Working Paper: NBER ID: w31361
Authors: Jeffrey G. Shrader; Laura Bakkensen; Derek Lemoine
Abstract: We provide the first revealed preference estimates of the benefits of routine weather forecasts. The benefits come from how people use advance information to reduce mortality from heat and cold. Theoretically, more accurate forecasts reduce mortality if and only if mortality risk is convex in forecast errors. We test for such convexity using data on the universe of mortality events and weather forecasts for a twelve-year period in the U.S. Results show that erroneously mild forecasts increase mortality whereas erroneously extreme forecasts do not reduce mortality. Making forecasts 50% more accurate would save 2,200 lives per year. The public would be willing to pay $112 billion to make forecasts 50% more accurate over the remainder of the century, of which $22 billion reflects how forecasts facilitate adaptation to climate change.
Keywords: weather forecasts; mortality; public health; climate change; economic value
JEL Codes: D83; I12; Q51
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| more accurate weather forecasts (C53) | reduced mortality (I14) |
| erroneous mild forecasts (C53) | increased mortality (I12) |
| erroneous extreme forecasts (C53) | null impact on mortality (I12) |
| making forecasts 50% more accurate (C53) | saving approximately 2,200 lives annually (J17) |
| improved forecasts due to climate change (Q47) | increased benefit leading to saving 2,400 lives annually by 2100 (J17) |
| net value of improving forecast accuracy (C53) | around $21 billion per year (H56) |
| net value of improving forecast accuracy by 2100 (C53) | $29 billion (L99) |