The market needs churn

There have been a vast number of discussions here and on many other sites about the future direction of the housing market. My own opinion, as I have stated a number of times, is that without some further government stimulus the market will continue its slide. This is mainly based on observations of the market itself and also an understanding of how boomer baby demographics and their asset holdings are going to effect the market in the longer term.

But as I say, this is just opinion. For an investor, you want to see data. But what data ? Is there really any data available that tells you with some confidence what is going to happen to the housing market?

While musing on this point, I realised I had talked about it previously without making myself clear. Here is what I said.

My parents purchased a 3 bedder in Townsville in 1983, it cost them $66,000 at the time. They sold it 12 years later for $113,500. Not bad , they nearly doubled their money in 12 years. Yes they did, but only because of inflation.

That same house sold again 8 years later in 2003 for just $25,500 more.  However it sold again in 2004 for nearly $100,000 dollars more. Hang on you say, inflation was running at 2.5% in 2004. Yes it was, but by then it didn’t matter because another force had taken over the property market.

18 months later the house sold again for $80,000 more.  Since then it has stayed with the same owner so I can’t give you anymore stats on it. However as I have said in previous posts I purchased my first house in 1998,  I sold it 18 months later for just $3,000 more. I purchased a much larger house in 2001 for $190,000 I sold it in 2007 for $550,000.  Have a look at the credit graphs above. Do you see any reason why you think this was possible?

At the time of writing that post, I didn’t make it very clear what those graphs actually represented. The data is credit issued by banks per month for finance towards housing. This does not however represent the total outstanding credit in the private sector for housing because new loans can extinguish existing loans and existing loans can be payed down over time. What these graphs really represent is the transaction levels in the housing market, or as I like to call it the “Churn Rate”.

Transaction volumes and their relationship to price movements is something I have been  talking about for a long time because I have always considered them very important in determining housing price futures. To prove my point I thought I would compare a number of other key pieces of available data that you would logically expect to be related to the movement in house prices. In each of the graphs below I have overlayed the ABS capital house price index ( in purple ) so you can see the relationship between the data represented and the movements in house price. The capital cities index has only been available since March 2002 which is why I have chosen this date as a starting point. If anyone has access to a dataset on prices with a longer date then let me know as I would be very interested to know how the data fits for a longer time period.

Firstly the RBA’s financial aggregate data for housing. No relationship between the total growth rate and house prices:

Next, growth in M3, which some argue is related. However, since 2009 it clearly has not been:

Next, outstanding private sector credit for housing ($Millions):

Getting closer, but you will notice that even during the GFC and the following boom of the first home buyers grant, that are both prominent in the house prices, the total credit line didn’t move off trend. From the chart you can infer that the long term trend in house prices is related to increase in credit, but the fluctuations in price certainly are not. It is therefore fairly useless in predicting any short-medium term trends in prices, which are relatively important from the “when should I buy perspective”.

Something else is doing the actual driving, which brings us to our “Churn Rate” chart. Following is the financial commitments to housing per month by Australians. I have added a 12 month trend to the issuance data so that it matches the 12 month trend house price line.

You can see from the chart that the rate of issuance of loans by the banks is a leading indicator for price changes. So what does this tell us? In my opinion, the price of housing is driven by the demand for credit. So in times of high demand the price will go up and visa-versa. In other words “the market needs churn”. What drives prices is market liquidity. When credit is flowing freely then transactions occur more quickly and houses are “seen” to be in short supply. This drives up demand and therefore prices, but interestingly seems to have little effect on the overall trend growth in outstanding credit. The “Churn Rate” determines the price.

You can see there is currently a large divergence between prices and credit issuance. One must fall or the other rise.

Latest posts by __ADAM__ (see all)


  1. The correlation between aggregate housing finance and house prices is appalling.
    The ABS has an earlier house price series going back to 1986 here:$File/641603.xls
    If you take the period June 1990 to June 1997 you get a total house price rise of 15.6%. Using Stapledon’s figures it comes out at 16.7%. It therefore looks right.
    Aggregate housing finance for that period grew from $78.4b to $202.8b – a rise of 159%. Staggeringly more than the house price change even taking into account population growth and inflation of 17% over that whole period.
    Perhaps you can just look at the “churn” element for this period.
    Even so, the departure of house prices from the “churn” since late 2009 has been enormous.

      • Finally some mature analysis of the RE market. I said it before: Thanks DE and UE for your analysis, for bringing new ways of looking at the data to the table. It is a pleasure to read.

