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Premiums or Peril
Using fine-grained data on 465,000 Florida home sales over twelve years and semiparametric machine learning methods, we examine how home prices respond to weather-related risk factors. After controlling for geography, home characteristics, and transaction features, we find that home prices are negatively related to property-level expected weather losses derived from catastrophe models, insurance premiums, and exposure to recent hurricanes, but with notably different magnitudes. Expected weather losses show the strongest association with prices and are consistent with markets rationally ...