Measuring House Price Movements

1. Measuring House Price Movements Methods, Issues and Some Recent Experience in the Australian Context

2. Background • Historically used in CPI for mortgage interest charges • Removed from CPI in 1998 • Continued to publish HPI because of user interest

3. Background • Surge in house prices to late 2003 led to criticism • Housing ... is an extremely important asset class for most people, yet the information we have on prices is hopeless compared with the information we have on share prices, bond prices, ... and consumer prices. It really is probably the weakest link in all the price data in the country so I think it is something that I wouldlike to see resources put into. - Ian MacFarlane, former Governor, RBA.

4. Conceptual and Practical Issues • Heterogeneity • Infrequent turnover • Compositional change • Quality change (not currently adjusted for) • Timeliness of data • approximately 6 months lag • blend VGs and mortgage lenders' data

5. Time lag with exchange data

6. Methods for Constructing House Price Indexes • Hedonics • products as 'bundles‘ of characteristics • dependent on data availability of price determining characteristics • Repeat sales • comparing like with like • assumes constant quality over time

7. Methods for Constructing House Price Indexes (continued) • Stratification • grouping 'similar' suburbs into clusters • SEIFA • structural information • locational information • Trade off between homogeneity and number of observations

8. ABS Past Experience • 1986 - 2002 predominantly a 'settlements' basis • Some geographical stratification • 'Trimean' method (Sydney, Melbourne, Brisbane, Adelaide) • Unweighted average prices (Perth, Hobart, Darwin, Canberra) • Limited solution for controlling compositional change

9. Hedonic Methods Investigations • Undertaken in 2003 • Hobart and Adelaide only, due to restricted data availability

10. Hedonic Methods Investigations (continued) • Based on data such as; • structural attributes for individual houses (land size, wall construction, number of bathrooms) • locational attributes (distance to CBD, nearest school, hospital) • neighbourhood attributes (SEIFA, which includes income, crime rate, etc). • Data limitations prevented firm conclusions

11. Current Approach • Stratification • By suburb, based on broadly available variables from Census • Structural (bedrooms, owner occupied status, % of dwellings that are houses) • Locational (distance to CBD, shops, hospital) • Neighbourhood (SEIFA) • Geographically bounded by Statistical Subdivision (SSD)

12. New Developments • Reserve Bank of Australia • Price based stratification • Considerable improvement on simple median approach • Compared favourably to more advanced hedonic measures

13. New Developments (continued) • Issues with current ABS methodology • number of observations per cluster problematic • SSD boundaries too restrictive • price ranges within strata too broad

15. New Developments (continued) • Test the following • removal of SSD restriction • inclusion of price as an indicator of homogeneity • For the future • improve timeliness (meet RBA timetable) • include units, apartments & townhouses • include regional areas

16. Thank You