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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. [ABSTRACT FROM AUTHOR]

Abstract: Applying the rational expectations hypothesis, this essay models the current value of a house as the conditional expectation of the discounted stream of housing services accruing to the owner of the house. The value of housing services is determined by neighborhood effects as well as the physical attributes of the property itself. In the existing hedonic literature, future transactions have not been utilized to describe neighborhood effects. The rational expectations asset pricing model in this study accounts for expected future neighborhood effects as well as observed current neighborhood effects. The reduced form of the rational expectations model is a spatial autoregressive (SAR) model with two spatial lags. After employing the generalized method of moments (GMM) in estimating the spatial asset pricing model, I find that both expected future transactions and prior transactions in the neighborhood are significant. The inclusion of expected future transaction prices in the neighborhood takes into account the influence of expected changes in the community and factors these potential changes into the current house price. This is consistent with forward-looking households. The forward-looking model generates superior out-of-sample prediction performance relative to both the conventional hedonic model without considering neighborhood effects or the standard spatial hedonic model including only past transactions. [Copyright &y& Elsevier]