Climate Aware Real Estate Pricing

This report describes the research related to use case 1 within pilot ♯6 of the FAME project: Embedding Climatic Predictions in Property Insurance Products. For a dataset with house value statistics over a high-resolution grid over California (USA), a hedonic regression model was fitted that explains the median house value over a grid cell through factors like population density, median income, and ocean proximity. Additional variability can be explained by a component in the regression model that quantifies the reduction in house value due to frequent episodes with extreme heat at this grid cell. Daily mean temperature simulations from several regional climate models are then statistically further downscaled to the resolution of the house price grid, and the projected increase in the number of days per year with excessive heat over the next decades is studied. When combining this information with the fitted regression model, the associated projected decrease of house values can be calculated.