I’m sympathetic with contrarian investing practices. You’ve likely heard that, in the real estate market, spring and summer are the “buying” seasons. If that’s true, then there is an economic case for improving your purchasing power during the non-buying seasons.
Taking a two mile radius from downtown Austin, we show the average-discount-from-list-price ratio of sale price to list price (subtract from 1 to get the discount) for real estate sold in June and December. The data is obtained from the MLS and goes back to 2004. On average, since 2005, you can buy central Austin property for less in December than you can in June. Last year if you purchased in December then you saved an additional 3% from asking price.
I call it the “December Discount”.
This chart affirms, at least in part, that in recent years buyers purchasing in the “off season” are getting slightly better deals than buyers in spring and summer. Since 2005 you can see the December Discount increasing with each year. With the FHA loans currently filling a void in the credit markets, and a tax incentive bringing more buyers to the table, this year we might not see a continued divergence beyond 3%.
Jim says
Maybe it’s not a discount at all. Maybe it’s overpriced homes that don’t sell during the summer that stay on the market until december and are forced to take a price reduction to bring them in line with what sold in the summer. This graph needs to be adjusted for average annual price, or days on market.
Jude Galligan says
Perhaps, but not necessarily. This is a comparison measure of seller motivation at a particular time.
Jim says
In that case, the graph should only include homes that sold in the fall that were put on the market after August. Motivated buyers often sell in the summer and ask less to begin with. Those who are less motivated, overprice and are forced to take a higher discount later in the year.
Jude Galligan says
I ran the same test with your qualifier of properties sold with DOM < 90 days. It was a good suggestion, but the results are nearly identical.
John Curry says
That’s a very interesting statistic. Its nice to have empirical data to prove what I’ve always suspected.