Abstract
The main objective of natural resource management is to create social and economic value while maintaining sustainability. In this paper, we introduce an enhanced method for simulating high-dimensional time series and apply it to Icelandic fishing resource management data. The methodology can be used in many contexts, but is particularly appropriate for simulating the many complex interactions involved in natural resource management. The simulations can be used to explore the sensitivity of resource management policies to future changes using an affinity parameter. Affinity, qualitatively similar to correlation, is a ordinal measure between –1 and +1 that models one's belief how much the future might behave like, or different from, the past. The main appeal of the method is its reliance on data and relative independence from assumptions about that data. In the paper, we apply it on data on Icelandic cod with encouraging results.
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