Tommorrow we get the latest data on nominal house price growth, both the Standard and Poor's Case-Shiller index and the Federal Housing Finance Agency. One series in particular to pay attention to is the Minneapolis series from Case-Shiller. What makes Minneapolis so interesting? In July it recorded its highest monthly growth rate ever, growing 4.8% from June to July. That was better than any month during the boom. See figure one. Even more interesting is that the growth in July came just four months after the worst month ever for Minneapolis, a negative 5.9% in March. To restate that, this year Minneapolis has seen both its worst and best month of nominal house price growth in the Case-Shiller index (the data for Minneapolis starts in 1989). Uff da!
Even more striking, is that dismal March for Minneapolis is the worst month ever for all of the cities for all of the months in the Case-Shiller index. Yes, March 2009 Minneapolis takes the title for worst Case-Shiller month. But the 4.8% in July 2009 is also one of the best. Only Phoenix June '05 (4.9%), a rogue July '88 in San Diego (5.3%) and Las Vegas from March '04 to July '04 (all above 5.0% with a peak of 6.0% in June '04). In other words, not only has Minneapolis gone from its worst month to its best in a span of 4 months, it has gone from the worst ever across all cities to one of the best ever for all cities! Uff da! For sake of comparison, figure two plots nominal house price growth for both Minneapolis and Las Vegas. The current seasonal cycle in Minneapolis is similar in magnitude to the boom and bust we saw in Las Vegas. Of course the Las Vegas cycle was longer so it has had a much larger impact on the house price level.
Why such a big change in house prices? Lars at the diner in Lindstom would shrug it off and say, `Oh, that's the snow, everyone knows that.' Lars is very likely correct. Inspection of figure one suggests that there has been an increase in the seasonality of house prices in Minneapolis. To get around the problem of seasonality in house prices most data is typically deseasonlized. Figure three plots the raw data (blue line) and the seasonally adjusted (black line) data for Minneapolis. Clearly, the seasonal adjustments are not fully accounting for changing seasonality.
The insufficiency of the seasonal adjustments leaves a problem. Due to increasing seasonality we cannot distinguish whether the high growth in Minneapolis house prices is due to snow or due to a recovery.
As I will show in the next post, the increasing seasonality is a problem for most cities in the Case-Shiller sample. (This appears to be due to most seasonal adjustments smoothing the seasonal factors, more on this in another post). This is making it very hard for us to distinguish whether prices are really rising, or we are just observing an artifact of increasing seasonality. This is why examining Minneapolis house price growth over the next few months is important. It will be the best data to disentangle the recovery from snow.