IDEAS home Printed from https://ideas.repec.org/a/eee/ecolec/v68y2009i11p2825-2833.html
   My bibliography  Save this article

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

Author

Listed:
  • Hildebrandt, Patrick
  • Knoke, Thomas

Abstract

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0921-8009(09)00222-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    3. 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.
    4. 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.
    5. Knoke, Thomas, 2008. "Mixed forests and finance -- Methodological approaches," Ecological Economics, Elsevier, vol. 65(3), pages 590-601, April.
    6. 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.
    7. Krysiak, Frank C., 2006. "Entropy, limits to growth, and the prospects for weak sustainability," Ecological Economics, Elsevier, vol. 58(1), pages 182-191, June.
    8. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    9. Knoke, Thomas & Seifert, Thomas, 2008. "Integrating selected ecological effects of mixed European beech–Norway spruce stands in bioeconomic modelling," Ecological Modelling, Elsevier, vol. 210(4), pages 487-498.
    10. 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.
    11. 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.
    12. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    13. D. Goldfarb & G. Iyengar, 2003. "Robust Portfolio Selection Problems," Mathematics of Operations Research, INFORMS, vol. 28(1), pages 1-38, February.
    14. Dawei Bai & Tamra Carpenter & John Mulvey, 1997. "Making a Case for Robust Optimization Models," Management Science, INFORMS, vol. 43(7), pages 895-907, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    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. Roessiger, Joerg & Griess, Verena C. & Härtl, Fabian & Clasen, Christian & Knoke, Thomas, 2013. "How economic performance of a stand increases due to decreased failure risk associated with the admixing of species," Ecological Modelling, Elsevier, vol. 255(C), pages 58-69.
    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. Chang, Sun Joseph, 2020. "Twenty one years after the publication of the generalized Faustmann formula," Forest Policy and Economics, Elsevier, vol. 118(C).
    6. Luz Maria Castro & Fabian Härtl & Santiago Ochoa & Baltazar Calvas & Leonardo Izquierdo & Thomas Knoke, 2018. "Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations," Journal of Bioeconomics, Springer, vol. 20(2), pages 183-211, July.
    7. 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.
    8. Pinnschmidt, Arne & Yousefpour, Rasoul & Nölte, Anja & Hanewinkel, Marc, 2023. "Tropical mixed-species plantations can outperform monocultures in terms of carbon sequestration and economic return," Ecological Economics, Elsevier, vol. 211(C).
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Knoke, Thomas, 2008. "Mixed forests and finance -- Methodological approaches," Ecological Economics, Elsevier, vol. 65(3), pages 590-601, April.
    2. 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.
    3. Ragavendran Gopalakrishnan & Eric Bax & Krishna Prasad Chitrapura & Sachin Garg, 2015. "Portfolio Allocation for Sellers in Online Advertising," Papers 1506.02020, arXiv.org.
    4. Los, Cornelis A. & Tungsong, Satjaporn, 2008. "Investment Model Uncertainty and Fair Pricing," MPRA Paper 8859, University Library of Munich, Germany.
    5. Erindi Allaj, 2020. "The Black–Litterman model and views from a reverse optimization procedure: an out-of-sample performance evaluation," Computational Management Science, Springer, vol. 17(3), pages 465-492, October.
    6. Raphael Hauser & Vijay Krishnamurthy & Reha Tutuncu, 2013. "Relative Robust Portfolio Optimization," Papers 1305.0144, arXiv.org, revised May 2013.
    7. Giorgio Costa & Roy H. Kwon, 2021. "Data-driven distributionally robust risk parity portfolio optimization," Papers 2110.06464, arXiv.org.
    8. Ankit Dangi, 2013. "Financial Portfolio Optimization: Computationally guided agents to investigate, analyse and invest!?," Papers 1301.4194, arXiv.org.
    9. Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    10. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    11. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    12. David E. Allen & Michael McAleer & Abhay K. Singh, 2019. "Daily market news sentiment and stock prices," Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
    13. Dipankar Mondal & N. Selvaraju, 2022. "Convexity, two-fund separation and asset ranking in a mean-LPM portfolio selection framework," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 225-248, March.
    14. Rostagno, Luciano Martin, 2005. "Empirical tests of parametric and non-parametric Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) measures for the Brazilian stock market index," ISU General Staff Papers 2005010108000021878, Iowa State University, Department of Economics.
    15. Shaikh, Salman, 2013. "Investment Decisions by Analysts: A Case Study of KSE," MPRA Paper 53802, University Library of Munich, Germany.
    16. Boes, M.J., 2006. "Index options : Pricing, implied densities and returns," Other publications TiSEM e9ed8a9f-2472-430a-b666-9, Tilburg University, School of Economics and Management.
    17. Nathan Jensen, 2007. "International institutions and market expectations: Stock price responses to the WTO ruling on the 2002 U.S. steel tariffs," The Review of International Organizations, Springer, vol. 2(3), pages 261-280, September.
    18. Roman Mestre, 2021. "A wavelet approach of investing behaviors and their effects on risk exposures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    19. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
    20. Sharpe, William F, 1991. "Capital Asset Prices with and without Negative Holdings," Journal of Finance, American Finance Association, vol. 46(2), pages 489-509, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolec:v:68:y:2009:i:11:p:2825-2833. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolecon .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.