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The Pitfalls of Median Price: How Typical Price Provides a More Accurate Picture

Have you ever wondered why the median price of a property market can sometimes be misleading?

In this article, we’ll delve into why this is the case and how the Typical Price can provide a more accurate representation.

Median Price is one of the most commonly reported property market metrics.

All major media outlets and data providers use it to highlight real estate price levels in capital city and regional markets.

Here is an example of capital city median prices for free standing houses plotted on a time series chart.

We can see that since the 2008 GFC house prices were rising until 2018 in the 2 hottest Australian markets of Sydney and Melbourne.

Then prices declined until September 2019, at which point the growth resumed.

Perth began declining in 2015, with other capital city markets showing moderate gains compared to MEL and SYD in this time-period.

In this article we will explore whether this metric is a reliable indicator to perform data-driven market research when assessing suburbs for investment opportunities.

Before we deep dive into data exploration, let’s first define Median Price.

Median Price: A Double-Edged Sword

Median Price is a widely used metric to describe the most common price of properties in a particular area. It’s calculated by sorting the sales by price and then taking the value in the middle of the list.

This approach helps to avoid the data skew problem in the Average Price formula due to outliers.

For example, if 10 properties sell in the 500,000$-600,000$ range and the 11th property sells for 3,000,000$ it will skew the Average Price towards the higher end property.

Whereas in reality majority of sales are on the lower end of the price spectrum.

Calculating Median Price

The formula gives us the typical value representation of the relevant capital city property market.

The capital city Median Price chart shows us a clear trend and values. There is no ambiguity as to how the prices evolved over time. It is also clear what their current values are.

We can conclude that at this level Median Price is the right metric to use when comparing capital city markets. However…

There are markets within markets, within markets, within markets…

Although a capital city price trend may be headed one way, the underlying suburb markets can have a different mix of rising and declining price levels and trends.

Therefore, it is important to always assess suburbs based on price and trend data produced specifically for that sub-market.

Not based on the median price associated with the broader area.

While the Median Price is a useful tool for comparing capital city markets, it has its limitations.

The Limitations of Median Price

The chart below plots 599 historical sales and calculated Median Price for 3-bedroom houses in the suburb of Trevallyn, Tasmania 7250.

Blue dots correspond to individual property sales.

The orange line is quarterly Median Price calculated off the back of these sales.

Suburb Median Price
Suburb quarterly price calculated via median value formula

Notice the sporadicity in Median Price values that fluctuate in the 50,000$ range quarter on quarter.

If you’re researching this market in 2021, the Median Price will be at 400,000$.

However, given the sporadic nature of price movement in the past, is 400,000$ a reliable value to go by?

If there aren’t enough property sales in a given period, the median price can swing dramatically from one period to the next.

These swings don’t necessarily reflect genuine changes in the property market’s overall trend.

Changes in median values can be more like static or background noise caused by the scarcity of data points and different types of properties transacted very month.

When compared to the capital city chart, the Trevally suburb chart bears a lot less information in that the price levels are ambiguous, and the trend is not easily detectable (although still visible).

Now that we’ve explored the limitations of the Median Price, let’s look at an alternative approach: the Typical Price.

Typical Price vs. Median Price

Due to limitations of the Median Price metric, HtAG uses a different approach when calculating typical house values.

The resulting metric is Typical Price, which we derive via a process called data fitting.

Data fitting is the process of fitting models to data and analysing the accuracy of the fit.

Engineers and scientists use data fitting techniques, including mathematical equations and nonparametric methods, to model acquired data.

In simple terms, data fitting is like trying on different sizes of a shirt until you find the one that fits you best.

Similarly, in data fitting, we try different mathematical equations until we find the one that best fits our data.

The chart below plots the Typical Price for Trevallyn.

As you can see, in contrast to Median Price metric the values are non-sporadic, and the trend is easily distinguishable.

Suburb Typical Price
Suburb quarterly price calculated via data fit procedure

Price for 3-bedroom houses in Trevallyn remained almost static (with slight decline) between 2010 and 2015.

The prices increased from 300,000$ in 2015 to 400,000$ in 2021.

Typical price is a revisionary metric and is recalculated every month for the current month and all previous month.

