Environmental Management

, Volume 44, Issue 4, pp 776–788 | Cite as

Determinants of National Fire Plan Fuels Treatment Expenditures: A Revealed Preference Analysis for Northern New Mexico

  • Curt ShepherdEmail author
  • Kristine Grimsrud
  • Robert P. Berrens


The accumulation of fire fuels in forests throughout the world contributes significantly to the severity of wildfires. To combat the threat of wildfire, especially in the wildland-urban interface (WUI), US federal land management agencies have implemented a number of forest restoration and wildfire risk reduction programs. In the spirit of revealed preference analyses, the objective of this study is to investigate the pattern and determinants of National Fire Plan (NFP) expenditures for fuel reduction treatments in northern New Mexico (USA). Estimation results from a set of Generalized Estimating Equations models are mixed with respect to risk reduction hypotheses, and also raise issues regarding how risk reduction should be defined for a region characterized by both pockets of urban sprawl into the WUI and large areas of chronic rural poverty. Program preferences for project funding under the federal Collaborative Forest Restoration Program in New Mexico are shown to be distinctly different (e.g., exhibiting greater concern for social equity) than for other NFP-funded projects.


Revealed preference Public expenditures Wildfire risk Social equity Generalized Estimation Equations 



Funding was provided under Research Joint Venture Agreement 06-JV-199 between the Rocky Mountain Research Station (RMRS), U.S. Department of Agriculture’s Forest Service (FS), and the University of New Mexico. We thank Carl Edminster and Carolyn Hull Sieg (RMRS, Flagstaff) for research support, and the FS personnel who provided data: Susan Lee (Fire Coordinator, Southwestern Region), Paul Fink (Region 3, Forester); Tom Johnston (Fuels Specialist, Santa Fe National Forest); and Thomas Marks (Timber Management Officer, Cibola National Forest). We thank the anonymous reviewers for their constructive comments. All errors and opinions are solely those of the authors. We thank Joe Little and John Talberth for help in the initial data collection and in editing.


