Dynamic Cost-Loss Ratio Decision-making Model with an Autocorrelated Climate Variable

Abstract

Abstract A dynamic decision-making problem is considered involving the use of information about the autocorrelation of a climate variable. Specifically, an infinite horizon, discounted version of the dynamic cost-loss ratio model is treated, in which only two states of weather ( adverse” or “not adverse ) are possible and only two actions are permitted ( protect” or “do not protect ). To account for the temporal dependence of the sequence of states of the occurrence (or nonoccurrence) of adverse weather, a Markov chain model is employed. It is shown that knowledge of this autocorrelation has potential economic value to a decision maker, even without any genuine forecasts being available. Numerical examples are presented to demonstrate that a decision maker who erroneously follows a suboptimal strategy based on the belief that the climate variable is temporally independent could incur unnecessary expense. This approach also provides a natural framework for extension to the situation in which forecasts are ...