Published 16 June 2006
Analysis of suburb-level house sales in Sydney & Melbourne indicates that around 60% of the quarterly variation in median price changes can be attributed solely to changes in the mix of sales between higher- & lower-priced suburbs, rather than to price changes reflecting demand & supply conditions, Reserve Bank of Australia researchers have found.
The research was a follow-up to a 2004 discussion paper and was presented in a full document recently. This week James Hansen, Nalini Prasad & Anthony Richards of the bank’s economic group presented their results in summary form.
The analysis drew on detailed transaction-level data provided by Australian Property Monitors for Sydney & Melbourne and the Real Estate Institute of Victoria for Melbourne.
The researchers said that in addition to compositional change, changes in the average quality of housing over time can be important: “If the quality of the housing stock tends to rise â€“ for example, through renovations of the existing stock and the addition of higher-quality newly constructed houses â€“ then the growth in a simple mean or median will tend to overstate the pure price change in housing.
“Such effects may be important for questions such as the longer-term performance of housing as an asset class, but they are unlikely to play a significant role in short-term movements in house prices.”
They said it was important, in light of the relevance of housing prices for macroeconomic developments, to be able to assess movements in aggregate housing prices both accurately and on a timely basis.
“However, the experience in Australia & in some other countries has been that measurement problems make it difficult to assess developments accurately with the available real-time data. The major problem in Australia has been with respect to compositional change, and the difficulties involved in inferring the price change for the overall housing stock from sales prices for the small fraction of dwellings that is transacted in any period. The compositional change problem is exacerbated by the poor timeliness of data, given the existence of a lag between when a sale is agreed and when it subsequently enters into a database of transactions.”
The researchers said a number of feasible techniques appeared to provide good measures of price changes â€“ mix-adjustment, hedonic and repeat-sales methods.
Why are house prices difficult to measure?
“House prices can be difficult to measure for a number of reasons, some methodological and some practical. These problems are most pronounced when using median price measures. Medians (or means) are commonly used measures internationally because they are easy to calculate and have a straightforward interpretation, representing the price in a â€˜typical’ transaction.
To be meaningful, measures of housing prices should be based on prices in actual transactions rather than on perceptions of valuations. However, only a relatively small fraction of the total housing stock is transacted in any particular period: in Australia, around 1Â½% of the housing stock is transacted each quarter and the average turnover is significantly lower in some other countries.
“Furthermore, the quality & composition of the small proportion of houses that are transacted may be quite different to the much larger stock of dwellings that are not transacted and for which prices cannot be observed. As a result, changes in the mix of properties sold over time can influence measures such as those based on median prices.
“For example, even when there are no changes in the value of any houses within a city in a particular period, if the proportion of sales that occur in more expensive suburbs increases, the measured citywide median price will increase. This type of compositional change can introduce significant noise into measures of aggregate house prices, particularly in the short term. For example, analysis of suburb-level transactions in Sydney and Melbourne indicates that around 60% of the quarterly variation in median price changes can be attributed solely to changes in the mix of sales between higher- & lower-priced suburbs, rather than to price changes reflecting demand & supply conditions.
“Analysis of housing transactions indicates that some of the compositional change in Australia is seasonal in nature, with more expensive houses tending to be sold at particular times of the year (typically the December quarter) and less expensive houses sold in other periods (the March quarter).
“This seasonality in the mix of dwellings contributes to seasonality in median house prices, with median prices being higher in those quarters when the proportion of more expensive houses sold increases and pushed lower when this proportion falls.
“Indeed, seasonal effects alone can explain around one-half (for Melbourne) & one-third (for Sydney) of the quarterly variation in median house prices. Analysis of price data for several other countries (the US, Canada & New Zealand) suggests that median price measures there are also subject to significant seasonality. This suggests that compositional change is a pervasive problem for median price measures.
“There are other practical issues involved in measuring prices accurately. In particular, unlike prices in other asset markets, price information for housing transactions is typically not available on a timely basis. In most countries there is a significant lag between the agreement on a price and the settlement of the transaction: in Australia, the settlement period is typically between 1-3 months (depending on local conventions). When combined with reporting lags, price information is sometimes not available until several months after the initial agreement on the price.
“A particular â€˜real-time’ problem may arise if there are systematic differences in reporting lags, so initial samples of housing transactions are unrepresentative of the full set of transactions. For example, if â€“ as appears to be the case in several Australian cities â€“ more expensive houses tend to take longer to settle, initial estimates of median prices will be biased downwards. Estimates of median prices will then be subsequently revised upwards as information on sales of more expensive houses becomes recorded in the transactions database.”
The research showed both mix-adjusted & regression-based measures were feasible for Australian cities and could substantially improve on a citywide median measure of house prices.
Attribution: Reserve Bank of Australia release, paper, story written by Bob Dey for this website.