Evaluating alternative prescribed burning policies to reduce net economic damages from wildfire

Download
(PDF; )
Cite
Feedback

Abstract

We estimate a wildfire risk model with a new measure of wildfire output, intensity-weighted risk and use it in Monte Carlo simulations to estimate welfare changes from alternative prescribed burning policies. Using Volusia County, Florida as a case study, an annual prescribed burning rate of 13% of all forest lands maximizes net welfare; ignoring the effects on wildfire intensity may underestimate optimal rates of prescribed burning. Our estimated supply function for prescribed fire services is inelastic, suggesting that increasing contract prescribed fire services on public lands may produce rapidly escalating costs for private landowners and unintended distributional and “leakage” effects.

  • Citation: Mercer, D. Evan; Prestemon, Jeffrey P.; Butry, David T.; Pye, John M. 2007. Evaluating alternative prescribed burning policies to reduce net economic damages from wildfire. Amer. J. Agr. Econ., Vol. 89(1): 63-77
  • Keywords: policy, prescribed fire, stochastic dominance, wildfire
  • Posted Date: February 20, 2007
  • Modified Date: March 9, 2017

    • Print Publications Are No Longer Available

    In an ongoing effort to be fiscally responsible, the Southern Research Station (SRS) will no longer produce and distribute hard copies of our publications. Many SRS publications are available at cost via the Government Printing Office (GPO). Electronic versions of publications may be downloaded, printed, and distributed.

    Publication Notes

    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
    • Our online publications are scanned and captured using Adobe Acrobat. During the capture process some typographical errors may occur. Please contact the SRS webmaster if you notice any errors which make this publication unusable.
    • To view this article, download the latest version of Adobe Acrobat Reader.