Interpreting Current Housing Indicators

Finding the right economic indicators is a challenge for investors. Often the same data are presented in several different ways. How does one make the right choice?

Yesterday's data on home prices from S&P Case-Shiller provides a useful example. As everyone knows, prices are down significantly from peak values and the annual data have a strong seasonal component. There are three quite different approaches.

Month-over month changes. The 20-city home price index for April fell by 0.6% from March. This decline was reported by some media sources, but ignores the seasonality in the data. When the seasonal effect is strong, it can be quite misleading.

Year ago changes. Most solve the seasonality problem by comparing the prices in April, 2009, to those in April of 2008. Sources using this approach cited a price decline of 18.1%. This ran as a headline on some stories and as a subtitle on CNBC.

The problem with these year-over-year changes is that it is difficult to see improvement fast enough to be helpful for investment decisions. Let us illustrate this with an unlikely and extreme example. Suppose that the index went up 10% from April to May. The year-over-year value would still be a decline of 9.2%.

To avoid this problem, those using the year-over-year method compare the annual change in one month to that of another. The conclusion often reached is that prices are declining at a lower rate. This is not correct. In the example given, prices would be increasing, not declining at a lower rate. It is not easy to get real insight from a string of year-over-year numbers.

Seasonally adjusted data. S&P also puts out a seasonally adjusted version of the series. This allows the user to focus on the month to month change, the real time movement of greatest interest, while removing the regular seasonal pattern. Using this approach, prices declined by 0.9%, worse than suggested by the other two methods.

Conclusion

Using seasonally adjusted data is frequently the best solution for this sort of problem. Many of our fellow data consumers are suspicious of any adjustments to raw data. They are then forced to make their own seat of the pants guesstimates about how important the changes are.

Calculated Risk, a favorite and featured source, also focuses on the seasonally adjusted data. You can check out the latest update to this series, comparing it to the bank stress test assumptions, in this article.

Comments

[John Lounsbury:]

Jeff - - -

Good post. The state of the housing market is subject to much confusion, misinterpretation and wild claims of "calling the bottom". The analysis is complex, as you document in this article.

In addition to the complexity of analysis needed for the national averages, some local markets deviate significantly from the averages. The housing market is, is in fact, several markets. In fact, within various metropolitan areas there can be very dissimilar locales. For example, over recent months many areas have seen much larger relative sales volumes for lower priced homes than for higher priced.

You have done a good job of cautioning those looking for easy answers.

Jul 01 11:13 AM

[John Lounsbury:]

I posted a long analytical comment on the housing market on another article today and will not repeat it here. Go to seekingalpha.com/autho.... I discuss a major reason for the absense of buyers in the current market and the viscious cycle that must be broken to turn things around.

Jul 01 11:49 AM

[ain't no fo...:]

Thanks, Jeff, I always become a little better informed and discriminating after reading your articles.

Jul 01 12:43 PM

[Ted Hurlbut:]

Thanks for the post. this helps with my understanding of how to interpret the numbers.

I believe we're in a bottoming phase overall, but the housing market is likely to be a drag on any recovery. There's still too much inventory and unemployment is driving fresh foreeclosures. Housing may have led us into this, but it's not going to lead us out. And the anticipated problems in the commercial real estate market will only increase the headwind.

www.hurlbutassociates.com

Jul 01 12:57 PM

[Russ Wetherill:]

I agree that the month-to-month (MTM) and year-over-year (YOY) changes don't add much clarity to the housing market. The best way to gage the market that I have found is to perform a 12 month moving average of the monthly price change. This adds a bit of "tail to the kite" - smoothing out the seasonal price fluctuations of the ebb and flow of demand.

Comparing year-ago 12 mo moving averages to current moving averages allows cycle-to-cycle comparison. This cycle-to-cycle comparison also allows one to estimate the rate of change and extrapolate a bottom by curve fitting the rate.

Many might say that looking at YOY changes won't allow you to predict when the market bottom occurs soon enough to be of any value. But, like a battleship , the housing market takes a long time to turn. The measurement period should be tailored to provide enough foreknowledge coupled with enough certainty to be actionable in a timely manner. Reviewing the long-term trend on a monthly basis by comparing changes to the 12 month moving average on a MTM basis and YOY basis provides great visibility of the trends and velocities of the downturn and/or recovery.

Of course, there are always wild cards like foreclosure moratoriums, or other government programs that can't be predicted by the data. These wild cards, however, will show up over time in the price data and shift the predicted housing bottom to the left or right.

Jul 01 01:29 PM