Understanding Price Dispersions

I recently had an interesting conversation with a Real Estate agent (whom I know for a long time) about local sales and prices. She had seen an increase in total units, but was surprised at the increase in home prices that have been reported. Having sold multiple identical units in the same waterfront condo complex, as well as having sold similar (or sometimes the same exact home) repeatedly, she was not seeing the allegedincrease in prices.

I mentioned Price Dispersion as the likely cause, and she looked at me quizzically. if someone in the industry for 3 decades is unfamiliar with the term, than perhaps a brief explanation and example are in order.

No two homes are truly identical, as they cannot occupy the same physical space. When the NAR or Zillow or RealtyTrack or Case-Shiller report about pricing, they are reporting a series of prices across different regions and neighborhoods, some with better locations and school districts than others. These are different size homes, with different finish quality and amenities

We do not do a particularly great job reporting these differences, other than describing them via price. We could report home sales the way we often do with Commercial Real Estate, on a $ per square footage basis; we mostly don’t.

Instead, we use a form of price dispersion that measures a range of price points. If you have access to the raw data, you can analyze the sale figures by deciles, showing which part of the market is doing better or worse, well or poorly. You could analyze monthly % differences from highest to lowest prices, standard deviation and variance of price distribution, etc.

But we don’t. We simply get a report of median sale price. This turns out to be highly misleading.

Let’s use cars as an example. If you wanted to know whether car prices were going up or down, you could take the average price of all cars sold each month. Or you could take a weighted average, where the greater the number of sale units have a greater impact on final price. We don’t want the 9 Bugatti Veyrons sold at $1.6 million dollars in 2011 skewing the results of 350,0000 Toyota Camrys at $23k.

Now imagine that this year, due to certain outside factors, we could not gain access to a small segment of auto data. No Toyota Yaris or Kia Rio or Ford Fiesta or Nissan Vestra or Chevy Sonic or, well, you get the idea. These are amongst the cheapest cars sold in America.

Imagine for the moment we stop getting the sales data for just these very inexpensive automobiles. What would this do to reported auto prices? Even if every make and manufacturer kept prices flat, it would appear that the median price was rising due to this dispersion.

Yet that is exactly what we have done in the residential real estate price reporting. Due to the voluntary foreclosure abatement, the bottom deciles of home sales appear to have stabilized, when in fact all that has happened is the distressed properties have artificially been kept off of the market.

That variance across sold homes is ending. We know that the foreclosure machinery is cranking up again now that the abatements are over. We should not be surprised if over the next 6 months we see significantly more distressed properties hit the market — and they typically sell at 20-30% discount below comparable non-distressed homes.

Consider how this will impact reported sale prices over the next few quarters. Its hard to make the case for housing turnaround when prices are falling.

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