Forest management decision making based on a real options approach: An application to a case in northeastern Argentina

Abstract

The Net Present Value (NPV) approach is widely applied to assess forest investments, but this method has serious shortcomings, which we propose to overcome by switching to the assessment through the Real Options Approach (ROA). The model in this paper starts with the simulation of the forest’s growth, combined with the projection of the products’ prices and valuing the assets using a binomial model. We include an option of postponement, determining the optimal period of felling. We find that ROA is more robust than the NPV approach because it relaxes the assumption of constancy of both the prices and the discount rate, allowing the determination of the optimal time of felling based on the growth rate of either the forest or the prices of its products. Contrary to the traditional NPV approach, the results obtained with ROA exhibit longer harvest turns and consequently higher profits. The key variable in the ROA, the Real Option Value (ROV) can be shown to be less (albeit moderately) sensitive to decreases of the discount rate than NPV. Moreover, ROV is moderately sensitive to decreases in the price of logs and is negligibly affected by rises in the costs of harvesting, loading and transporting rolls.

A Big Data approach to forestry harvesting productivity

“…The planted area with pine and eucalyptus used to be less than 100,000 hectares in 1990, and in 2012 the planted area rose to 990,030 hectares (Boscana & Boragno, 2017). The management of forest operations in industrial plantations is an extremely complex decision-making process involving ecological, productive, and economic factors, among others (Broz et al 2017a). This complexity is increased if the production cycle is considered (i.e.…”