Fighting fire with fire: estimating the efficacy of wildfire mitigation programs using propensity scores
Document Type: Journal Article
Author(s): David T. Butry
Publication Year: 2009

Cataloging Information

  • climatology
  • coniferous forests
  • elevation
  • enogeneity
  • ENSO - El Nino Southern Oscillation
  • fire intensity
  • fire management
  • fire suppression
  • forest management
  • fuel types
  • fuels management
  • humidity
  • ignition
  • population density
  • propensity score
  • range management
  • rangelands
  • rate of spread
  • sloping terrain
  • statistical analysis
  • suppression
  • treatment effects
  • wetlands
  • wildfire production functions
  • wildfires
  • wind
Record Maintained By:
Record Last Modified: June 1, 2018
FRAMES Record Number: 3646
Tall Timbers Record Number: 24069
TTRS Location Status: In-file
TTRS Call Number: Fire File
TTRS Abstract Status: Okay, Fair use, Reproduced by permission

This bibliographic record was either created or modified by the Tall Timbers Research Station and Land Conservancy and is provided without charge to promote research and education in Fire Ecology. The E.V. Komarek Fire Ecology Database is the intellectual property of the Tall Timbers Research Station and Land Conservancy.


This paper examines the effect wildfire mitigation has on broad-scale wildfire behavior. Each year, hundreds of million of dollars are spent on fire suppression and fuels management applications, yet little is known, quantitatively, of the returns to these programs in terms of their impact on wildfire extent and intensity. This is especially true when considering that wildfire management influences and reacts to several, often times confounding factors, including socioeconomic characteristics, values at risk, heterogeneous landscapes, and climate. Due to the endogenous nature of suppression effort and fuels management intensity and placement with wildfire behavior, traditional regression models may prove inadequate. Instead, I examine the applicability of propensity score matching (PSM) techniques in modeling wildfire. This research makes several significant contributions including: (1) applying techniques developed in labor economics and in epidemiology to evaluate the effects of natural resource policies on landscapes, rather than on individuals; (2) providing a better understanding of the relationship between wildfire mitigation strategies and their influence on broad-scale wildfire patterns; (3) quantifying the returns to suppression and fuels management on wildfire behavior.

Online Link(s):
Butry, David T. 2009. Fighting fire with fire: estimating the efficacy of wildfire mitigation programs using propensity scores. Environmental and Ecological Statistics 16(2):291-319.