BusinessWeek had a good idea this week: look at big metropolitan areas and see how the best-performing zip codes have compared to the worst-performing ones. Unfortunately, the final implementation is atrocious: it involves clicking laboriously through an interminable slide show, and it’s impossible to see all the data at once. So here’s an at-a-glance table:
|City||Best ZIP||Price change (%)||Worst ZIP||Price change (%)||Difference (ppts)|
|Salt Lake City||84103||+17||84044||-7||24|
As a rule, expensive neighborhoods seem to be the ones which have gone up in price, while cheaper ones have gone down. But Cleveland is an exception: houses in Solon, which fell by 22% over the past year, are still 44% more expensive than houses in Amherst, which rose by 6%. The same’s true in Seattle, whose worst-performing neighborhood, Magnolia, has a median listing price of more than $700,000.
It’s interesting that there are bits of the Miami metropolitan area – like Jupiter, Florida – which have gone up substantially in price. (Admittedly, it’s almost 100 miles from Miami proper.) But my favorite pair of datapoints is in San Francisco — where Belvedere/Tiburon, in Marin (median house, $2.965 million, up 20% on the year), is directly across the bay from Richmond (median house, $202,771, down a whopping 49% on the year).
One big thing to learn from all this is that it’s silly trying to hedge downside in the value of your home by using the CME’s housing futures. It’s entirely possible that you could short your city’s house prices only to see your city’s housing prices go up and the value of your own home go down — thereby losing on both legs of the trade.
And the other thing to learn is that there are still entire zip codes, like Preston Hollow in Dallas, which have massively bucked the national trend and have seen house prices rise by a third over the course of the past year. Yes, we’re in a nationwide housing recession, but not all houses in the nation are falling in value. Exactly where you are within a metropolitan area can mean the difference between soaring values and slumping ones.
Update: Jake at Econompic Data has turned this into a pretty chart!