Econometric analysis of fire suppression production functions for large wildland fires
Thomas P. Holmes A C and David E. Calkin B
+ Author Affiliations
- Author Affiliations
A USDA Forest Service, Southern Research Station, PO Box 12254, Research Triangle Park, NC 27709, USA.
B USDA Forest Service, Rocky Mountain Research Station, Federal Building, 200 East Broadway, Missoula, MT 59807, USA.
C Corresponding author. Email: tholmes@fs.fed.us
International Journal of Wildland Fire 22(2) 246-255 https://doi.org/10.1071/WF11098
Submitted: 14 July 2011 Accepted: 16 July 2012 Published: 18 September 2012
Abstract
In this paper, we use operational data collected for large wildland fires to estimate the parameters of economic production functions that relate the rate of fireline construction with the level of fire suppression inputs (handcrews, dozers, engines and helicopters). These parameter estimates are then used to evaluate whether the productivity of fire suppression inputs during extensive fire suppression efforts are similar to productivity estimates derived from direct observation and used as standard rates by the US Forest Service. The results indicated that the production rates estimated with operational data ranged from ~14 to 93% of the standard rates. Further, the econometric models indicated that the productivity of all inputs taken together increases more than proportionally as their use is increased. This result may indicate economies of scale in fire suppression or, alternatively, that fire managers learn how resources may be deployed more productively over the course of a fire. We suspect that the identified productivity gaps are primarily due to unobserved factors related to fire behaviour, other resources at risk, firefighter fatigue, safety considerations and managerial decision-making. The collection of more precise operational data could help reduce uncertainty regarding the relative importance of factors that contribute to productivity shortfalls.
Additional keywords: efficiency, fireline productivity, fractal dimension, random parameters, returns to scale, selective rationality.
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