The Social Value of Predicting Hurricanes - Renato Molina; Ivan Rudik (Center for Economic Studies and ifo Institute (CESifo), 2022)
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 social value of forecast improvements. We find that pre-landfall federal protective expenditures exponentially increase with the forecast wind speed and with the degree of uncertainty about the forecast. Correspondingly, we find that forecast errors are costly: underestimating wind speed results in damages and post-landfall recovery spending up to an order of magnitude larger than if the forecast had been accurate. Our main contribution is to develop a new theoretically-grounded approach for estimating the marginal value of information and we apply it to establish the social value of improving hurricane forecasts. On the margin, the value of hurricane information is large and has increasing returns. We find that forecast improvements since 2009 reduced total costs associated with hurricanes by 5%, totalling hundreds of millions of dollars per hurricane. When aggregated, these benefits are over an order of magnitude greater than the cumulative budget for operating and improving the hurricane forecast system.
Keywords: Q54; Q58; C53; 330; natural disasters; hurricanes; tropical cyclones; forecasts; information; climate change