective of financial stability: climate-related risks will remain largely unhedgeable as long as a system-wide and structural transformation is not undertaken, including an unprecedented level of cooperation between central banks, fiscal authorities, the private and public sectors at large, civil society, and the international community. Third, and as a result of the first two points, embracing climate-related uncertainty means that central banks play a new role: helping to coordinate the policies needed to fight climate change, so as to fulfil their own mandate of financial stability. To this end, we make a few specific policy proposals.

Key policy insights

• Central banks’ traditional risk models do not enable them to identify climate-related systemic risks (Green Swans).

• Adopting new forward-looking and non-equilibrium modelling approaches is necessary to better appreciate the nature of climate-related risks, but it is not sufficient.

• To continue fulfilling their mandate of financial stability over longer time horizons than those traditionally considered, central banks must also get involved in policy coordination to mitigate climate change.

• This includes exploring which policy mixes (fiscal-monetary-prudential) can better address the climate imperatives ahead; considering climate stability as a global public good to be supported through reforms of the international monetary and financial system; and systematizing the integration of long-term sustainability criteria in both private and public sectors.

KEYWORDS:

• Climate risk management
• socio-technical contexts
• macroeconomic effects
• mitigation scenarios
• financial viability
• complex systems

Acknowledgments

the authors acknowledge all the suggestions, comments and contributions made to the book ‘The green swan: central banking and financial stability in the age of climate change’, which has informed this article. We also thank Paul Vignat for his help.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The concept of uncertainty refers to the possibility of outcomes that do not lend themselves to probability measurement (Knight, 1921; Keynes, 1936), whereas the concept of risk refers to something that has a calculable probability.

2 The term ‘green’ is used in italics throughout the text as a reminder that the greenness of an asset or economic activity depends on multiple assumptions. For instance, diverging opinions can be found as to whether nuclear energy or electric vehicles are green.

3 A Minsky moment refers to a sudden and significant collapse in the value of financial assets (typically brought on by excessive leverage and speculation), leading to a market crash and potentially to a systemic crisis.

4 Complexity science is a cross-disciplinary field that specifically studies properties that emerge from interactions between system components (Mercure et al., 2016).

5 Battiston et al. (2017) also use network theory to estimate how climate-related losses can affect individual investors through second-round effects (e.g. if they hold shares or bonds of financial institutions that are exposed to fossil fuels).

6 An alternative interpretation consists in considering that such models are grounded in a positivist philosophy of science when the modeler does not acknowledge the limitations of the model and its outcomes.

7 For instance, some climate-economy models rely so much on negative emissions technologies and on carbon capture and storage (CCS) to meet ambitious climate targets (e.g. leading to an increase in the remaining carbon budget to reach a 1.5°C world of up to 290% (Carbon Brief, 2018)) that they pose the question of their technical feasibility, let alone their potentially devastating impacts on other ecosystems (IPCC, 2019).

8 For instance, renewable energy could be subject to barriers in the short to medium term due to intermittent and unpredictable power output (Moriarty & Honnery, 2016), which requires major improvements in current energy storage technologies. In addition, low-carbon technologies available for several sectors such as steel production and air travel are limited (Semieniuk et al., 2020).

9 The most promising technological developments emphasized in the literature have varied greatly over short time horizons, e.g. by moving from biofuel to hybrid-electric and then battery-electric (Geels et al., 2017), before highlighting the role of hydrogen fuel more recently.

10 It is noteworthy that the volume of investments needed (a critical element to assess the risk and opportunities related to a low-carbon transition) can vary significantly. The survey of six models estimating the additional annual average energy-related investments needed to limit global warming to 1.5°C (over the period 2016 to 2050, compared to the baseline) finds significant variations, with values ranging from $150 billion ($2010) to $1,700 billion ($2010). Total investments (i.e. not just additional ones) in low-carbon energy also vary greatly, from $0.8 trillion ($2010) to $2.9 trillion ($2010; IPCC, 2018, p. 153).

11 The risk of seeing real interest rates rise could even be null (e.g. Kelton, 2019), from a post-Keynesian perspective in which interest rates are set exogenously by central banks (Lavoie, 2014). Whether one agrees or not with this view, it is unlikely that real interest rates will sharply increase in the near future given the current macroeconomic situation.