Estimation of Forest Fire-fighting Budgets Using Climate Indexes

Zhen Xu and Gerrit van Kooten

No 127967, Working Papers from University of Victoria, Resource Economics and Policy

Abstract: Given the complexity and relative short length of current predicting system for fire behavior, it is inappropriate to be referred for planning fire-fighting budgets of BC government due to the severe uncertainty of fire behavior across fire seasons. Therefore, a simple weather derived index for predicting fire frequency and burned area is developed in this paper to investigate the potential feasibility to predict fire behavior and fire-fighting expenses for the upcoming fire season using climate indexes. Linear regression models with spatial dummy variables are employed to estimate necessary coefficients that describe relationships across climate events, regional weather conditions, fire behavior and direct fire-fighting expenses in the interior of British Columbia; and Monte Carlo simulation are then used to predict future situations. We conclude that the BC government can use the last-year average solely, or together with January through April climate indexes for planning wildfire budgets for the upcoming fire season.

Keywords: Environmental; Economics; and; Policy (search for similar items in EconPapers)
Pages: 50
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/127967/files/WorkingPaper2012-03.pdf (application/pdf)

Related works:
Working Paper: Estimation of Forest Fire-fighting Budgets Using Climate Indexes (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:uvicwp:127967

DOI: 10.22004/ag.econ.127967

Access Statistics for this paper

More papers in Working Papers from University of Victoria, Resource Economics and Policy
Bibliographic data for series maintained by AgEcon Search ().