Count Models and Wildfire in British Columbia
Zhen Xu and
Gerrit van Kooten
No 2013-06, Working Papers from University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group
Two count models are estimated in this analysis to explain the occurrence of wildfire and area burned by wildfire in the interior of British Columbia, Canada. The main explanatory variable is the 4-month lagged El Niño 1&2 index, which is found to have a strong positive influence on wildfire in the study region. As a result of the lag on the climate index, the count models can be used to predict annual wildfire occurrence and the overall monthly size of the area burned by fire districts. An increase in the mean value of the monthly El Niño 1&2 index is projected to result in a slight increase in the number of fires and an increase in the probability that large areas will be burned. Not unexpectedly, however, the impact in July and August could be quite high (increases of 30%). In conclusion, given the large variance, actual changes caused by climate change are uncertain and could be dramatic.
Keywords: Wildfire occurrence and climate change; negative binomial and Pareto distributed count models; El Niño Southern Oscillation (search for similar items in EconPapers)
JEL-codes: Q23 Q26 Q51 Q54 R21 R32 (search for similar items in EconPapers)
Pages: 33 pages
New Economics Papers: this item is included in nep-agr and nep-env
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Working Paper: Count Models and Wildfire in British Columbia (2013)
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