It’s the edge of the world
And all of western civilization
The sun may rise in the East
At least it settles in the final location
It’s understood that Hollywood
sells Californication

Destruction leads to a very rough road
But it also breeds creation
And earthquakes are to a girl’s guitar
They’re just another good vibration
And tidal waves couldn’t save the world
From Californication

California is one of America’s cultural centers — for better or worse. Now that we have had our first nationwide housing bubble, it will be interesting to see if California exports one of its most pernicious beliefs: perpetual house price appreciation.

In the 1970s California experienced extreme price appreciation coinciding with the rampant inflation of the times. Like any financial bubble, many people made large fortunes, and many bagholders got burned. Once Californians realized they could drive up house prices and make large fortunes, the stage was set for repetition of the cycle.

This may be the most important point I have made on this blog:

House prices in California go up because Californians believe house prices go up.

Think about that for a moment. This simple fact eludes most people, and if there is anything I would like the readers of this blog to really understand it is how this works.

When people believe house prices will rise, it makes them want to buy. When they buy, they drive up house prices. Rising house prices convinces others that house prices will rise further. This causes even more buying. The cycle of rising and falling house prices in California is a completely psychological phenomenon.

It started in the 1970s, it was repeated again in the late 1980s, and it has been repeated again in the early 2000s. There is nothing magical about California real estate that makes it a better investment than real estate in other places. All California has is a pathological belief in appreciation that creates a high degree of volatility in the housing market. In my opinion, Houses Should Not Be a Commodity.

This uniquely Californian cultural pathology has been unleashed on the rest of the country. It will be interesting to see where else it takes hold.

Asking Price: $695,000

Income Requirement: $173,750

Downpayment Needed: $139,000

Purchase Price: $738,500

Purchase Date: 12/5/2005

Address: 42 Great Lawn, Irvine, CA 92620

Beds: 2
Baths: 2.5
Sq. Ft.: 1,824
$/Sq. Ft.: $381
Lot Size: –
Type: Condominium
Style: Other
Year Built: 2005
Stories: Two Levels
View(s): Mountain, Park or Green Belt
Area: Woodbury
County: Orange
MLS#: S512634
Status: Active
On Redfin: 4 days

From Redfin, “This home has it all; GREAT PRICE! BEST LOCATION! HIGHLY UPGRADED! OPEN FLOORPLAN! This home features gorgeous custom ‘old board’ wood flooring & berber carpeting. Gourmet kitchen w/ beautiful walnut cabinetry, ceasar stone counters & stainless steel appliances. Master suite offers walk-in closet, dual vanities w/ marble & Juliet’s balcony. Private courtyard entry opens to a separate den/office (which can be converted to a 3rd bedrm). Uppper level private deck w/ ‘picture perfect’ views & MORE. ..”

This home has all the UPPERCASE LETTERS AND EXCLAMATION POINTS YOU COULD EVER WANT!!!!!!!!!!

What is a ‘picture perfect’ view in Woodbury? Let me guess, your balcony looks directly into your neighbors bedroom, but at least the neighbor is hot.

Uppper?

And, of course, another gourmet kitchen…

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Ordinarily I would tell you about how much this seller would lose if they get their asking price ($85,200), but this seller is not going to get their asking price because of the REO in the neighborhood…

Asking Price: $639,900

Income Requirement: $147,475

Downpayment Needed: $117,980

Bank Purchase Price: $491,396

Bank Purchase Date: 9/20/2007

Address: 79 Winding Way, Irvine, CA 92620

Beds: 2
Baths: 2.5
Sq. Ft.: 1,850
$/Sq. Ft.: $346
Lot Size: –
Type: Condominium
Style: Other
Year Built: 2006
Stories: Two Levels
Area: Woodbury
County: Orange
MLS#: S513083
Status: Active
On Redfin: 1 day
New Listing (24 hours)

From Redfin, “Location, Location, Location! Fabulous Woodbury condo! Spacious kitchen with breakfast bar that opens to living room. Perfect for entertaining!!Gourgous tiled floors throughout. Master bedroom has it’s own bath with dual sinks. Nice patio in front. Close to everything and resort style amenities that include pool, spa, and more! “

Gourgous? Is that like couscous?

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I think the kool aid man must have visited JP Morgan’s REO department if they think they can sell this place for 25% more than they paid at auction.

It appears to me that our featured property seller is screwed. They are being undercut by this REO by $60,000, and based on the auction price of the REO, there doesn’t appear to be any market for these units at all. JP Morgan went to the auction and bought this unit for $491,396. There were no professional flippers out there who would even bid $500,000 and try to flip it for $575,000? If the pros don’t think this could sell for over $600,000, how is our featured seller going to get $695,000? No, I am afraid our featured seller is going to lose more than $85,000… a lot more…

But you tell me
Over and over and over again, my friend
Ah, you don’t believe
We’re on the eve
of destruction.

