Investment decisions under uncertainty—A methodological review on forest science studies

Abstract

Several parametric and non-parametric approaches have been developed to value financial assets. Yet, financial valuation techniques have only slowly percolated into disciplines concerned with the management of ecosystems. Particularly in forest management, decision-makers often find themselves confronted with extremely long time horizons and severely uncertain information. This requires careful valuation approaches, which are often underrepresented or even completely lacking in forest management. This paper gives a comprehensive overview on techniques for financial decision-making under uncertainty and develops future research needs. First, we analyse different approaches from the expected utility framework as well as option pricing models and robust optimisation techniques as possible approaches to make decisions on forest investments and giving a short review regarding forestry-related applications. Afterwards we discuss the suitability of the presented approaches to support decisions in forestry and conclude that robust optimisation techniques should be developed further, especially since erroneous financial data is likely to occur, as well as deviations from the assumption of normality. Currently, the maximization of financial robustness is probably the most adequate approach for many long-term decisions in forestry, such as selecting the optimum tree species composition. Further development of this approach appears possible and necessary. Finally, we come to the conclusion that even though it is intuitively clear that many long-term decisions should consider uncertainty, adequate financial valuation is not sufficiently developed within forest science. In the case of Central Europe, this may be an effect of ecological research dominating in forest science. Consequently, an intensification of the analysis of uncertainty in forest decision-making is necessary.