This paper outlines the production of monthly house price indices (HPIs) for New Zealand produced using data from the Real Estate Institute of New Zealand (REINZ) using three alternative methodologies.
The database provided by REINZ is a rich unit-record sales dataset with information on price, location, valuation, and property characteristics (such as the number of bedrooms and the floor area). We use this data to produce HPIs based on three well-established and widely adopted methodologies: 1) sales-price to appraisal ratio (SPAR); 2) hedonic regression; and 3) repeat sales.
All three methods are found to produce credible-looking indices, which match the turning points and well-established cyclical properties of New Zealand’s existing house price statistics.
As a benchmarking exercise, the three candidate indices are evaluated alongside a simple median and a stratified median index. Applying a range of criteria to assess index performance, we find that all three alternative candidate methodologies out-perform the simple median and the stratified median methodologies, with the SPAR method performing best.