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- W4213302866 abstract "Throughout the winter months across the globe, mountain communities and snow-enthusiasts alike anxiously monitor ever-changing snowpack conditions. We model the behavioral response to this climate amenity by pairing a unique panel of 12 million short-term property rental transactions with daily local weather, daily local snowpack, and daily local snowfall in every major ski resort market across the United States. Matching the spatial and temporal variation in the level of the amenity with that of related market transactions, we derive market-specific demand elasticities, explicitly accounting for substitution, to model recreation patterns throughout a typical season. Lastly, we combine downscaled projections of local snowpack under future climate scenarios to estimate within and across season trends in visitation during mid and late-century conditions. Our model predicts reductions in snow-related visitation of –40% to –60%, almost twice as large as previous estimates suggest. This translates to a lower-bound on the annual willingness to pay to avoid reductions in snowpack between $1.23 billion (RCP4.5) and $2.05 billion (RCP8.5) by the end of the century." @default.
- W4213302866 created "2022-02-24" @default.
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- W4213302866 date "2022-05-01" @default.
- W4213302866 modified "2023-10-01" @default.
- W4213302866 title "A market for snow: Modeling winter recreation patterns under current and future climate" @default.
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- W4213302866 doi "https://doi.org/10.1016/j.jeem.2022.102637" @default.
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