Climate Change and Housing Prices: Hedonic Estimates for North American Ski Resorts
Bibliographic record
Abstract
We use a hedonic framework to estimate and simulate the impact of global warming on real estate prices at North American ski resorts. To do so, we combine data on resort-area housing values from two sources--data on average values for U.S. Census tracts across a broad swath of the western U.S. and data on individual home sales for four markets in the western U.S. and Canada, each available over multiple decades--with detailed weather data and characteristics of ski resorts in those areas. Our OLS and fixed-effects models of changes in home values with respect to medium-run changes in the share of snowfall in winter precipitation yield precise and consistent estimates of positive snowfall effects on housing values in both data sources. We use our estimates to simulate the impact of likely climate shifts on home values in coming decades and find substantial variation across resort areas based on climatic characteristics such as longitude, elevation, and proximity to the Pacific Ocean. Resorts that are unfavorably located face likely large negative effects on home prices due to warming, unless adaptive measures are able to compensate for the deterioration of conditions in the ski industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".