        @david: The statement “The most important factor in determining the value (price) of an asset is the cost of credit” tells me a lot about the current analysis of the RE market.

        The constant interchangeable use of the words price and value in the RE must go. I understand that the MSM and even the banks use them as if they meant the same thing. They don’t and any serious analysis should keep that in mind.

        The issue is that technical and fundamental analyses are getting mixed up. The source of that is that ambiguity of the price/value concepts in RE.

        I consider DE’s analysis a technical analysis piece. That is, he analysed the movement of price and came up with a leading indicator. Whether the indicator works or not, and how often, should be the matter of discussion.

        If you talk about value, then you have immediately engaged in fundamental analysis. As such, you should know that the most important factor to value an asset is not the price of credit. The most important factors are the future estimated inflows and the potential for growth against the risk free rate.

        If you talk about price movement, then you are in the realm of technical analysis. You are trying to analyse the emotional state of the market players: The buyers, the sellers, and those standing on the sidelines (yes, the latter count very much).

        In other words, you have to fire with concepts about price movements to shoot down DE’s argument in this article.

    • Sinbad. I agree with your analysis to a degree. Mortgage credit issuance will only have a direct impact on prices if supply is restricted. When supply is responsive, the extra credit demand will result predominantly in more homes being constructed rather than price increases.

      Australia’s housing supply was likely far more responsive in the 1990s than the 2000s as it preceded the establishment of urban growth boundaries in most of Australia’s capital cities and the hard push toward urban consolidation, up-front infrastructure charging, etc in the 2000s, which have since steepened the supply curve for housing.

      It could be the case that churn rates have become more indicative of price changes over the 2000s as supply has become less responsive, but possibly less relevant in the past when supply was more responsive.

    • It could also be that the correlation was weaker in the more distant past, but in the recent past it is more strong, due to some more fundamental changes in the system.

      Hence, reference to past relationships does not necessarily invalidate DE’s points.

      You need to:

      1) Specify the parameters selected for each time period, and why they were selected (underlying philosophy), and

      2) make a more holistic apples-to-apples comparison.

      It’s simply a matter of a making a better and more valid description.

      My 2c

      • “You need to:”
        I don’t think I do. I’m not the one asserting that:
        “the price of housing is driven by the demand for credit”
        “The “Churn Rate” determines the price.”
        “….prices and credit issuance. One must fall or the other rise.”

        • OK, sorry.

          1) “You” should have been more generic, and

          2) My points are to promote more robust logic, both in proposition of an arguement (DE in this case) and in of its critique (Sinbad in this case)

          Hope that clarifies…


  2. Alex Heyworth

    I suppose the banks might argue that they have to provide lots more finance, because the cost of housing has gone up so much!

  3. a simple passing on of debt through market transactions. If the baby boomer generation has had a significant involvement in the creation of a real estate bubble, then we could well expect the exodus of this generation to shape the market. I would imagine that IF this generation has used the R/E market for wealth generation over the past ten years then they would wish to realise this wealth at retirement.

  4. You know who else needs churn? Real estate agents. And IMO this will be a hidden driver behind the crash accelerating.

    There’s no doubt house prices are falling, and at the moment the industry is trying to hide this fact. But when it becomes obvious to everyone, real estate agents will have no choice but to tell vendors to reduce their expectations. Why? Because the agents need their commission – a low sale is better than no sale at all. Real estate agents will ironically be the ones who drive prices down even further as this crash progresses. They need churn, and lower priced churn is better than no churn at all.


  5. “You can see there is currently a large divergence between prices and credit issuance. One must fall or the other rise.”
    That conclusion has no basis. You have produced a relatively short term graph with some correlation over a few years and conclude that it must return? Your two lines are only close for those few years because you have selected scales which make them so. Check out that 1990-7 period.

  6. Sam Birmingham

    I was thinking along a similar line just this morning…

    Remember the days when people bought their new house “subject to the sale of” their current house?

    Is it just me or was that once the norm? What percentage of housing contracts contain the same condition precedent nowadays?

    Excuse me for reminiscing, but it seems that when the majority of people were trading in the same market (ie. selling one house to buy another), society wasn’t so concerned with whether prices went up or not…

    • this is definetely the normal practice in real estate now. a high percentage of contracts are subject to sale and it is not uncommon for there to be a string of at least half a dozen contract to be involved. a very complicated and frustrating environment for agents. this will change though when desperation increases…

      • Sam Birmingham

        Interesting… No doubt long chains of “subject to” contracts suck a heap of liquidity out of the market – ie. lower churn.

