Measurement error in residential property valuation: An application of forecast combination

In this study we use a large database of real estate transactions to assess the magnitude of measurement error associated with using popular house price indices (HPIs) to value individual properties. In the 4 large U.S. counties that we analyze, we find that the bias associated with using these HPIs to value individual homes increased from near zero in 2005 to between 26% and 113% in 2010. In the second part of the analysis, we use data from Florida to demonstrate that forecast combination methods can be used to improve the accuracy of property-level valuations, in some cases reducing the estimated bias by more than a factor of 3. We find that even the simplest forecast combination method - a simple average - has the potential to significantly improve value estimates.