We provide the first revealed-preference estimates of the benefits of routine weather forecasts. The benefits come from how people use the information to reduce mortality from heat or cold. We show that more accurate forecasts reduce mortality if and only if mortality risk is convex in forecast errors, which in turn depends on the actions people take in response to forecasts. Using data on the universe of mortality events and weather forecasts for a twelve-year period in the U.S., we show that making forecasts 50% more accurate would save 1,700 lives per year, for gross annual benefits of $16 billion. The effects of forecast errors indicate that adaptation becomes less effective if temperatures are either higher or lower than expected. Forecast-driven adaptation is especially important in extreme heat, which suggests that short-run weather forecasts could be an important tool for managing the effects of climate change.

 

About the speaker

Jeffrey Shrader is an Assistant Professor at Columbia University's School of International and Public Affairs (SIPA).

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He is an environmental and labor economist who uses theory and data to study how beliefs affect decision making, the role of information—especially professional forecasts—in shaping beliefs, and the effect of forward-looking behavior on empirical analyses. His work focuses on estimating damages from a changing climate, accounting for how individuals and groups anticipate and adapt to those changes.

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