  1. Alkire C (2004) The federal wildland fire budget—let’s prepare, not just react—emphasis on reduced financial and ecological costs. The Wilderness Society, Washington D.C. Accessed 13 Aug 2007
  2. Ballinger GA (2004) Using generalized estimating equations for longitudinal data analysis. Organizational Research Methods 7(2):127–150CrossRefGoogle Scholar
  3. Berrens R, Bohara A, Baker A, Baker K (1999) Revealed preferences of a state bureau: case of New Mexico’s underground storage tank program. Journal of Policy Analysis and Management 18(2):303–326CrossRefGoogle Scholar
  4. Berry AH, Hesseln H (2004) The effect of the wildland-urban interface on prescribed burning costs in the pacific northwestern United States. Journal of Forestry 102(6):33–37Google Scholar
  5. Calkin DE, Gebert KM (2006) Modeling fuel treatment costs on forest lands in the western United States. Western Journal of Applied Forestry 21(4):217–221Google Scholar
  6. Calkin DE, Gebert KM, Jones JG, Neilson RP (2005) Forest service large fire area burned and suppression expenditure trends—1970–2002. Journal of Forestry 103:179–180Google Scholar
  7. Donovan G, Brown T (2007) An alternative incentive structure for wildfire management on national forest land. Forest Science 51(5):387–395Google Scholar
  8. EMNRD (2004) New Mexico communities at risk assessment plan. Santa Fe, Energy, Minerals, and Natural Resources Department, Forestry Division. Accessed 13 Aug 2007
  9. ERS (2004) Rural income, poverty, and welfare. Economic Research Services USDA, Washington D.C. Accessed 13 Aug 2007
  10. FAO (2001) Global forest fire assessment 1990-2000. Food and Agriculture Organization of the United Nations, Forest resources assessment programme working paper 55Google Scholar
  11. Fernandez L (2004) Revealed preferences of an international trade and environment institution. Land Economics 80(2):224–238CrossRefGoogle Scholar
  12. Gantenbein D (2002) Burning questions. Scientific American 80(5):82–89CrossRefGoogle Scholar
  13. Ghisletta P, Spini D (2004) An introduction to generalized estimating equations and an application to assess selectivity effects in a longitudinal study on very old individuals. Journal of Educational and Behavioral Statistics 29(4):421–437CrossRefGoogle Scholar
  14. Gregory L (2005) Following the money: national fire plan funding and implementation. The Wilderness Society, Washington, D.C. Accessed 13 Aug 2007
  15. Gude P, Rasker R, van den Noort J (2007) Potential for future development on fire prone lands. Manuscript submitted to Journal of the American Planning Association. Accessed 1 Mar 2008
  16. Hardin JW, Hilbe JM (2003) Generalized estimating equations. Chapman and Hall/CRC, Boca RatonGoogle Scholar
  17. Howarth RB, Wilson MA (2006) A theoretical approach to deliberative valuation: aggregation by mutual consent. Land Economics 82(1):1–16Google Scholar
  18. Liang K-Y, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrica 73:13–22CrossRefGoogle Scholar
  19. Lynn K, Gerlitz W (2005) Mapping the relationship between wildfire and poverty. A collaborative project between the National Network of Forest Practitioners, Resource Innovations at the University of Oregon, and the United States Department of Agriculture Forest Service State and Private Forestry, Cooperative Programs and Research and Development [unpublished]. Accessed 15 Nov 2008
  20. McCarthy LF (2004) Snapshot: state of the national fire plan. Forest Trust, Santa Fe, NM. Accessed 12 July 2007
  21. McFadden D (1975) The revealed preferences of a government bureaucracy: theory. Bell Journal of Economics 6(2):401–416CrossRefGoogle Scholar
  22. McFadden D (1976) The revealed preferences of a government bureaucracy: empirical evidence. Bell Journal of Economics 7(1):55–72CrossRefGoogle Scholar
  23. Miller C (2003) Wildland fire use: a wilderness perspective on fuel management. Aldo Leopold Wilderness Research Institute. Rocky Mountain Research Station. USDA Forest Service, Missoula, MT (USDA Forest Service Proceedings RMRS-P-29)Google Scholar
  24. Mittlehammer R, Judge GG, Miller D (2000) Econometric foundations. Cambridge University PressGoogle Scholar
  25. Moore MR, Maclin EB, Kershner DW (2001) Testing theories of agency behavior: evidence from hydropower project relicensing decisions of the Federal Energy Regulatory Commission. Land Economics 77(3):423–442CrossRefGoogle Scholar
  26. Moseley C, McDaniel J (2006) Forest management contracting for the US forest service in New Mexico: in-state competitiveness and the use of guest workers, Ecosystem Workforce Program (working paper 15). Accessed 5 Sept 2008
  27. Moseley C, Toth N (2004) Fire hazard reduction and economic opportunity: How are the benefits of the national fire plan distributed? Society and Natural Resources 17:701–716CrossRefGoogle Scholar
  28. NAPA (2002) Wildfire suppression: strategies for containing costs. A report by a panel of the National Academy of Public Administration, Washington, DCGoogle Scholar
  29. Nelder JA, Wedderburn RWM (1972) Generalized linear models. Journal of the Royal Statistical Society Series B 54:3–40Google Scholar
