ECONOMICALLY OPTIMAL WILDFIRE INTERVENTION REGIMES

Wildfires in the United States result in total damages and costs that are likely to exceed billions of dollars annually. Land managers and policy makers propose higher rates of prescribed burning and other kinds of vegetation management to reduce amounts of wildfire and the risks of catastrophic losses. A wildfire public welfare maximization function, using a wildfire production function estimated using a time series model of a panel of Florida counties, is employed to simulate the publicly optimal level of prescribed burning in an example county in Florida (Volusia). Evaluation of the production function reveals that prescribed fire is not associated with reduced catastrophic wildfire risks in Volusia County Florida, indicating a short-run elasticity of -0.16 and a long-run elasticity of wildfire with respect to prescribed fire of -0.07. Stochastic dominance is used to evaluate the optimal amount of prescribed fire most likely to maximize a measure of public welfare. Results of that analysis reveal that the optimal amount of annual prescribed fire is about 3 percent (9,000 acres/year) of the total forest area, which is very close to the actual average amount of prescribed burning (12,700 acres/year) between 1994-99.Resource /Energy Economics and Policy,

Meta-analysis of nature conservation values in Asia & Oceania: Data heterogeneity and benefit transfer issues

We conduct a meta-analysis (MA) of around 100 studies valuing nature conservation in Asia and Oceania. Dividing our dataset into two levels of heterogeneity in terms of good characteristics (endangered species vs. nature conservation more generally) and valuation methods, we show that the degree of regularity and conformity with theory and empirical expectations is higher for the more homogenous dataset of contingent valuation of endangered species. For example, we find that willingness to pay (WTP) for preservation of mammals tends to be higher than other species and that WTP for species preservation increases with income. Increasing the degree of heterogeneity in the valuation data, however, preserves much of the regularity, and the explanatory power of some of our models is in the range of other MA studies of goods typically assumed to be more homogenous (such as water quality). Subjecting our best MA models to a simple test forecasting values for out-of-sample observations, shows median (mean) forecasting errors of 24 (46) percent for endangered species and 46 (89) percent for nature conservation more generally, approaching levels that may be acceptable in benefit transfer for policy use. We recommend that the most prudent MA practice is to control for heterogeneity in regressions and sensitivity analysis, rather than to limit datasets by non-transparent criteria to a level of heterogeneity deemed acceptable to the individual analyst. However, the trade-off will always be present and the issue of acceptable level of heterogeneity in MA is far from settle

mitigation programs using propensity scores

Abstract 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

Wildfire Risk and Housing Prices: A Case Study from Colorado Springs

ABSTRACT. In 2000, concerned about the risks of wildfires to local homes, the Colorado Springs Fire Department rated the wildfire risk of 35,000 housing parcels within the wildland-urban interface and made its findings available online. We examine the effectiveness of this rating project by comparing the relationship between home price and wildfire risk before and after the information was posted on the Web site. Before the information was available, home price and wildfire risk were positively corre-lated, whereas, afterwards, they were not. (JEL R26, Q51) I

Part 1633 on bed fire outcomes

Beds are a prevalent combustible in fatal fires in the United States effective 1 July 2007, the US Consumer Product Safety Commission promulgated a standard to severely reduce the heat release rate and the early heat output from mattresses and foundations when ignited by a flaming ignition source. This study estimates the Standard’s success over its first decade using fire incidence, US population, and mattress sales data. The technique mitigates the influence of some exogenous factors that might have changed during this decade. The Standard is accomplishing its purpose, preventing approximately 65 fatalities (out of an estimated 95 fatalities in 2002–2005) from bed fires annually during 2015–2016, although not all pre-Standard mattresses had yet been replaced. Compared to residential upholstered furniture fires, which were not affected by the Standard, the numbers of bed fires decreased by 12%, injuries by 34%, and deaths by 82% between 2005–2006 and 2015–2016. Per bed fire, injuries decreased by 25% and fatalities decreased by 67%, indicating that the severity of bed fires is being reduced

ECONOMICALLY OPTIMAL WILDFIRE INTERVENTION REGIMES

Wildfires in the United States result in total damages and costs that are likely to exceed billions of dollars annually. Land managers and policy makers propose higher rates of prescribed burning and other kinds of vegetation management to reduce amounts of wildfire and the risks of catastrophic losses. A wildfire public welfare maximization function, using a wildfire production function estimated using a time series model of a panel of Florida counties, is employed to simulate the publicly optimal level of prescribed burning in an example county in Florida (Volusia). Evaluation of the production function reveals that prescribed fire is not associated with reduced catastrophic wildfire risks in Volusia County Florida, indicating a short-run elasticity of -0.16 and a long-run elasticity of wildfire with respect to prescribed fire of -0.07. Stochastic dominance is used to evaluate the optimal amount of prescribed fire most likely to maximize a measure of public welfare. Results of that analysis reveal that the optimal amount of annual prescribed fire is about 3 percent (9,000 acres/year) of the total forest area, which is very close to the actual average amount of prescribed burning (12,700 acres/year) between 1994-99