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Resource Allocation Under Fire

Author

Listed:
  • Bayham, Jude
  • Yoder, Jonathan
Abstract
Rising suppression cost and severity of wildfires in the US has prompted debate over federal wildfire management policy. The empirical economic literature on wildfire has sought to identify the factors that contribute to wildfire growth and cost without directly modeling the role of resource allocation over the course of the fire. Without a model of suppression resource allocation, it is difficult to understand how policy will impact wildfire outcomes. We fill this gap in the literature by estimating an econometric model of suppression resource allocation, wildfire expenditures, growth, and home damage using a dynamic panel dataset on over 500 wildfires in the Western U.S. Our econometric model is grounded in a theory of resource allocation that shows how individual fire managers communicate their need for resources to a regional command unit through the resource's shadow price. This model allows us to parse the complex incentives of wildfire managers, and disentangle direct from indirect impacts of threatened assets, environmental conditions, and resource scarcity on wildfire expenditure, growth, and damage. Among other results, we find that the use of aircraft increases daily wildfire expenditures by 35% while highly trained ground crews mitigate the daily damage to threatened homes.

Suggested Citation

  • Bayham, Jude & Yoder, Jonathan, 2015. "Resource Allocation Under Fire," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 204143, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea15:204143
    DOI: 10.22004/ag.econ.204143
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    References listed on IDEAS

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    1. Prestemon, Jeffrey P. & Donovan, Geoffrey H., 2008. "AJAE Appendix for “Forecasting Resource Allocation Decisions Under Climate Uncertainty: Fire Suppression with Assessment of Net Benefits of Research”," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(4), pages 1-15, January.
    2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
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    4. Nada Petrovic & David L Alderson & Jean M Carlson, 2012. "Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-9, April.
    5. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    6. Kennedy, Peter E, 1981. "Estimation with Correctly Interpreted Dummy Variables in Semilogarithmic Equations [The Interpretation of Dummy Variables in Semilogarithmic Equations]," American Economic Review, American Economic Association, vol. 71(4), pages 801-801, September.
    7. David Roodman, 2006. "How to Do xtabond2," North American Stata Users' Group Meetings 2006 8, Stata Users Group.
    8. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    9. Jeffrey P. Prestemon & Geoffrey H. Donovan, 2008. "Forecasting Resource-Allocation Decisions Under Climate Uncertainty: Fire Suppression with Assessment of Net Benefits of Research," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 1118-1129.
    10. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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    Cited by:

    1. Hazra, Devika & Gallagher, Patricia, 2022. "Role of insurance in wildfire risk mitigation," Economic Modelling, Elsevier, vol. 108(C).
    2. Wibbenmeyer, Matthew & Plantinga, Andrew J. & Walsh, Randall, 2020. "Priorities and Effectiveness in Wildfire Management: Evidence from Fire Spread in the Western US," RFF Working Paper Series 20-21, Resources for the Future.
    3. Bayham, Jude & Bryan, Calvin, 2023. "The Economics of Wildland Firefighting Aviation Procurement and Effectiveness," Western Economics Forum, Western Agricultural Economics Association, vol. 21(2), September.
    4. Rossi, David & Kuusela, Olli-Pekka & Dunn, Christopher, 2022. "A microeconometric analysis of wildfire suppression decisions in the Western United States," Ecological Economics, Elsevier, vol. 200(C).
    5. Bayham, Jude & Yoder, Jonathan K., 2018. "A Real Barn Burner: The Effectiveness of Home Protection During Wildfire," 2018 Annual Meeting, August 5-7, Washington, D.C. 274302, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    Resource /Energy Economics and Policy;

    JEL classification:

    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy

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