Modeling Awareness & Decision Making: The Case of Climate Change and Water Resources
12:00 - 13:30
We can classify future problems and their contingencies into 3 level of increasing unawareness: White Swans, Grey Swans and Black Swans (Taleb 2007). White Swans are problems with known sets of probable outcomes and contingencies (i.e. complete awareness). Grey Swans are problems that are known and we are aware that the complete set of outcomes and contingencies is unknown. Black Swan problems involve unforeseen problems (i.e. totally unaware).
Climate change is a classic Grey Swan. Climate change is expected to alter the mean, variance, timing and intensity of rainfall. The spatial events of temporal changes in rainfall will determine the volume of water available for irrigation within a river basin. The future realized emission path is unknown and when combined with the complexities of climate modeling and downscaling issues associated with hydrological responses, an incomplete problem set exists. This poses complex problems for decision makers to ensure that environmental, social and economic objectives are achieved.
This paper illustrates the differences of allocating water resources using a state contingent analysis versus an expected value approach in Australia’s Murray-Darling Basin. The comparison of these two approaches helps illustrates the need to be able to separate the environmental signal and the management response to that signal. By separating the management response inductive reasoning and differential learning about climate change can be represented. This representation then helps prevent a Grey Swan turn Black.
Key Words: Awareness, Expected Value, State Contingent Analysis, Uncertainty
JEL Codes: D81, Q15, Q54