Quantifying Buyer Motivation

[RCA]

"I avoid statements like " The sale does not represent market value", or " it sold for over market value"..."

Why?

Some properties sell for over market value some for under, as we would expect from the typical definition of market value which included "most PROBABLE price". You will NEVER get all sales comp sale prices to mach the most probable price. So, think about it, you have to include all sales comp sale prices and live with it .... unless you feel that there is an anomaly to the effect that you don't have all the typical information for the property. So, for example, if a property sells for way above market value, and you don't have the lot size, then you should eliminate it from the analysis. Otherwise, you include it. And then look at the residual produced by your model and analyze that. You may conclude the reason the residual is so large is because the buyer was an idiot. But accept the sale price, after all the market has idiots, more or less than average depending on location, - it's a fact of life. Some states have more than others, from what I read on this forum. To be more specific, "idiots when it comes buying property."

The other issue I have observed, is that construction quality varies greatly between different areas. California, with it's zoning ordinances probably is producing some of the best homes nationwide, especially in areas where there are significant earthquake and fire hazards. And Californians can simply pay more for a home ... and that affects everything. And when you are sure of the quality - that impacts how tight the comps are going to be. People simply trust the market more.

When appraisers do high quality work, when they as a group can hit the market value on the head, they public trusts their work and adjusted comp sales prices narrow. One thing leads to the next.

If I were at Fannie Mae, I would want to go through all the recent SFR appraisals over the past several years on a state-by-state basis and study the spread of adjusted sale price values. That could turn up some interesting conclusions.