Striving for Improvement: The Perceived Value of Improving Hurricane Forecast Accuracy

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  • 1 University of Miami, Rosenstiel School of Marine and Atmospheric Science, Department of Environmental Science and Policy, Miami, FL & University of Miami, Herbert Business School, Department of Economics, Coral Gables, FL
  • 2 University of Miami, Rosenstiel School of Marine and Atmospheric Science, Department of Environmental Science and Policy, Miami, FL
  • 3 University of Miami, Rosenstiel School of Marine and Atmospheric Science, Department of Atmospheric Science, Miami, FL
  • 4 Florida International University, Department of Earth and Environment, Miami, FL & Florida International University, Department of Economics, Miami, FL
  • 5 University of Miami, Rosenstiel School of Marine and Atmospheric Science, Department of Environmental Science and Policy, Miami, FL
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Abstract

Hurricanes are the costliest type of natural disaster in the United States. Every year, these natural phenomena destroy billions of dollars in physical capital, displace thousands, and greatly disrupt local economies. While this damage will never be eliminated, the number of fatalities and the cost of preparing and evacuating can be reduced through improved forecasts. This paper seeks to establish the public’s willingness to pay for further improvement of hurricane forecasts by integrating atmospheric modeling and a double-bounded dichotomous choice method in a large-scale contingent valuation experiment. Using an interactive survey, we focus on areas affected by hurricanes in 2018 to elicit residents’ willingness to pay for improvements along storm track, wind speed and precipitation forecasts. Our results indicate improvements in wind speed forecast are valued the most, followed by storm track and precipitation, and that maintaining a rate of improvement of 5% error reduction for another decade is worth between US$90.25 to US$121.86 per person in vulnerable areas. Our study focuses on areas recently hit by hurricanes in the United States, but the implications of our results can be extended to areas vulnerable to tropical cyclones globally. In a world where the intensity of hurricanes is expected to increase and research funds are limited, these results can inform relevant agencies regarding the effectiveness of different private and public adaptive actions, as well as the value of publicly funded hurricane research programs.

Corresponding author: Renato Molina, renato.molina@rsmas.miami.edu

Abstract

Hurricanes are the costliest type of natural disaster in the United States. Every year, these natural phenomena destroy billions of dollars in physical capital, displace thousands, and greatly disrupt local economies. While this damage will never be eliminated, the number of fatalities and the cost of preparing and evacuating can be reduced through improved forecasts. This paper seeks to establish the public’s willingness to pay for further improvement of hurricane forecasts by integrating atmospheric modeling and a double-bounded dichotomous choice method in a large-scale contingent valuation experiment. Using an interactive survey, we focus on areas affected by hurricanes in 2018 to elicit residents’ willingness to pay for improvements along storm track, wind speed and precipitation forecasts. Our results indicate improvements in wind speed forecast are valued the most, followed by storm track and precipitation, and that maintaining a rate of improvement of 5% error reduction for another decade is worth between US$90.25 to US$121.86 per person in vulnerable areas. Our study focuses on areas recently hit by hurricanes in the United States, but the implications of our results can be extended to areas vulnerable to tropical cyclones globally. In a world where the intensity of hurricanes is expected to increase and research funds are limited, these results can inform relevant agencies regarding the effectiveness of different private and public adaptive actions, as well as the value of publicly funded hurricane research programs.

Corresponding author: Renato Molina, renato.molina@rsmas.miami.edu
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