Today Trulia announced the Trulia Price Monitor, which measures changes in listing prices of homes within their coverage areas. What’s interesting about this index is that reflects what’s happening now, as opposed to Case-Shiller and other indexes which measure sold prices of homes that actually went “pending” several months earlier.
In short, this index can give us an early hint at how home prices are changing.
The downside of course is that Trulia’s data is far from perfect. And it’s too soon to tell if their seasonal adjustments and adjustments for the “mix” of homes for sale will produce worthwhile results.
The Trulia Price Monitor and the Trulia Rent Monitor show every month what’s happening to asking prices and rents almost in real-time. By focusing on asking prices and releasing each month’s Monitors just days after each month ends, we can detect price movements at least three months before the major sales-price indexes do.
The Trulia Price Monitor differs from the major sales-price indexes in important ways.
First, we focus on asking prices. Final asking prices lead sales prices by about two or three months, reflecting the time that homes are typically on the market. In 2011, the Trulia Price Monitor’s national month-on-month changes track the seasonally-adjusted month-on-month changes in Case-Shiller and FHFA two months later. Asking prices, however, areNOT a perfect predictor of sales prices: the final sales price for a home can be above or below asking, and some listed homes might not sell. Asking prices and sales prices each have their advantages for understanding the housing market: asking prices have the advantage of showing current market conditions and trends, but sales prices are the best guide to historical and long-term trends in the housing market.
Second, the Trulia Price Monitor uses a different statistical approach: a “hedonic” rather than “repeat-sales” method.
Here’s their explanation of their “hedonic” method (how their sausage is made):
We run hedonic regressions of log-prices on property-level attributes, ZIP-code-level attributes and month dummies. We run separate regressions on for-sale and rental properties in each metropolitan area. The month-dummy coefficients are the basis for the Trulia Price Monitor and the Trulia Rent Monitor. The metro-level regressions are unweighted (unlike the Case-Shiller index, for example, which weights sales pairs by initial value). The national-level series is a weighted average of the metro series, weighted by the number of non-vacant owner-occupied or rental units (for the Price and Rent Monitors, respectively) according to the 2010 Census. We seasonally adjust the Trulia Price Monitor with the Census X-12 ARIMA software using five years of historical data, with separate seasonal adjustments for the national and each metro series.
List Prices Are Slowly Rising
So what does the listing data show? That, on a seasonally-adjusted basis, list prices are rising so far this Spring.
And Trulia notes:
One thing to keep in mind — because the Trulia Price Monitor is seasonally adjusted, these monthly and quarterly increases are on top oftypical springtime price jumps. Without adjusting for seasonality, asking prices rose 2.4% quarter over quarter.
Breaking Down California Metropolitan Areas
Trulia shares the Metro areas with the biggest price increases and biggest price declines. The only Northern California Cities to make the lists were Sacramento and Fresno, both among the worst performing cities. I’d be curios to know from any agents in these towns if this data passes the “sniff test.”
San Francisco registered an annual (March-t0-March) listing price drop of 2.9% and a quarterly (March-to-December) increase of just 0.1%. Oakland registered an annual drop of 5.8% and a quarterly drop of 0.9%. San Jose fell 2.0% annually and rose 0.9% over the last quarter. Click HERE for the complete list of cities.
I like what Trulia is attempting to do, which is tell us if the market is getting stronger or weaker right now. But because Bay Area neighborhoods are so diverse, with ultra-high end homes all the way down to crumbling shacks, short sales, and foreclosures, and because the samples are so large, I’m not convinced that any Buyer or Seller can see the index rising and believe that the real-time value of their home is going up accordingly.
Understanding the real-time momentum in a specific neighborhood and price range is the holy grail of housing data. Trulia’s new model is a step in the right direction, but doesn’t seem like anything that would help Buyers or Sellers in the trenches.