Unexpectedly Intriguing!
March 20, 2008

Money and Homes One of the ways in which a real estate agent can separate themselves from the pack is to develop and promote a hyper-local market focus. By zeroing in on a particular market niche or geographic area, an agent with strong marketing savvy can really set themselves apart from other agents in the area and become a leading choice to become the listing agent for homesellers within that market.

We've previously remarked on how one agent has gone about establishing both transparency and building goodwill with prospective future clients in our own community. Way back in the stone age for Political Calculations, in fact, we cited one of the things that set them apart: a regular newsletter that provides information about the current state of the real estate market for the realtor's target region, in which the Realtor:

Lists all recent sale prices of homes sold for the Realtor's targeted market neighborhoods. The information is organized by neighborhood, address, house features (number of bedrooms, bathrooms, garages, square footage) and is listed by price from highest to lowest.

That was back in July 2005, in the early days of the building of the housing bubble. We recently received the Realtor's latest newsletter, and were surprised to see how they've modified the information they provide about recent home sales to adjust to the post-bubble market. The Realtor still organizes the data related to recent sales much the same way, but has dropped the garage data in favor of a much more useful metric: the number of days the homes that have recently sold were listed on the market!

This is extremely useful information - in fact, so useful that we've created the following chart showing the recent successful sales in our area, which reveals where the latest level of equilibrium has been established for the housing prices in our area:

Recent Selling Prices per Square Foot - March 2008

A quick note before continuing. For the Realtor's targeted neighborhoods, in which lot sizes are pretty similar from property to property, we've determined that the strongest driver that affects the selling price of a home is the house's square footage, followed next by the neighborhood in which the home is located, which affects the selling price to a much lesser extent. Other features, such as number of bedrooms, bathrooms, garages, etc. would seem to have a much lesser impact (or rather, are reflected in the square footage data.)

Now back to the chart. What we find is that the Realtor is rather subtly communicating where potential homesellers should be setting their asking prices. By including the days on market data, in which the lowest number of days listed until sold is 7 and the highest is 626 for the period covered by these recent home sales, we can have some pretty good confidence that the mean selling price per square foot of $144.37 is very close to the true equilibrium for housing prices today, as the number of days on market would seem to be largely independent of the price at which the home finally sold.

From this basic figure, the only other adjustment that a homeseller might need to be make is to adjust the asking price to take the home's neighborhood into account.

Armed with this data, the prospective homeseller can now have a reasonable expectation that their home will sell within a desirable period of time. We'd have to go through the entire MLS history for the homes that were on the markets the longest, but we strongly suspect that each of these homes started out being listed at much higher prices - only selling when they reached the relative level of equilibrium prices with homes listed for much shorter periods of time.

The chart also suggests that there is some stability entering into this particular housing market. To be sure, we'd have to go searching through the Realtor's back newsletters and preferably, MLS data, but as we don't have access to the MLS, we'll leave that exercise to either an enterprising Realtor or perhaps an economics student looking for a good thesis project.

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