About the Model
The aim of the model is to conduct a conceptual and model-based analysis of structural and financial measures for reducing the impacts of climate change and variability on regional welfare, agricultural production, supporting objectives of sustainable regional development. Identification and planning of proper land use policies for dealing with extremes may essentially decrease regional vulnerability and catastrophic losses which otherwise produce dramatic and long-term consequences for societies and economy. The model is comprised of the four main modules: hazard simulation, vulnerability estimation, a multi-agent accounting system, and a decision-making stochastic optimization procedure. The model addresses the specifics of catastrophic risks: highly mutually dependent and spatially distributed endogenous risks, the lack of historical location-specific observations (unknown risks), the need for long-term perspectives, robust strategies, and explicit treatment of spatial and temporal heterogeneities of involved agents such as farmers, producers, households, local and central governments, land use planners, water authorities, insurers, and investors..

How the Model works
A case study region is subdivided into grid cells or sub-regions with “homogenous” properties, i.e., the grid cells (not necessarily of strict geometrical form) may correspond to a collection of houses, a collection of land plots with similar land use practices (e.g. agricultural land), a segment of a pipe line, urban area, rural settlement. The choice of cells provides a desirable representation of potential catastrophic losses. The cells consist of the value of the physical structures. Each grid is characterized by a property value. The hazard module in a Monte Carlo fashion simulates catastrophes as they may happen in reality. The vulnerability module estimates losses to property values according to vulnerability curves. The multi-agent accounting system derives histograms of gains and losses to the agents exposed to and involved in land use planning and catastrophe management. The losses substantially depend on past and current decisions. To minimize the losses and achieve stable economic performance of the region, spatially explicit decision-making stochastic optimization procedure tracks the gains and losses and adjusts the decision variables towards fulfillment of goals and constraints of the agents.

Background
The projects builds on the integrated catastrophic risks management model developed at IIASA for a number of catastrophic risks, e.g., earthquakes, floods, livestock epidemics. Management of agricultural risks is often a more challenging task than any other type of risks due to the lower levels of income for rural areas as compared with many other areas.

Challenges
Novel stochastic optimization methodology and downscaling procedures are used for the design of robust strategies coherent with goals and constraints of involved agents. Fast Monte Carlo stochastic optimization techniques allowing to deal with significant computational complexities of the problems are being developed and implemented in the model. Policy analysis is guided by GIS-based catastrophe models and stochastic optimization methods with respect to location-specific risk exposures. The model uses economically sound risk indicators leading to convex stochastic optimization problems strongly connected with non-convex insolvency constraint and Conditional Value-at-Risk (CVaR).

Fast facts
The model permits to analyze the implications of extreme events on the proper choice of discounting for evaluation of policies with long-term perspectives, e.g. climate change and catastrophe management projects such as construction and maintenance of dikes. The misperception of discounting may dramatically contribute to the alarming increase of regional vulnerability.
The model has been used for designing optimal portfolios of financial instruments in catastrophe management, e.g. such as a composition of a multi-pillar flood loss-spreading program involving partial compensation to flood victims by the central government, a mandatory public-private insurance on the basis of location-specific exposures, a contingent ex-ante credit to reinsure the insurance liabilities, a catastrophe bond.

Responsible for this page: Elisabeth Kawczynski
Last updated: 03 Nov 2011