Ever wonder why some REALTORS consistently take overpriced listing - even when they have access to pricing data in their MLS system? Is it simply because the agent is a wimp? Do they not know how to read the data, or generate an "absorption rate" analysis from it? Are sellers really so intimidating that, during the same meeting, they can force a REALTOR to take an overpriced listing, agree to endless newspaper advertising and cut their commission?

Naah. No matter how wimpy the agent is, nobody can be that much of a pushover (ouch, I just bit my tongue! I need to keep it out of my cheek...)

Maybe there's another explanation. Could it be that something in the data is wrong - leading REALTORS to "accept" overpriced listings because the data has led them to accept overpricing as the correct position in the market?

Here's an analogy: Ever wonder why the airline industry drives itself into bankruptcy on a regular basis? It's simple: The pricing of seats in the entire airline industry is set by the dumbest CEO in the business. That's right: If El-Cheapo Airlines decides they're going to run seats at some crazy-low price, at the tiniest profit, all of the other airlines rush to match their price! That's because, airline seats (like home listings) are commodities: and the lowest price in the marketplace sets the baseline for consumption for all buyers. In the same way that one airline with under-priced seats causes all airlines to drop their prices in order to compete for the buyers, perhaps a similar effect happens when real estate listings are overpriced in a marketplace. In either case, bad pricing policies ruin the industry for everyone - nationwide or in the local neighborhood.

This is the danger with un-carefully using MLS data for pricing references. The "dark side" of the data used for a CMA (market analysis) is this: if you don't know how to analyze the data, then you're only presenting it. So, in the old computer lingo: Garbage In, Garbage Out. Bad MLS data will lead to bad pricing decisions: and a bad marketplace. And where does bad data come from? Well, overpriced listings, of course.

Look at it this way: If the current listing inventory has been priced incorrectly (by even just one agent who will take any listing "at any cost"), then the MLS data becomes corrupt. Other agents, relying on the data to make "comparisons" with comparable competing properties are sabotaged. Their market analyses will become faulty, too, at least in the eyes of the seller, who wants the most for their sale. So a few agents overpricing a few listings could cause all agents to overprice their listings, too. Because listing price is public. And sellers have it before they even ask an agent to stop by with a CMA.

And there goes the neighborhood.

One might ask: doesn't the "sold" and "days on market" data prevent this from becoming exaggerated? Not likely. For starters, sold data is a picture of the past; listing price is about the present. REALTORS arguing against their prospective clients to select a current price based on past data are facing an uphill battle. Surely, the rational choice should be to price according to sold data (representing absorption rate). But sellers challenged with setting a current price can argue that the market must be different than the recent past. His evidence is that other agents are pricing their comparable listings much higher. Even the "days on market" argument won't protect the agent, because time is frequently more disposable to the seller than margin. They will gladly wait a few extra weeks to sell in the hopes of securing a higher price. Since the agent's fee is contingency based, time is of no matter to the seller, even though more time means higher costs for the agent.

All of this leaves many agents holding the bag: their overpricing friends in the marketplace make their "rational" pricing argument untenable. How do you get a seller to price it "right" because everyone else is happily continue pricing it "wrong." It's the myth of the rational consumer: When there's always another agent who will take the listing at a higher price, the seller will prefer to rely on current MLS pricing data.

And around and around we go. But the basic point remains: If the weakest link in the chain causes everybody to fall apart, then perhaps the worst-pricing agent in the MLS is making things tougher for the rest of us.

Oh: need a solution? Simple: Stop using MLS data.

But that's a story for another time.

- M