EDHEC’s Ricardo Rebonato On Climate Change For Investors, Policymakers & Regulators
Riccardo Rebonato dives deep into the challenges posed by climate change, especially for investors, policymakers, and regulators. The uniqueness of the current climate crisis stems from its unprecedented nature, and the lack of historical data, which often is the backbone for most financial and risk assessment models.
The Uncharted Territory of Climate Scenario Analysis
In the realm of financial stress testing, a century’s worth of data allows for a certain level of predictive accuracy. This luxury doesn’t extend to climate scenario analysis, which grapples with limited data and inconsistent models connecting temperature rises to economic repercussions. The necessity to assign probable outcomes to various climate events poses further challenges.
Comparing Macrofinancial and Climate Scenarios
Rebonato draws a distinction between macrofinancial systems, which operate under the assumption of being fundamentally stationary, and the dynamic and adaptive nature of climate impacts on societies. The interconnectedness and cyclical impacts between human responses and the environment amplify the complexity of the issue.
The Imperative of Probabilistic Information
The importance of probabilistic data becomes evident when considering the allocation of resources to prevent and mitigate climate change impacts. The existing climate scenario framework, the SSP/RCP approach, unfortunately, lacks this probabilistic dimension. This model, while based on extensive research, focuses on the most probable outcomes, which could potentially foster complacency and risk underestimation.
Building on the SSP/RCP Framework
The efforts of EDHEC Risk Climate Impact Institute aim to improve upon the current SSP/RCP approach by integrating probabilistic data. The Institute’s research emphasizes understanding the different uncertainties in the climate/economy system, from understanding the physics of climate change to the unpredictable nature of policy actions.
Toward Modular Scenario Architecture
Rebonato proposes a modular approach where distinct facets like damage function and climate physics can be modeled separately. This modular structure allows for traditional statistical techniques to be applied, providing a clearer understanding of potential outcomes, especially when policymakers and investors need this data the most.
Conclusion and Ongoing Research
The article concludes by shedding light on the ongoing research initiatives of the EDHEC Risk Climate Impact Institute. Their primary focus revolves around creating comprehensive probability distributions for possible climate outcomes, with works like Kainth and Melin (2023) and Rebonato and Kainth (2023a, 2023b) delving deeper into the subject. All these endeavors aim to offer a more holistic understanding of climate scenarios, emphasizing both the range of possible outcomes and their relative probabilities.
Rebonato’s article is a well-articulated exploration into the complexities of climate scenario analysis. It not only highlights the challenges faced but also offers avenues for improvement. His emphasis on probabilistic information and the need for a modular approach provides a fresh perspective on addressing the uncertainties of climate change. The article serves as a clarion call for researchers and policymakers to approach climate change with a renewed sense of rigor and innovation.