Rooned. We’ll all be rooned.
There is something about the way real estate trends are reported that borders on the irresponsible. OK. Real estate is the single biggest exposure that Joe and Jill Average have to the economic cycle and people are naturally interested. I get it. But bearing in mind the level of herd behaviour involved in any market, media exaggeration of any figure that can be converted into a sensational headline can only fuel irrational exuberance and despair.
Are sick people ever just driven to hospital by ambulance? No. they are always rushed to hospital. Do real estate markets ever just fall? No they plunge and then reel and then plunge again. But don’t worry. if you hang in long enough they will eventually surge. All these are verbal commentaries on what looks like a pretty orderly statistical process.
The common thread in all these headlines is the use a measure of middle sale price (usually the median). The headline figures actually differ significantly depending on the data source (REIV or APM) and are possibly dodgy. But regardless of which figure you take, it occurs to me, and I am sure I am not the first to make this observation, that there is a potentially huge transaction bias in these figures.
We are told that the first home buyers market is booming. So there are many more sales in the lower price range. So the median or mean sale price would go down, even in flat market.
It would be nice if some adjustment were made for this. The obvious way to do it is to benchmark the “fair value” of each property before it goes to market, using its features (such as land size, floor space, age and suburb) and some kind of flexible statistical model - say a neural net or random forest (or just a very flexible regression). You then measure whether each property sold for above or below trend and report the average % of this figure each month. You could use the previous 12 months of data with a rolling window.
I know that a team of MBA students at AGSM did something like this for McGrath and Partners in Sydney back in about 2001. But as far as I know their index (I am not clear if it became the McGrath APM Index) has never gained any traction with the commentariat.
According to the Herald Sun, Victorian house prices just suffered the biggest drop in 40 years. And now there is great speculation that the federal government will kill the first home buyers grant in their next budget and fear that this will cause the housing market to plunge and reel. If Kev does kill it, and if the first home buyers market does indeed suffer, then we will expect to see many fewer sales in this market segment. And so we will expect the median house price to…..surge.
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May 2nd, 2009 at 3:44 pm
Adjusting for the features of a house still presents problems though. There is a large difference in price between the house in Brighton which overlooks the bay, and the house in Brighton on/near the highway. How would you quantify this difference?
May 2nd, 2009 at 7:33 pm
The Case-Shiller in the US uses a better method of tracking repeat sales to give a better impression of price changes. I’m not certain if they correct for depreciation but it has only been a small factor in recent price changes.
The real estate mafia seems to have a very selective attitude towards price changes. Near to me is an area where the drop in prices 2007 to 2008 is apparently due to the large number of new units sold in 2007 inflating prices. This was something that they forgot to mention when promoting the areas potential in 2008 due to price rises 2006 to 2007.
Anyway asset price inflation is simply due to excessive expansion of debt, something that has now been relegated to the Federal government. Maybe they can “save” the property market for a few years but eventually it will collapse when they can no longer run the size of deficits required. A government running up sizeable debts to prop up property prices, something that mainly benefits the middle class, is an interesting new form of socialism.
May 4th, 2009 at 3:56 pm
Matt C over at CoreEcon (where I posted the same story) has pointed out that the ABS have a housing price index (ABS 6416.0) which at least tries to measure trend price. Specifically
The method used is “by calculating price movements on a matched sample basis”. For exisiting housing they use stratification to cluster houses according to a set of price determining characteristics. However, they apparently only use two variables to cluster - suburb average price and neighbourhood SEC.
It seems then that this matching would not account for more low priced houses coming onto the market, even though the effect might be reduced within more homogenous geographical areas.
Case-Shiller is based on tracking the re-sale price of specific houses and averaging over area. It strikes me that such data is going to be pretty rare so averages will be innaccurate. It also does not account for renovation and extensions. The other thing that worries me is that the Case-Shiller index is administered by the discredited and corrupt Standard and Poors.
Lastly, responding to Steve there are plenty of statistical models that can account for geography. You can input the latitude and longitude and model quite complex topology using neural nets or heirarchical Bayesian models.
All in all, I think that some kiind of statistical model for fair price is going to deliver the best index.
May 5th, 2009 at 7:46 am
I’ve seen a figure for Australia that house sales are now about every 7 years, and US is presumably similar, so there would be no problem with obtaining a reasonable sample. Main difficulty would be checking for renovations et, but they do remove houses with these from the index. Shiller is a respected economist, probably more respected now that his theory that most of the US economy is a bubble and will come to an end has been proven, and I expect he wouldn’t lend his name to something that was open to manipulation.