Discounting and catastrophic risk management

The risk management of complex coupled human-environmental systems essentially relies on discounting future losses and gains to their present values. These evaluations are used to justify catastrophic risks management decisions which may turn into benefits over long and uncertain time horizons. The misperception of proper discounting rates critically affects evaluations and may be rather misleading. Catastrophes are not properly treated within conventional economic theory. The lack of proper evaluations dramatically contributes to increasing the vulnerability of our society to human-made and natural disasters. Underestimation of rare low probability - high consequences potentially catastrophic scenarios (events) have led to the growth of buildings and industrial land and sizable value accumulation in flood (and other disaster) prone areas without paying proper attention to flood mitigations. A challenge is that an extreme event, say a once-in-300-year flood which occurs on average only once in 300 years, may have never occurred before in a given region. Therefore, purely adaptive policies relying on historical observations provide no awareness of the risk although, a 300-year flood may occur next year. For example, floods in Austria, Germany and the Czech Republic in 2002 were classified as 1000-, 500-, 250-, and 100-year events. Chernobyl nuclear disaster was evaluated as 106-year event. Yet common practice is to ignore these types of events as improbable events during a human lifetime. This paper analyzes the implications of potentially catastrophic events on the choice of discounting for long-term catastrophic risk management. It is shown that arbitrary discounting can be linked to "stopping time" events, which define the discount-related random horizon ("end of the world") of valuations. In other words, any discounting compares potential gains and losses only within a finite random discount-related stopping time horizon. The expected duration of this horizon for standard discount rates obtained from capital markets does not exceed a few decades and, as such, these rates cannot properly evaluate impacts of 1000-, 500-, 250-, 100- year catastrophes. The paper demonstrates that the correct discounting can be induced by the concept of stopping time, i.e. by explicit modelling of arrival time scenarios of potential catastrophes. In general, catastrophic events affect the induced discount rates, which alter the optimal mitigation efforts that, in turn, change events. The paper shows that stopping-time related discounting calls for the use of stochastic optimisation methods. Combined with explicit spatio-temporal catastrophe modelling, this induces the discounting which allows to properly focus risk management solutions on arrival times of potential catastrophic events rather then horizons of capital markets

Robust Management of Systemic Risks and Food-Water-Energy-Environmental Security: Two-Stage Strategic-Adaptive GLOBIOM Model

Critical imbalances and threshold exceedances can trigger a disruption in a network of interdependent systems. An insignificant-at-first-glance shock can induce systemic risks with cascading catastrophic impacts. Systemic risks challenge traditional risk assessment and management approaches. These risks are shaped by systemic interactions, risk exposures, and decisions of various agents. The paper discusses the need for the two-stage stochastic optimization (STO) approach that enables the design of a robust portfolio of precautionary strategic and operational adaptive decisions that makes the interdependent systems flexible and robust with respect to risks of all kinds. We established a connection between the robust quantile-based non-smooth estimation problem in statistics and the two-stage non-smooth STO problem of robust strategic-adaptive decisionmaking. The coexistence of complementary strategic and adaptive decisions induces systemic risk aversion in the form of Value-at-Risk (VaR) quantile-based risk constraints. The two-stage robust decision-making is implemented into a large-scale Global Biosphere Management (GLOBIOM) model, showing that robust management of systemic risks can be addressed by solving a system of probabilistic security equations. Selected numerical results emphasize that a robust combination of interdependent strategic and adaptive solutions presents qualitatively new policy recommendations, if compared to a traditional scenario-by-scenario decision-making analysis

Discounting, catastrophic risks management and vulnerability modeling

Traditional discounting dramatically affects the outcome of catastrophic risk management and spatio-temporal vulnerability modeling. The misperception of discount rates produces inadequate evaluations of risk management strategies, which may provoke catastrophes and significantly contribute to the increasing vulnerability of our society. This paper analyses the implication of potential catastrophic events on the choice of discounting. In particular, it shows the necessity of using proposed equivalent undiscounted stopping time criterion and Monte Carlo based stochastic optimization procedures