Do On-Line Home Price Estimators Distort the Market, Creating Drag or Distortion?

In an over-simplified nutshell, he is saying that no statistical model can know the market conditions and intricate attributes of a single property. Even in a subdivision where homes are basically Levittown-like replicas of each other, differences exist.

Rossi says “lying behind online home value estimators are a host of complicated statistical models that attempt to predict a home’s price based on comparisons with similar properties (comparable sales) using county property record data on a variety of attributes such as house square footage, number of bedrooms and bathrooms, among a number of features unique to that property. ”

Yes, aggregated data has come light years but is not a perfect science and significant information lags exist. And when we rely on “modelled outcomes” like, say, we did prior to the real estate bust, well things don’t always work out like the models say they should. In fact, it leads to a misunderstanding of risk.

These models have been around for a number of years and during the boom years were used extensively behind the scenes by banks (including those I worked for) as well as Fannie Mae and Freddie Mac as a way of reducing processing costs. During these years, regulatory agencies identified a number of significant limitations surrounding the use of these models. They tend to work better on homes of similar type and quality but break down quickly on custom homes, homes in rural areas, small neighborhoods and nonstandard property features. Further, no statistical model can understand the market and condition issues of a particular property. For example, these models cannot factor in property upkeep or whether the property sits directly across the street from a gas station, which could reduce its value.

Yes, we know that. Real estate is a hyperlocal story. But how can these ‘Zestimates” hurt a flea? I mean, most of us know they are off but it’s fun sometimes to see the numbers they come up with. But what if someone uses them to formulate an offer on a property?

Of some concern for regulators is the tradeoff between the percentage of homes where an automated valuation model could be used (known as AVM coverage) and the accuracy of the estimated value. The greater the use of the model across property types, the higher the valuation errors, typically. Those tradeoffs remain, and as we have learned from the crisis, anytime we become overly reliant on modeled outcomes it leads to a misunderstanding of risk: so saith Rossi.

In the specific application of online valuation engines, buyer offers can be highly influenced by the estimates generated from these models. In forming an offer, a buyer needs to obtain a reasonable view of what a home is worth. LOCAL appraisers are a good place to start. The values displayed by online real estate sites provide an easy way for a buyer to develop an offer. Let’s say they don’t know that the numbers they are looking at are at least 6 months old and many plusses about the house were not even recorded. Many homeowners fail to report property improvements, thinking they are saving on property taxes.

So what you get, says Rossi, is a lower offer based on flawed information. Flawed, old, stale information.

…Such outcomes create an artificial drag on house values during recovery periods and amplify price appreciation trends during boom periods given potential data lags in market pricing. In addition, the use of such valuations in forming bids can lengthen or prevent real estate transactions from being consummated given large potential gaps between sale and offer prices using these estimates.

I have to admit, I never thought of it that way. Did you?