An MBC reader requested a data run on the gap between asking prices
and closed sales
in the Sand Section over the last year or so. This was a buyer hoping to use the information for a negotiation on a future purchase.
Now we’ve got the results, covering 74 closed sales
(all property types, SFRs, THs, condos and MFRs) in the Sand Section between March 2006 and July 2007. Click here to download
the spreadsheets (PDF), which consist of several different sorts of the same data. Each sort runs 2 pages. The subject of the sort is labeled at top. Some logical groupings or gradations of data are noted with horizontal bars.First thing:
You’ll likely find this data fascinating. And yet, you may ask yourself – what do asking prices really mean?Major caveat:
The data aren’t complete, in that we’re only publishing sales with reductions,
and even then, not all sales with reductions in the time period.
These are limitations that result mainly from our going back beyond the starting point of MBC’s extensive local-market data tracking – our first Market Update
was dated March 27, 2007. Relying on other data sources (including a huge hat tip to the Manhattan Beach Real Estate Bubble blog
, which posted a database here
), it became clear we could not state with high levels of certainty that the data set was complete. Very likely we’d be missing some full-price or over-asking sales.
If we ignored a bunch of sales at or above asking, this would lead to criticism that MBC was skewing the data. So, we punted
– we show no
full-price sales, and ask readers to understand the decision. What that means is that we can’t describe how common it was
for prices to be reduced – we have just this set of data on reductions that did occur as sellers did what they had to do to get a deal.Solid numbers:
The closing dates and sale prices are solid, drawn mainly from Zillow and the county assessor’s records.Corrections:
There may be errors in this data, despite our best efforts. This posting is Version 1. We will make corrections and post new versions as necessary. Correx can be posted in comments or by private email to email@example.com.Analysis by Order of SortsSort by Address:
This is self-explanatory. If you’re wondering how much less your neighbor took than they were asking, you may find the answer easily here.Sort by $ reduction:
This one shows the amount of the reduction between asking price and closed price. Keep in mind, we’re tracking from the original asking price, not the latest list price. (Our brethren at the MB Bubble blog took the same approach as MBC does: recording the actual start date and price, not to be fooled by bogus re-listings. That makes this data more accurate, on the whole, than MLS-generated reports.)
The range of reductions in this data set is $14,000 to $937,500.
Reductions by $Sort by % reduction:
$300k or more: 11
Total price reduction is divided by original asking price. This calculation can help smooth out the differences between homes at different market tiers. In other words, $250k seems like a big reduction, unless the home sells for $3.7m (e.g., 132 18th
). That’s the same as taking $100k off a home priced nearer to $1.5m.
Reductions by %
Most reductions (62%) were less than 10%. Nearly a third (30%) were between 11-20%, however.Sort by Price Per Square Foot (PPSF):
Knowing PPSF for nearby, comparable sales can be very helpful. But with differences in lot size and many less-quantifiable factors (view, vintage, build quality, location, etc.), this measure can shrink in importance when comparing homes. Teardowns further skew the data, since they’re typically small homes being sold for lot value (70-80% or so of local property values) before they're replaced by much larger homes.
That said, there’s a clear confluence in these data around the $800-$900 range per square foot.
Price Per Square FootSort by Closed Sale Date:
This one is interesting because it appears to disprove
a theory one might have about the market generally, which we’ve read elsewhere. To wit:
2005 was the market peak, but by 2006 the winds shifted and many sellers were confused as to how to price their properties. By 2007 the confusion had dissipated and asking prices were gradually more realistic.Not so.
Watch the reductions-by-% column while scanning down this sort by date. There’s no pattern in the percentage reductions that corresponds with the sale closing date. Sellers were just as likely to be wrong on price in Spring 2006 as they were in Summer 2007.Bottom Line
Looking at price reductions this way is just one of many interesting, but flawed ways to evaluate the state of the market. (The data is probably most useful for the purpose of the original requester – to use in negotiations.)
Median price, for example, is dreadful for tracking the market, because it is so susceptible to changes in the market mix, as we are witnessing today on a broad scale and locally. Price per square foot is a good measure, but it’s thrown off by differences in lot size, location, variability in age and build quality, and, of course, teardowns/lot sales. We could go on…
But if there are this many reductions to talk about in one sub-section of Manhattan Beach,
that tells us one thing pretty clearly – as if it needed to be repeated – these ain’t the go-go days of wild and crazy appreciation, speculators and routine multiple-offer situations.
More subtly, the data show us that sellers are still struggling to balance their demands against the shifting market.
And as we go through this data now, there is a broad, palpable sense that this particular chapter is closing, as the market shifts from strange and confusing to… something else.