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Design of insurance contracts using stochastic programming in forestry planning

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  • Jose Mosquera
  • Mordecai Henig
  • Andres Weintraub

Abstract

This work addresses a tactical planning problem faced by a forestry firm, deciding which timber units to harvest and what roads to build to obtain the greatest possible benefits. We include uncertainty in prices by means of utility theory. This enables solutions to be found that the firm finds preferable to those obtained when risk aversion is ignored and makes it possible to design insurance contracts that benefit the firm while also being attractive to an insurer. Two types of contract are designed; one dependent on the firm’s operating result and the other independent of it. Metrics are then developed to quantify the benefits conferred by a contract, demonstrating that the latter contract type dominates the former. These results are then illustrated by applying them to a simplified planning problem of a forest owned by the Chilean forestry operator Millalemu. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Jose Mosquera & Mordecai Henig & Andres Weintraub, 2011. "Design of insurance contracts using stochastic programming in forestry planning," Annals of Operations Research, Springer, vol. 190(1), pages 117-130, October.
    • Handle: RePEc:spr:annopr:v:190:y:2011:i:1:p:117-130:10.1007/s10479-009-0676-3
    DOI: 10.1007/s10479-009-0676-3
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    References listed on IDEAS

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    1. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    2. Andrés Weintraub & Carlos Romero, 2006. "Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison," Interfaces, INFORMS, vol. 36(5), pages 446-457, October.
    3. Martell, David L. & Gunn, Eldon A. & Weintraub, Andres, 1998. "Forest management challenges for operational researchers," European Journal of Operational Research, Elsevier, vol. 104(1), pages 1-17, January.
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    Cited by:

    1. Miguel A. Lejeune & Janne Kettunen, 2017. "Managing Reliability and Stability Risks in Forest Harvesting," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 620-638, October.
    2. Miguel A. Lejeune & Janne Kettunen, 2018. "A fractional stochastic integer programming problem for reliability-to-stability ratio in forest harvesting," Computational Management Science, Springer, vol. 15(3), pages 583-597, October.
    3. Bernardo K. Pagnoncelli & Adriana Piazza, 2017. "The optimal harvesting problem under price uncertainty: the risk averse case," Annals of Operations Research, Springer, vol. 258(2), pages 479-502, November.
    4. Adriana Piazza & Bernardo Pagnoncelli, 2014. "The optimal harvesting problem under price uncertainty," Annals of Operations Research, Springer, vol. 217(1), pages 425-445, June.

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