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- Author or Editor: Donald M. Waldman x
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To estimate the economic effects of weather variability in the United States, the authors define and measure weather sensitivity as the variability in economic output that is attributable to weather variability, accounting for changes in technology and changes in levels of economic inputs (i.e., capital, labor, and energy). Using 24 yr of economic data and weather observations, quantitative models of the relationship between state-level sectoral economic output and weather variability are developed for the 11 nongovernmental sectors of the U.S. economy; temperature and precipitation measures were used as proxies for all weather impacts. All 11 sectors are found to have statistically significant sensitivity to weather variability. Economic inputs were then constant and economic output was estimated in the 11 estimated sector models, varying the weather inputs only using 70 yr of historic weather observations. It was found that U.S. economic output varies by up to $485 billion yr−1 of 2008 gross domestic product, about 3.4%, owing to weather variability. U.S. states that are more sensitive to weather variability are identified and sectors are ranked by their degree of weather sensitivity. This work illustrates a valid approach to measuring the economic impact of weather variability, gives baseline information and methods for more detailed studies of the sensitivity of each sector to weather variability, and lays the groundwork for assessing the value of current or improved weather forecast information given the economic impacts of weather variability.
To estimate the economic effects of weather variability in the United States, the authors define and measure weather sensitivity as the variability in economic output that is attributable to weather variability, accounting for changes in technology and changes in levels of economic inputs (i.e., capital, labor, and energy). Using 24 yr of economic data and weather observations, quantitative models of the relationship between state-level sectoral economic output and weather variability are developed for the 11 nongovernmental sectors of the U.S. economy; temperature and precipitation measures were used as proxies for all weather impacts. All 11 sectors are found to have statistically significant sensitivity to weather variability. Economic inputs were then constant and economic output was estimated in the 11 estimated sector models, varying the weather inputs only using 70 yr of historic weather observations. It was found that U.S. economic output varies by up to $485 billion yr−1 of 2008 gross domestic product, about 3.4%, owing to weather variability. U.S. states that are more sensitive to weather variability are identified and sectors are ranked by their degree of weather sensitivity. This work illustrates a valid approach to measuring the economic impact of weather variability, gives baseline information and methods for more detailed studies of the sensitivity of each sector to weather variability, and lays the groundwork for assessing the value of current or improved weather forecast information given the economic impacts of weather variability.
Abstract
Hurricane warnings are the primary sources of information that enable the public to assess the risk and develop responses to threats from hurricanes. These warnings have significantly reduced the number of hurricane-related fatalities in the last several decades. Further investment in the science and implementation of the warning system is a primary mission of the National Weather Service and its partners. It is important that the weather community understand the public’s preferences and values for such investments; yet, there is little empirical information on the use of forecasts in evacuation decision making, the economic value of current forecasts, or the potential use or value for improvements in hurricane forecasts. Such information is needed to evaluate whether improved forecast provision and dissemination offer more benefit to society than alternative public investments.
Fundamental aspects of households’ perceptions of hurricane forecasts and warnings and their potential uses of and values for improved hurricane forecast information are examined. The study was designed in part to examine the viability of survey research methods for exploring evacuation decision making and for eliciting values for improved hurricane forecasts and warnings. First, aspects that affect households’ stated likelihood of evacuation are explored, because informing such decisions is one of the primary purposes of hurricane forecasts and warnings. Then, stated-choice valuation methods are used to analyze choices between potential forecast-improvement programs and the accuracy of existing forecasts. From this, the willingness to pay (WTP) for improved forecasts is derived from survey respondents.
Abstract
Hurricane warnings are the primary sources of information that enable the public to assess the risk and develop responses to threats from hurricanes. These warnings have significantly reduced the number of hurricane-related fatalities in the last several decades. Further investment in the science and implementation of the warning system is a primary mission of the National Weather Service and its partners. It is important that the weather community understand the public’s preferences and values for such investments; yet, there is little empirical information on the use of forecasts in evacuation decision making, the economic value of current forecasts, or the potential use or value for improvements in hurricane forecasts. Such information is needed to evaluate whether improved forecast provision and dissemination offer more benefit to society than alternative public investments.
Fundamental aspects of households’ perceptions of hurricane forecasts and warnings and their potential uses of and values for improved hurricane forecast information are examined. The study was designed in part to examine the viability of survey research methods for exploring evacuation decision making and for eliciting values for improved hurricane forecasts and warnings. First, aspects that affect households’ stated likelihood of evacuation are explored, because informing such decisions is one of the primary purposes of hurricane forecasts and warnings. Then, stated-choice valuation methods are used to analyze choices between potential forecast-improvement programs and the accuracy of existing forecasts. From this, the willingness to pay (WTP) for improved forecasts is derived from survey respondents.
