03 Mar Myths: Property statistics never lie – Andrew Wilson
Dr Andrew Wilson defends the stats we all rely on and while they seem to differ, there are some ways to look at them that will reveal the true story. Andrew tells us more today.
Kevin: Another myth that we’re either going to dispel or prove today: that property statistics never lie. I’m going to talk to a man who deals with statistics all the time, Dr. Andrew Wilson, Senior Economist at the Domain Group.
Andrew, good morning.
Andrew: Good morning, Kevin.
Kevin: Do they ever lie?
Andrew: It depends on the models, of course. It’s a problematic exercise – modeling the housing market – for various reasons. At the granular level, every buyer and seller are different, every property is different in time and space, and it’s a question of putting enough observations together to get a feel for what the underlying activity levels are in a particular market.
That can mean, firstly, that you need a larger number of actual sales to get an accurate insight into the market and you also need a timeframe, as well, within a period that’s not looking too far back.
There are a number of factors – the mix of property sales, the time period involved, and the actual volume of sales that are available. We don’t want to be modeling… It’s easy enough to know what happened two or three years ago because we have a robust set of statistics. We want to know what’s happening as close to now as possible. That’s where we do get some flexibility in outcome.
I think it’s important for statistics in terms of house price modeling to use correlating measures of housing market activity. So not just house prices – the various methodologies – but also other factors such as auction clearance rates, auction volumes, and of course, the housing lending data that comes out from the ABS.
I think that helps us put a richer picture together to give us an understanding of what is actually happening now in the housing market. But the very nature of the fact that we only get 6% of all properties sold in a given year in most capital cities means that it’s always only ever going to be a snapshot.
It does remain a difficult issue, but nonetheless, one that if you use a variety of approaches, can give you some clear insight into what’s happening in the marketplace, which, of course, is very important if you’re thinking of buying and selling.
Kevin: That’s an interesting statistic you just hit us with there – that 6% of properties turn over. When you look at it in that sense, it really is a small snapshot, isn’t it?
Andrew: Absolutely. Then you think about all of the variety within that 6% and all the different agendas for buyers and sellers. Some sellers are desperate to sell; others might just be feeling the market out.
Some buyers are very keen on a particular property because it might be close to a relative or its size might suit them, and they’re prepared to pay a lot more than perhaps a buyer who doesn’t have that same motivation.
Some buyers have a higher financial capacity and are prepared to pay more, and other sellers might have more motivation or less motivation depending on their financial circumstances.
You need to put all these different variables together to try to understand what the underlying energy or the underlying fact or the underlying nature of a particular housing market is. That’s balanced against not having to look too far back because you want to know your information is more appropriate the closer it is to now rather than looking back a year when you have a lot of sales volume.
That’s the other point, too. Sales data does trickle through. Official sales data can take up to nine months to come through to those who model the data. Again, there is the lag in actually collecting the data.
There are a number of issues there. As I said, the key is to use different correlating methods of measurement, so that can put it all together and give you a clearer sense of what’s happening in housing markets.
Kevin: Well said, as always. Dr. Andrew Wilson, Senior Economist at the Domain Group.
Andrew, thank you so much for your time. Great talking to you.
Andrew: Thank you so much, Kevin.