Module 4: Risk Under Deep Uncertainty
Module 4 examines the challenges of quantifying financial risk given the complex dynamic nature of the climate-economy system, and explores how underpricing risk can result in decision-making that is, at best, sub-optimal, and at worse, potentially catastrophic. Unlike the risks normally encountered by an organization, climate risks are characterized by a higher probability of extreme impacts that are not only financial, but also existential.
When financial models fail to account for the likelihood of extreme values, climate change risk will be underpriced. As a result, decision-makers (governments, businesses, households) may make less-than-optimal choices that can exacerbate, rather than mitigate, the climate crisis (for example, by delaying or watering down action).
In this module, we’ll explore the complex dynamic nature of climate and economies, and consider various models for decision-making under deep uncertainty.
By the end of this unit, you will:
- Understand the uncertainty arising from the complex dynamic nature of climate systems, socio-political systems, and the inter-relationships between them;
- Define the “tail risks” in hazard distributions and understand the implications of “fat tails” on adaptation decision-making;
- Identify examples of models for decision-making under deep uncertainty (adaptation pathways, real options, robust decision making);
- Contemplate the relevance of the precautionary principle when the probability of catastrophic outcomes are greater than zero.