Despite its revisionary nature, the Typical Price offers a more accurate representation of the current market and long-term trends, when compared to median prices.

Conclusion: The Benefits of the Typical Price Metric

The world of real estate is complex and ever-changing. As such, the metrics we use to understand and navigate this landscape must be robust, accurate, and reflective of the market’s nuances.

While the Median Price has traditionally been a go-to metric for many investors and analysts, our exploration has revealed its limitations, particularly when it comes to assessing prices and trends at the suburb level.

The Median Price, though useful in providing a snapshot of a broad market like a capital city, can often mask the true dynamics at play within smaller sub-markets.

This is due to its susceptibility to fluctuations caused by data sparsity and the varying mix of property types and values within a suburb.

As a result, relying solely on the Median Price can lead to a skewed understanding of the market, potentially resulting in less informed investment decisions.

The typical price metric, derived using the data fit method, offers a more nuanced and accurate representation of property prices.

In the context of real estate, this method allows us to capture and reflect the true trends and price movements within a specific market over time.

The Typical Price is a revisionary metric, recalculated every month for the current month and all previous months.

This means it continually evolves and refines itself in response to new data, ensuring it remains an accurate reflection of the market.

Moreover, the Typical Price is not just a more accurate metric; it’s a reflection of the evolution of real estate analysis.

As we continue to harness the power of data and statistical methods, we can move beyond traditional metrics and embrace more sophisticated and accurate ways of understanding the property market.

Ready to take your market research to the next level?

Typical Price is one of the core property market metrics available in all HtAG reports and dashboards.

Visit our Getting Started Guide to discover other relevant metrics that can take your data-driven market research to the next level.

4 thoughts on “The Pitfalls of Median Price: How Typical Price Provides a More Accurate Picture”

  1. โš  Ever pause to wonder why the veterans of property investment rarely trust median prices when dissecting suburb statistics?

    Let me share a secret:

    Median prices can be deceiving. ๐Ÿค”

    Hereโ€™s why โ€“ most median price data floating around is based on a yearโ€™s worth of sales to pinpoint the current month’s median values for suburbs.

    Sounds unreasonable, right?

    But here’s why many data providers chose this method to report price data for suburbs:

    Relying solely on the current month’s sales turns the data into a bit of a wild card.

    Different properties trade hands every month, making median prices appear to jump unpredictably.

    So, you’re left with a choice:

    1๏ธโƒฃ Outdated data hitched to a year of sales,

    2๏ธโƒฃ Or the rollercoaster of current month data.

    There is no lesser evil. ๐Ÿ‘ฟ

    Both options are equally bad if you’re researching property markets.

    And that’s why it can feel like trying to grab hold of a mirage when you’re hunting houses at the suburb’s median price (or below it).

    Well, breathe easy. Iโ€™ve got your back! ๐Ÿ™Œ

    We’ve introduced something revolutionary called the Typical Price.

    Itโ€™s our secret sauce to provide you with reliable, realistic price data for suburbs, cutting through the confusion.

    Some of our customers go as far as calling it the AVM for suburbs.

  2. Hi Alex
    I wondered if you could have a filter for bedrooms for Typical Value? In some hot markets the 4 bedroom prices are much higher than the 3 bed ones so that would distort the typical value upwards as well. A filter on that would be awesome! Thanks mate!

  3. Hi Kien,

    We certainly do.

    Enable the ‘Any’ filter for beds on the LGA/Suburb ranking table.

    You’ll see data per number of bedrooms (where available).

    Then flick over to the Expert view and apply filter on the bedrooms column i.e. 3 BR houses.

    Do note that bedroom level data is only available where there are significant sales recorded per that bedroom series. Many markets only have data for the overall typical price value (all bedrooms). By filtering on BR data you’re essentially excluding these markets from your search.

    A better way would be to leave the BR filter at Any and apply the price filter slightly above the ‘All’ value for typical price. That way you capture markets with 4 BR houses in them that only have the overall typical price available.

    To understand the composition of BRs in these markets refer to the Demand Profile chart – you’ll need to drill down to the suburb dashboard to do that.

    Hope this helps and feel free to ask more questions!


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