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Forecast Accuracy Matters for Hurricane Damage

Author

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  • Andrew B. Martinez

    (Office of Macroeconomic Analysis, US Department of the Treasury, Washington, DC 20220, USA
    Research Program on Forecasting, The George Washington University, Washington, DC 20052, USA
    Climate Econometrics, Nuffield College, Oxford OX1 1NF, UK)

Abstract
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 model specifications and when controlling for ex-ante uncertainty and potential endogeneity. Using a counterfactual exercise I find that the cumulative reduction in damage from forecast improvements since 1970 is about $82 billion, which exceeds the U.S. government’s spending on the forecasts and private willingness to pay for them.

Suggested Citation

  • Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damage," Econometrics, MDPI, vol. 8(2), pages 1-24, May.
    • Handle: RePEc:gam:jecnmx:v:8:y:2020:i:2:p:18-:d:357835
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    2. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    3. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
    4. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
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    6. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
    7. Song, Yuqi, 2024. "The value of weather forecasts: Evidence from labor responses to accurate versus inaccurate temperature forecasts in China," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    8. Renato Molina & Ivan Rudik, 2022. "The Social Value of Predicting Hurricanes," CESifo Working Paper Series 10049, CESifo.

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    More about this item

    Keywords

    adaptation; model selection; natural disasters; uncertainty;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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