  30. Niemi E, Lee K (2001) Wildfire and poverty: an overview of the interactions among wildfires, fire-related programs, and poverty in the western states. Prepared by EcoNorthwest, Eugene, Oregon, for the Center for Watershed and Community Health. Accessed 13 Aug 2007
  31. OCS (Office of Community Services at Fort Lewis College) (2004) Lessons and strategies for community forestry capacity building. Prepared by: The Four Corners Sustainable Forests Partnership, for the USDA FS, RMRS. Flagstaff, AZ. Accessed 13 Aug 2007
  32. Parkins JR (2006) De-centering environmental governance: a short history and analysis of democratic processes in the forest sector of Alberta, Canada. Policy Sciences 39:183–203CrossRefGoogle Scholar
  33. PIC (2002) An introduction to the national fire plan: history, structure, and relevance to communities. Prepared by: Pinchot Institute for Conservation, Washington D.C. Accessed 13 Aug 2007
  34. Prante T, Thacher JA, McCollum DW, Berrens RP (2007) Building social capital in forest communities: analysis of New Mexico’s Collaborative Forest Restoration Program. Natural Resources Journal 47(4):(in press)Google Scholar
  35. Rasmussen K, Hibbard M, Lynn K (2007) Wildland fire management as conservation-based development: an opportunity for reservation communities? Society and Natural Resources 20:497–510CrossRefGoogle Scholar
  36. Rideout DB, Omi PN (1995) Estimating the cost of fuels treatment. Forest Science 41(4):664–674Google Scholar
  37. Rollins MG, Keane RE, Zhu Z, Menakis J, Hann WJ, Shlisky AJ (2003) LANDFIRE; a nationally consistent and locally relevant interagency fire, fuels and risk assessment. Proceedings of the 2nd International Wildland Fire Ecology and Fire Management Congress (11/16-20/2003). Orlando, FL. Accessed 15 Nov 2008
  38. Schmidt K, Menakis J, Hardy C, Bunnell D, Sampson N, Cohen J (2002) Development of coarse scale spatial data for wildland fire and fuels management. RMRS GTR-87. USDA Forest Service. Rocky Mountain Research Station, Ogden, UTGoogle Scholar
  39. Shahbaz B, Ali T, Suleri AQ (2007) A critical analysis of forest policies of Pakistan: implications for sustainable livelihoods. Mitigation and Adaptation Strategies for Global Change 12:441–453CrossRefGoogle Scholar
  40. Silvis Lab (2005) The Wildland-Urban interface (WUI) defined. Forest Ecology and Management, University of Wisconsin–Madison. Accessed 13 Aug 2007
  41. Steelman TA, Burke CA (2007) Is wildfire policy in the United State sustainable? Journal of Forestry 105(2):67–72Google Scholar
  42. Stephens SL, Ruth LW (2005) Federal forest-fire policy in the United States. Ecological Applications 15(2):532–542CrossRefGoogle Scholar
  43. Stewart S, Radeloff V, Hammer R, Fried J, Holcomb S, McKeefry J (2005) “Mapping the Wildland Urban Interface and Projecting its Growth to 2030” Silvis Lab, Forest Ecology and Management, University of Wisconsin–Madison. Accessed 12 July 2007
  44. Sun C, Zhang D (2001) Forest resources, government policy, and investment location decisions of the forest products industry in the southern United States. Forest Science 47(2):169–177Google Scholar
  45. Talberth J, Berrens RP, McKee M, Jones M (2006) Averting and insurance decisions in the wildland urban interface: implications of survey and experimental data for wildfire risk reduction policy. Contemporary Economic Policy 24(2):203–223CrossRefGoogle Scholar
  46. USCB (2000) American factfinder: Summary Table SF-3. U.S. Census Bureau, Washington, D.C.Google Scholar
  47. USDA/OIG (2006) “Large Fire Suppression Costs” Forest Service Audit report, Office of the Inspector General-Western Region, report no. 08601-44-SFGoogle Scholar
  48. USDA/USDI (2001) A collaborative approach for reducing wildland fire risks to communities and the environment: 10-year comprehensive strategy. USDA/USDI, Washington, D.C. Accessed 13 Aug 2007
  49. USDI/USDA (2006) Protecting people and natural resources—a cohesive fuels treatment strategy. USDI/USDA, Washington D.C. Accessed 13 Aug 2007
  50. Wedderburn RWM (1974) Quasi-likelihood functions generalized linear models, and the Gauss-Newton method. Biometrika 61:439–447Google Scholar
  51. Wilson MA, Howarth RB (2002) Discourse-based valuation of ecosystem services: establishing fair outcomes through group deliberation. Ecological Economics (41):431-443Google Scholar
  52. Yoder J, Blatner K (2004) Incentives and timing for prescribed fire for wildfire risk management. Journal of Forestry 102(6):38–41Google Scholar
  53. Zeger SL, Liang K-Y (1986) Longitudinal data analysis for discrete and continuous outcomes. Biometrics 42:121–130CrossRefGoogle Scholar
  54. Zorn CJW (2001) Generalized estimating equation models for correlated data: a review with applications. American Journal of Political Science 45(2):470–490CrossRefGoogle Scholar
  55. Zorn CJW (2006) Comparing GEE and robust standard errors for conditionally dependent data. Political Research Quarterly 59:329–341CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Curt Shepherd
    • 1
    Email author
  • Kristine Grimsrud
    • 1
  • Robert P. Berrens
    • 1
  1. 1.Department of EconomicsUniversity of New MexicoAlbuquerqueUSA

Personalised recommendations