        I know that when I was in the market a few years back, people were so focused on “not missing out” that they could afford to sign on the dotted line and take a punt that they would sell the current house before they were required to settle (mind you, that was in Perth’s “Boomtown” era, when prices jumped 30%pa and you couldn’t find a spare bottle of champagne anywhere in the city)

  7. “…the price of housing is driven by the demand for credit…”

    It could just as easily be the other way around: the price of housing determines the demand for credit. If housing is thought of as being cheap, demand for housing and for finance will both rise.

    I think you are confusing cause and effect.

    Surely the demand for credit is a function of the price of credit, which also reflects the conditions of supply of credit.

    The cost of housing reflects both the supply of and demand for property. Among the factors that influence effective demand for housing, we can include the availability (supply) of credit.

    It is also pertinent to note that property is treated by sellers, buyers and financiers alike as an asset – not simply as a good for consumption. The most important factor in determining the value (price) of an asset is the cost of credit: that is, the level of real interest rates. The expectation that interest rates may fall/rise will certainly lead to an increase/reduction in the estimate of the future value of property, and induce an increase/decline in demand for property.

    So it is the level of current and expected real interest rates that determine both the demand for credit and the demand for housing.

    It cannot be that demand for credit as such is a cause of demand for housing and is therefore a determinant of property prices. Rather, it is supply of credit (and the cost of that supply) that mediates effective demand for and the price of housing.

    • Well you may be right but the chart seems to show that a change in credit issuance by banks leads to a change in price, not the other way around.

      There may be other factors that drive the change in the rate of credit issuance, such as real or perceived interest rates, wages, alien invasions, etc, but that doesn’t change the fact that as an investor watching the churn rate of mortgages seems to be a fair indicator for future price movements.

      But I will qualify that I will check the extended dataset provided by sinbad to make sure that this conclusion still fits.

      I will let you all know as soon as I have analyses the data, having said that I am sure you all, including sinbad, have spreadsheeting software, so feel free to whip up your own charts email them to me and tell me that my theory only works in the new
      Millennium. 🙂

      • The rate of credit issuance is not the same thing as demand for credit.

        Surely, the rate of issuance is a function of both supply and demand.

        It is entirely to be expected that the housing market and the credit market operate with a high degree of correlation. But correlation is not causation.

        • David, I am somewhat of an observationalist on data, in fact I once thought of changing my name to “observational economics”.

          I am not a statistician, and would easily lose an argument against one.

          I am simply pointing to trends in data that match what we are ACTUALLY seeing.

          If you can find a dataset that more closely matches movements in price then let me know. I will happily publish it giving you full ownership.

          • Observations are essential, DE.

            Other correlations which would be interesting to look at would be

            Nominal GDP
            Nominal gross housing stock
            Nominal gross household disposable income
            Nominal gross household debt

            and the household savings rate

            Somewhere such data must exist.

          • Good points by David.

            Qualitative and quantitative notions of the correlation of price with each of those such factors would be a GREAT analysis; as would examining the relative timing of peaks, troughs and inflexion points, for the sake of possibly invoking weak and strong causal mechanisms.

      • DE: I definitely want to plot these series. What data did you use from the set? I noticed the financial commitments spread sheet has many categories. I found none at the 20B mark for March 2011.



  8. The spikes in the commitments seem to be a leading indicator for market saturation (decline or flatlining). Given the lag, what you might be seeing is supply constraint, although, that doesn’t necessarily fail to inform about the future. There are a lot of bagholders in a RE crash. One of them is the builders.

  9. “without some further government stimulus the market will continue its slide.” Shhh, don’t give them ideas!


    Most housing transactions settle with the creation of new additional aggregate mortgage debt, when looking at the aggregate credit and housing market.

    Large quantity of new credit created = large buying power = high price

    Small quantity of new credit created = small buying power = low price

    If the creation of aggregate new mortgage credit fell to zero annual in aggregate prices would fall to a fraction of the total money on deposit in banks.

    • ^^^

      great point

      ie. relative demand (–> price support) must be considered, and is partially a function of both the magnitude of the injected money, and the rate of injection.

  11. To paraphrase the Irish P.M. Where did we get the idea that you could get rich by swapping mortgages for ever increasing amounts of debt? Ponzi. All in, no where left to go but down.

    Ah the herd. The government tells them not to worry, that sound was only a fart on the edge of the herd.

    Some of the herd believe it was a shot. Concerned but not yet freaked out.

    By the next fart expect the sound of thundering hoofs.