I analyze damage from hurricane strikes on the United States since 1955. Using machine learning methods to select the most important drivers for damage, I show that large errors in a hurricane's predicted landfall location result in higher damage. This relationship holds across a wide range of...

Hurricanes are among the costliest natural disasters in the world, with a significant portion of their impact linked to the accuracy of their forecasts. In this paper, we estimate the economic impacts of the official hurricane forecasts in the US and develop a new approach for measuring the...

We investigate the uncertainty dynamics surrounding extreme weather events through the lens of option and stock markets by identifying market responses to the uncertainty regarding both potential hurricane landfall and subsequent economic impact. Stock options on firms with establishments...