In this paper we consider how choices in the econometric approach to impute prices affect the Törnqvist and Jevons hedonic imputed indexes. We compare the rolling window approach to estimation by smoothing methods. The main difference between the rolling window and the smoothing methods is in the way information is weighted. We propose that the Kalman filter smoother is the most appropriate estimator for the task as it optimally weights current and past information. We show the rolling window approach does not produce estimates that are attenuated over time leading to chain drift in the index. We also compare two alternative specifications to model property location. The empirical section uses data from a small and homogeneous market in the state of Queensland, Australia. The Törnqvist and Jevons indexes differ in value during periods of market volatility. This seems expected given their different weighting of transactions and the likelihood that price movements of properties at the upper and lower end of the price distribution might differ during periods of market volatility.