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Forest planning and productivity-risk trade-off through the Markowitz mean-variance model

Author

Listed:
  • Antonello Lobianco

    (LEF - Laboratoire d'Economie Forestière - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

  • Arnaud A. Dragicevic

    (LEF - Laboratoire d'Economie Forestière - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

  • Antoine Leblois

    (LEF - Laboratoire d'Economie Forestière - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

Abstract

In order to make a comparative assessment between productivity and risk, we study the forest planning by means of the Markowitz mean-value (M-V) portfolio model. By weighting the forest productivity with factors of future climate change effects, we compute the optimal tree species mixes, within reach of forest managers, in ninety French administrative departments. Considering three different productivity measures (wood production, carbon sequestration and economic valorization) and their respective variances, we find that: a) the empirical allocation lies between the optimizations of wood production and economic valorization; b) forest managers prefer low variance to high productivity, i.e. their revealed risk aversion is high; and c) unlike maximizing wood productivity or carbon sequestration, which leads to similar portfolios, maximizing the economic value of wood production decreases both the levels of wood production and carbon sequestration. Under high risk aversion, the economic valorization would lead to a high species specialization, which is very unlikely in reality. In all considered scenarios, the objectives set out in the Kyoto Protocol would be attained, which puts into question its relevance in terms of additionality.
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Suggested Citation

  • Antonello Lobianco & Arnaud A. Dragicevic & Antoine Leblois, 2015. "Forest planning and productivity-risk trade-off through the Markowitz mean-variance model," Working Papers hal-01627581, HAL.
  • Handle: RePEc:hal:wpaper:hal-01627581
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    References listed on IDEAS

    as
    1. Marielle Brunette & Arnaud A. Dragicevic & Jonathan Lenglet & Alexandra Niedzwiedz & Vincent Badeau & Jean-Luc Dupouey, 2014. "Portfolio Management of Mixed-Species Forests," Post-Print hal-01628375, HAL.
    2. Newman, D.H., 2002. "Forestry's golden rule and the development of the optimal forest rotation literature," Journal of Forest Economics, Elsevier, vol. 8(1), pages 5-27.
    3. Lecocq, Franck & Caurla, Sylvain & Delacote, Philippe & Barkaoui, Ahmed & Sauquet, Alexandre, 2011. "Paying for forest carbon or stimulating fuelwood demand? Insights from the French Forest Sector Model," Journal of Forest Economics, Elsevier, vol. 17(2), pages 157-168, April.
    4. Alexandre Sauquet & Ahmed Barkaoui & Sylvain Caurla & Philippe Delacote & Franck Lecocq, 2011. "Paying for forest carbon or stimulating fuel wood demand? Insights from the French Forest Sector Model," Post-Print halshs-00602112, HAL.
    5. Knoke, Thomas, 2008. "Mixed forests and finance -- Methodological approaches," Ecological Economics, Elsevier, vol. 65(3), pages 590-601, April.
    6. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    7. Wan, Yang & Clutter, Michael L. & Mei, Bin & Siry, Jacek P., 2015. "Assessing the role of U.S. timberland assets in a mixed portfolio under the mean-conditional value at risk framework," Forest Policy and Economics, Elsevier, vol. 50(C), pages 118-126.
    8. Merton, Robert C., 1972. "An Analytic Derivation of the Efficient Portfolio Frontier," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(4), pages 1851-1872, September.
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    Cited by:

    1. Dragicevic, Arnaud Z., 2019. "Rethinking the forestry in the Aquitaine massif through portfolio management," Forest Policy and Economics, Elsevier, vol. 109(C).
    2. Friedrich, Stefan & Paul, Carola & Brandl, Susanne & Biber, Peter & Messerer, Katharina & Knoke, Thomas, 2019. "Economic impact of growth effects in mixed stands of Norway spruce and European beech – A simulation based study," Forest Policy and Economics, Elsevier, vol. 104(C), pages 65-80.
    3. Nahuel Bautista & Bruno D. V. Marino & J. William Munger, 2021. "Science to Commerce: A Commercial-Scale Protocol for Carbon Trading Applied to a 28-Year Record of Forest Carbon Monitoring at the Harvard Forest," Land, MDPI, vol. 10(2), pages 1-22, February.
    4. Wildberg, Johannes & Möhring, Bernhard, 2019. "Empirical analysis of the economic effect of tree species diversity based on the results of a forest accountancy data network," Forest Policy and Economics, Elsevier, vol. 109(C).

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    More about this item

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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