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Abstract Climate change impacts threaten the stability of the US housing market. In response to growing concerns that increasing costs of flooding are not fully captured in property values, we quantify the magnitude of unpriced flood risk in the housing market by comparing the empirical and economically efficient prices for properties at risk. We find that residential properties exposed to flood risk are overvalued by US$121–US$237 billion, depending on the discount rate. In general, highly overvalued properties are concentrated in counties along the coast with no flood risk disclosure laws and where there is less concern about climate change. Low-income households are at greater risk of losing home equity from price deflation, and municipalities that are heavily reliant on property taxes for revenue are vulnerable to budgetary shortfalls. The consequences of these financial risks will depend on policy choices that influence who bears the costs of climate change. 

We discuss data quality and modeling issues inherent in the use of nationwide property data to value environmental amenities. By example of ZTRAX, a U.S.-wide real estate database, we identify challenges and propose guidance for: (1) the identification of arm’s-length sales, (2) the geo-location of parcels and buildings, (3) temporal linkages between transaction, assessor, and parcel data, (4) the identification of property types, such as single-family homes and vacant lands, and (5) dealing with missing or mismeasured data for standard housing attributes. We review current practice and show that how researchers address these issues can meaningfully influence research findings.