Alternative way of looking at the housing market by using quartiles data over median house price data.

This week's article offers an alternative way of looking at the housing market by using quartiles data over median house price data. Quartile data is a measure used by data analysts that shows typical pricing at the lower priced and higher priced end of the market and is also a signal about how much diversity there is across housing stock within a region.

To explain: A median price is a commonly used measure of pricing in the housing market. It represents the ‘middle’ sale price in a list of transactions arranged in ascending (or descending) order. For example, if there were eleven house sales across a suburb, the median would be the sixth most expensive sale which means that there would be an equal number of more expensive and more affordable properties.

It is valuable to look at other measures such as quartiles from time-to-time as this methodology provides a reflection of the more affordable and more expensive segments of the housing market in a region. If a region had 21 sales over a period the lower quartile would be the 6th cheapest sale and the upper quartile would be the 6th most expensive sale.

The difference across the lower and upper quartiles provides us with more than just a view of range in prices; quartile measures also provide an indication of the diversity of housing stock in a region. A good example of this is the high profile suburb of Point Piper in Sydney which has significantly diverse housing stock due to its harbourside location. The lower quartile price is still hefty at $4,720,000 however, the upper quartile comes in at $30,000,000; more than six times the lower quartile price.

For this analysis we are highlighting the capital city suburbs with the least difference between the bottom and top quartile; or the least amount of diversity in housing stock.

For houses, Strathmore Heights in Melbourne has shown the smallest difference at just 5.6% based on sales over the past year. Across the unit market the suburb with the smallest differential between the lower and upper quartile was Albany Creek in Brisbane at just 1.3%.


Houses | Least diversified suburbs


Units | Least diversified suburbs


Of surprise is the fact that very few of the suburbs listed for either houses or units are relatively new development areas. In fact across both product types the areas can generally be classified as established suburbs with relatively few new homes over recent years. This would tend to indicate that at the time of development many of the homes built were fairly similar and since that time relatively little in the way of renovation may have taken place.

The results suggest that these suburbs have very little difference between precincts within the suburb. What this means is there are no areas particularly more or less desirable within these suburbs and this is reflected by the fact there is relatively little price variation throughout the suburb.

While using a median price as a measure is common across the property industry, by looking at quartiles it enables us to provide greater insights into the dynamics of a particular market. These insights simply aren’t available when medians are the focus.

The results also reiterate that the median represents the typical housing cost but above and below that figure there can be significant variation in quality and cost or there can be very little difference.


Article by Tim Lawless, CoreLogic RP Data head of research.

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In compiling this publication, CoreLogic has relied upon information supplied by a number of external sources and CoreLogic does not warrant its accuracy or completeness. To the full extent allowed by law CoreLogic excludes all liability for any loss or damage suffered by any person or body corporate arising from or in connection with the supply or use of any part of the information in this publication. CoreLogic recommends that individuals undertake their own research and seek independent financial advice before making any decisions. © 2014 CoreLogic.