IDEAS home Printed from https://ideas.repec.org/p/ags/aaea16/235775.html
   My bibliography  Save this paper

Sensitivity of miscanthus supply: Application of Faustmann's rule in deterministic and stochastic cases

Author

Listed:
  • Ben Fradj, Nosra
  • Jayet, Pierre-Alain

Abstract

This paper aims to analyze the sensitivity of the supply of a perennial crop, i.e, miscanthus for which high interest arises when it is dedicated to second generation biofuels production. We develop a methodology based on the "Faustmann's rule" usually used in forest management fields. We first determine the yield growth function over time and the discounted present value of this crop in a deterministic case. Then, a stochastic process based on a beta distribution is introduced to manage the variability of miscanthus yield. A short-term agricultural model (AROPAj) is used to highlight the large scale impact of annual yield randomization. This analysis details the impact assessment regarding optimal length cycle, land use, N input demand and nitrate losses. Ideally, miscanthus would be grown on marginal land. However, miscanthus profitability causes farmers to cultivate it on the most productive land generally devoted to food crops. An increase in yield potential leads to significant direct and indirect land re-allocation, favoring therefore the competition between food and biofuel production.This change in land use leads to a substantial decrease in N-input application and, consequently, in nitrate losses. Results significantly changes when yields are affected by annual randomized variability. Throughout a sensitivity analysis, we notice that yields, renewal cycle costs and the discount rate may interact with yield randomization and significantly affect the future profitability of miscanthus.

Suggested Citation

  • Ben Fradj, Nosra & Jayet, Pierre-Alain, 2016. "Sensitivity of miscanthus supply: Application of Faustmann's rule in deterministic and stochastic cases," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235775, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea16:235775
    DOI: 10.22004/ag.econ.235775
    as

    Download full text from publisher

    File URL: http://ageconsearch.umn.edu/record/235775/files/aaea2016.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Clarke, Harry R. & Reed, William J., 1989. "The tree-cutting problem in a stochastic environment : The case of age-dependent growth," Journal of Economic Dynamics and Control, Elsevier, vol. 13(4), pages 569-595, October.
    2. Willassen, Yngve, 1998. "The stochastic rotation problem: A generalization of Faustmann's formula to stochastic forest growth," Journal of Economic Dynamics and Control, Elsevier, vol. 22(4), pages 573-596, April.
    3. Carl H. Nelson & Paul V. Preckel, 1989. "The Conditional Beta Distribution as a Stochastic Production Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 370-378.
    4. Miller, Robert A. & Voltaire, Karl, 1983. "A stochastic analysis of the tree paradigm," Journal of Economic Dynamics and Control, Elsevier, vol. 6(1), pages 371-386, September.
    5. Cyril Bourgeois & Nosra Ben-Fradj & Mélissa Clodic & Pierre-Alain Jayet, 2011. "How cost-effective is a mixed policy targeting the management of three pollutants from N-fertilizers," Working Papers 2011/03, INRA, Economie Publique.
    6. Godard, C. & Roger-Estrade, J. & Jayet, P.A. & Brisson, N. & Le Bas, C., 2008. "Use of available information at a European level to construct crop nitrogen response curves for the regions of the EU," Agricultural Systems, Elsevier, vol. 97(1-2), pages 68-82, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Crop Production/Industries; Environmental Economics and Policy; Resource /Energy Economics and Policy; Risk and Uncertainty;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ags:aaea16:235775. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaeaaea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.