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A theoretical economic model for choosing efficient wildfire suppression strategies

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  • Mendes, Isabel

Abstract

In spite of increasing efforts by the authorities to qualitatively improve means of fire fighting, the wildfire scenario in Mediterranean regions has been worsening and one fears that this situation will only be further aggravated. Within a scenario of resource scarcity, huge budgetary constraints and other public choices of equivalent priority to that of combating wildfires, new wildfire management strategies seem necessary to achieve efficient answers to the increasing complexity of the economic and technical Mediterranean forest fire framework. In this paper, we seek to contribute towards clarifying how economic tools can be deployed to improve wildfire management and decrease fire risk within a context of economic scarcity and increasing forest fire risk. We describe how traditional microeconomic producer theory can be used to design a theoretical model enabling the choice of efficient wildfire suppression strategies. Along with linear programming techniques, GIS based data, and computer simulation programs, the efficient theoretical model enables those responsible to gain answers to some key questions arising throughout the course of wildfire process management, and particularly wildfire combat management.

Suggested Citation

  • Mendes, Isabel, 2010. "A theoretical economic model for choosing efficient wildfire suppression strategies," Forest Policy and Economics, Elsevier, vol. 12(5), pages 323-329, June.
  • Handle: RePEc:eee:forpol:v:12:y:2010:i:5:p:323-329
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    References listed on IDEAS

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    1. Jonathan Yoder & Mariam Lankoande, 2006. "An Econometric Model of Wildfire Suppression Productivity," Working Papers 2006-10, School of Economic Sciences, Washington State University.
    2. Prestemon, Jeffrey P. & Mercer, D. Evan & Pye, John M. & Butry, David T. & Holmes, Thomas P. & Abt, Karen L., 2001. "Economically Optimal Wildfire Intervention Regimes," 2001 Annual meeting, August 5-8, Chicago, IL 20470, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Mercer, D. Evan & Prestemon, Jeffrey P., 2005. "Comparing production function models for wildfire risk analysis in the wildland-urban interface," Forest Policy and Economics, Elsevier, vol. 7(5), pages 782-795, August.
    4. Riera, Pere & Mogas, Joan, 2004. "Evaluation of a risk reduction in forest fires in a Mediterranean region," Forest Policy and Economics, Elsevier, vol. 6(6), pages 521-528, October.
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    Cited by:

    1. Rodríguez y Silva, Francisco & González-Cabán, Armando, 2016. "Contribution of suppression difficulty and lessons learned in forecasting fire suppression operations productivity: A methodological approach," Journal of Forest Economics, Elsevier, vol. 25(C), pages 149-159.
    2. Duff, Thomas J. & Chong, Derek M. & Tolhurst, Kevin G., 2015. "Using discrete event simulation cellular automata models to determine multi-mode travel times and routes of terrestrial suppression resources to wildland fires," European Journal of Operational Research, Elsevier, vol. 241(3), pages 763-770.
    3. Isabel Mendes, 2018. "Social risks of forest fires: a methodological proposal for their monetary evaluation," Working Papers Department of Economics 2018/02, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    4. Thompson, Matthew P. & Haas, Jessica R. & Finney, Mark A. & Calkin, David E. & Hand, Michael S. & Browne, Mark J. & Halek, Martin & Short, Karen C. & Grenfell, Isaac C., 2015. "Development and application of a probabilistic method for wildfire suppression cost modeling," Forest Policy and Economics, Elsevier, vol. 50(C), pages 249-258.

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