This paper concerns the estimation of granular property price indices incommercial real estate and residential markets. We specify and apply a repeat salesmodel with multiple stochastic log price trends having a hierarchical additive structure: One common log price trend and cluster specific log price trends in deviation from the common trend.

Moreover, we assume that the error terms potentially have a heavy tailed (t) distribution to effectively deal with outliers. We apply the hierarchical repeat sales model on commercial properties in the Philadelphia/Baltimore region and on residential properties in a small part of Amsterdam.

The results show that the hierarchical repeat sales model provides reliable indices on a very detailed level based on a small number of observations.

The estimated degrees of freedom for thet-distribution is small, largely rejecting the commonly made assumption of normality of the error term...

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