Weather-based estimation of wildfire risk
AbstractCatastrophic wildfires in California have become more frequent in past decades, while insured losses per event have been rising substantially. On average, California ranks the highest among states in the U.S. in the number of fires as well as the number of acres burned each year. The study of catastrophic wildfire models plays an important role in the prevention and mitigation of such disasters. Accurate forecasts of potential large fires assist fire managers in preparing resources and strategic planning for fire suppression. Furthermore, fire forecasting can a priori inform insurers on potential financial losses due to large fires. This paper describes a probabilistic model for predicting wildland fire risks using the two-stage Heckman procedure. Using 37 years of spatial and temporal information on weather and fire records in Southern California, this model measures the probability of a fire occurring and estimates the expected size of the fire on a given day and location, offering a technique to predict and forecast wildfire occurrences based on weather information that is readily available at low cost.
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Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2009-032.
Length: 26 pages
Date of creation: Jun 2009
Date of revision:
biased sampling; forest fires; fire occurrence probabilities; fire weather;
Find related papers by JEL classification:
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
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- Haerdle, Wolfgang & Cabrera, Brenda Lopez, 2007.
"Calibrating CAT bonds for Mexican earthquakes,"
101st Seminar, July 5-6, 2007, Berlin Germany
9265, European Association of Agricultural Economists.
- Heckman, James, 2013.
"Sample selection bias as a specification error,"
Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
- Michał Grajek & Lars-Hendrik Röller, 2009.
"Regulation and Investment in Network Industries: Evidence from European Telecoms,"
SFB 649 Discussion Papers
SFB649DP2009-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Michał Grajek & Lars-Hendrik R�ller, 2012. "Regulation and Investment in Network Industries: Evidence from European Telecoms," Journal of Law and Economics, University of Chicago Press, vol. 55(1), pages 189 - 216.
- Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
- Roland Strausz, 2010.
"The Political Economy of Regulatory Risk,"
CESifo Working Paper Series
2953, CESifo Group Munich.
- Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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