Measuring Housing Price Growth – Using Stratification to Improve Median-based Measures
Developments in housing prices are of interest to households, policy-makers and those involved in the housing industry. This has been the case both in Australia and in other countries where house price developments are having significant macroeconomic impacts. However, the construction of measures of city-wide or nationwide average housing prices is not a straightforward exercise. One problem is that the sample of dwellings transacted in any period may be far from random and the characteristics of the sample may change from period to period. As a result, widely used measures of growth in mean or median housing prices will reflect changes in the composition of dwellings sold as well as changes in demand and supply conditions. We demonstrate that median price measures in most major Australian capitals are significantly affected by such compositional change. In this paper, we propose a simple measure of house price growth that addresses the problem of compositional change by stratifying individual transactions into different groups. Our measure differs from those commonly used internationally in that we group small geographic regions (suburbs) according to the long-term average price level of dwellings in those regions, rather than just clustering smaller geographic regions into larger geographic regions. This produces a measure of price growth that substantially improves upon median price measures, and one that is highly correlated with more sophisticated (but more computationally intensive) measures. While we focus on providing a basic framework for measuring house price growth, the stratification techniques contained in this paper have broader applications for dealing with datasets that are affected by compositional change.
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