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α: calibrated so average coauthorship-adjusted count equals average raw count
The widely used repeat sales method for constructing house price indexes only uses data for properties that sell twice or more. This makes it susceptible to selection bias as price movements for these properties may not be representative of those for the stock of homes. We outline a novel approach to modelling repeat sales, which allows for a home's characteristics to influence its price movement. This allows us to impute price changes for the stock of homes and control for selection‐on‐observables. Using data for Florida from 2002 to 2020 we find that selection effects significantly exaggerated the volatility of Florida's housing prices.