Stochastic-dynamic modelling of farm-level investments under uncertainty

Alisa Spiegel*, Wolfgang Britz, Utkur Djanibekov, Robert Finger

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)


In the light of uncertainties, high initial costs, and temporal managerial flexibility, the real options approach has gained interest as a valuation tool for different types of natural resources management problems. Yet, neither real options valuation method excels under consideration of variability of resource endowments, returns-to-scale and predefined sizes of options. We fill the methodological gap by developing a method based on Monte Carlo simulation, scenario tree reduction, and stochastic programming that is advantageous for valuing real options where timing, scale and interactions among constraints and alternatives matter. The method advances in straightforward conversion of deterministic programming applications based on the classical net present value approach into a real options framework, and in introducing complexity into existing real options models. We illustrate the method with a case study featuring investment options regarding the adoption, coppicing, and conversion of perennial biomass energy production systems.

Original languageEnglish
Article number104656
JournalEnvironmental Modelling and Software
Publication statusPublished - May 2020


  • Investment decision
  • Monte Carlo simulation
  • Perennial crop
  • Real options
  • Stochastic programming

Fingerprint Dive into the research topics of 'Stochastic-dynamic modelling of farm-level investments under uncertainty'. Together they form a unique fingerprint.

Cite this