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Optimizing the shares of native tree species in forest plantations with biased financial parameters


  • Hildebrandt, Patrick
  • Knoke, Thomas


Addressing uncertainty is a key requirement to follow the principle of precaution in sustainable ecosystem management. The maximization of worst-case outcomes according to the "maximin" decision rule, based on the two parameters mean and variance of a financial indicator, is a prominent approach to integrate uncertainty in decision-making. In forestry, the problem of selecting the optimum tree species combination for a forest plantation investment can be seen as a problem of optimal portfolio selection, to be solved according to the "maximin" decision rule. Yet, it is well known that portfolios computed from expected means and variances are highly sensitive to changes in the estimated parameters. The financial results may be poor if we rely too much on the historical data. This paper tests an extended worst-case model that considers a lower bound for the expected mean net present value (NPV) of a tree species portfolio and an upper bound for its variance. Biased expected mean NPVs, variances and correlations for the tree species Picea abies [L.] Karst. (Spruce) and Fagus sylvatica L. (Beech) were used to test the variability of the resulting tree species portfolios (27 scenarios). A comprehensive simulated data set, which was adopted from an existing study and defined as the independent reference, served to evaluate the financial performance of the tree species portfolios obtained from optimization with the biased data. Compared with the results of classical worst-case optimization instances, it was feasible to reduce the variability of tree species shares effectively when the optimization was carried out with the extended worst-case approach. Furthermore, the financial performance of this approach was better when tested with the independent data. The worst-case forest NPVs achieved with the extended approach were on average 10% (statistical confidence 0.95) or 147% (statistical confidence 0.99) greater in comparison to the results of the classical approach. The influence of the uncertainty parameter selection was tested and the results were discussed against the controversial viewpoints on the usefulness of the "information-gap decision theory". Finally, the significance of our results for sustainable ecosystem management is pointed out.

Suggested Citation

  • Hildebrandt, Patrick & Knoke, Thomas, 2009. "Optimizing the shares of native tree species in forest plantations with biased financial parameters," Ecological Economics, Elsevier, vol. 68(11), pages 2825-2833, September.
  • Handle: RePEc:eee:ecolec:v:68:y:2009:i:11:p:2825-2833

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    References listed on IDEAS

    1. Ross, Stephen A., 1976. "The arbitrage theory of capital asset pricing," Journal of Economic Theory, Elsevier, vol. 13(3), pages 341-360, December.
    2. Wayne Y. Lee & Ramesh K. S. Rao, 1988. "Mean Lower Partial Moment Valuation and Lognormally Distributed Returns," Management Science, INFORMS, vol. 34(4), pages 446-453, April.
    3. Moog, Martin & Borchert, Herbert, 2001. "Increasing rotation periods during a time of decreasing profitability of forestry -- a paradox?," Forest Policy and Economics, Elsevier, vol. 2(2), pages 101-116, June.
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    6. repec:eee:ecomod:v:210:y:2008:i:4:p:487-498 is not listed on IDEAS
    7. Yakov Ben-Haim, 2005. "Value-at-risk with info-gap uncertainty," Journal of Risk Finance, Emerald Group Publishing, vol. 6(5), pages 388-403, November.
    8. Knoke, Thomas & Moog, Martin, 2005. "Timber harvesting versus forest reserves--producer prices for open-use areas in German beech forests (Fagus sylvatica L.)," Ecological Economics, Elsevier, vol. 52(1), pages 97-110, January.
    9. Edwards, Steven F. & Link, Jason S. & Rountree, Barbara P., 2004. "Portfolio management of wild fish stocks," Ecological Economics, Elsevier, vol. 49(3), pages 317-329, July.
    10. Figge, Frank & Hahn, Tobias, 2004. "Sustainable Value Added--measuring corporate contributions to sustainability beyond eco-efficiency," Ecological Economics, Elsevier, vol. 48(2), pages 173-187, February.
    11. Knoke, Thomas, 2008. "Mixed forests and finance -- Methodological approaches," Ecological Economics, Elsevier, vol. 65(3), pages 590-601, April.
    12. Dawei Bai & Tamra Carpenter & John Mulvey, 1997. "Making a Case for Robust Optimization Models," Management Science, INFORMS, vol. 43(7), pages 895-907, July.
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    Cited by:

    1. Hahn, W. Andreas & Härtl, Fabian & Irland, Lloyd C. & Kohler, Christoph & Moshammer, Ralf & Knoke, Thomas, 2014. "Financially optimized management planning under risk aversion results in even-flow sustained timber yield," Forest Policy and Economics, Elsevier, vol. 42(C), pages 30-41.
    2. Knoke, Thomas & Paul, Carola & Härtl, Fabian & Castro, Luz Maria & Calvas, Baltazar & Hildebrandt, Patrick, 2015. "Optimizing agricultural land-use portfolios with scarce data—A non-stochastic model," Ecological Economics, Elsevier, vol. 120(C), pages 250-259.
    3. repec:eee:ecomod:v:255:y:2013:i:c:p:58-69 is not listed on IDEAS
    4. Nguyen, Trung Thanh & Nghiem, Nhung, 2016. "Optimal forest rotation for carbon sequestration and biodiversity conservation by farm income levels," Forest Policy and Economics, Elsevier, vol. 73(C), pages 185-194.
    5. Ben-Haim, Yakov & Osteen, Craig D. & Moffitt, L. Joe, 2013. "Policy dilemma of innovation: An info-gap approach," Ecological Economics, Elsevier, vol. 85(C), pages 130-138.
    6. Hildebrandt, Patrick & Knoke, Thomas, 2011. "Investment decisions under uncertainty--A methodological review on forest science studies," Forest Policy and Economics, Elsevier, vol. 13(1), pages 1-15, January.


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