Don’t you understand what I’m tryin’ to say
Can’t you feel the fears I’m feelin’ today?
If the button is pushed, there’s no runnin’ away
There’ll be no one to save, with the world in a grave
[Take a look around ya boy, it’s bound to scare ya boy]

Eve of Destruction — Barry McGuire

The following test came to me from a reader named Zileas. It is great stuff, and it contains some sobering conclusions for those hoping to sell in Ladera Ranch…

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{adsense}
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What I did was try to build a predictive model using the same statistical
techniques used by economists and scientists to glean insights from data.

I did this because most of the time you just see “median price” or “low tier
median price” or whatever, and this tells you very little, and with such a
shallow market (low # of sales), these medians are all over the place… so
I wanted to get the best estimate I could, so I used the tools I know how to
use — statistical regression. The quick summary is that price may be
correcting a lot faster than the medians are letting on.

I took the last 6 months of condo sales in Ladera Ranch off of the MLS
database. I only used 1, 2 or 3 bedrooms condos to try to allow some
breadth of data, but to mostly be comparing apples to apples.

Anyway, before I get into the nitty-gritty of the model, here are my
important findings, the ones that I’m very confident about:

– 1/2/3 bedrooms in Ladera Ranch, on average, are losing $334 in value PER
DAY (over the last 6 months, and there is weak evidence this is
accelerating, and no evidence it is decelerating). This represents a 2.6%
value decrease per month on a 400k home!!! This is a lot higher than a lot
of other estimates, but ties in to all the talk about the low-tier market
falling faster.

– Each additional square foot you add to a property in this band adds $134
to the price, holding all else equal.

– Bedrooms and Bathrooms each add about 25k in value to a house, all other
factors held constant.

– Overpricing your house causes you to lose $0.23 on the final sale price
for every dollar you list it over its eventual sale price (if it sells at
all). Note that this is an anomaly — in good markets, over-pricing often
causes you to get more. Note 2 (sellers): price to sell!

Details:

My approach was to start with what I thought the major factors would be:
– Square Feet
– # of Bedrooms
– # of Bathrooms
– Garage Capacity
– Time at which it was sold (just raw market trend, not “seasonality” —
since I was only looking at 6 months of data its hard to do stuff like say
that Christmas is slow and prove it)
– Square of time at which it was sold (there is some rejiggering in here to
make this work, but this is to crudely capture some
accelerating/decelerating market trends)
– Fixed effects for development (this is an adjustment for whatever tract
the home was in)
– (there were other factors I wanted too look at but which were not in the
data set — HOA dues, taxes, quality of property, the development it is in,
if it was a REO, etc, but I had to work with what I had)

I was somewhat hampered by the lack of data points — I only had 61 to work
with, and more would allow me to make a much better model.

After messing around for a while, I realized I could only get meaningful
results using the following variables, given my shortage of data(if only I
had a full dump of the past year of MLS sales in OC…):

Square Feet
# of Baths
# of Beds
# of days ago the sale closed (I did this analysis on Nov 2)

Results (for Ladera Ranch):

1) As every day goes by, the average price of a house drops by $334. No
joke. On a $400k house that represents price going down 2.6% per month.
This means if you were offering on a house there, and your comparables were
telling you “$400k right now”, you would at the very minimum add 6 weeks of
depreciation in the offer to calculate when the house would actually close.

2) Garage capacity does not seem to predict housing price. This is probably
due to my limited data and because “garages” on MLS are not very descriptive
— you can’t tell if its tandem, or wide, or whatever. It’s also because
garages strongly predict baths and vice versa (bizarre!)

3) For every bed you add to a house, the value goes up about $25,000… But
this value tweaks around depending on how you do the model — it’s not super
accurate, but adding beds, holding all else equal, almost always increases
values.

4) For every bath you add to a house, value goes up about $25,000. This has
a lot of the same issues as the bed count, and has some other issues because
beds and baths “predict” each other.

5) For every additional square foot you add to a property, given that you
have a set # of beds, baths, etc, the value of the property rises by $143.

6) Yes, houses have some intrinsic value in this model at very small sqft
and 1 bed/1 bath, but the lower you go, the less accurate the model becomes.

7) This model still has a fair amount of swing for properties, as you might
expect… obviously, I’m not capturing a lot of other relevant factors and
my model only accounts for about 3/4 of the pricing factors.

Interesting other random results

– For every $1 you list your property over market price, the actual amount
you get for it goes down by about $0.23 in this market. This is
fascinating because other studies I’ve read have shown the opposite, that
every $1 you list over market price, you get $0.50 more. Note that I was
able to prove this result with high confidence, but it wasn’t in my model
because it had a minor interaction with the beds/baths variables and due to
my lack of data, I couldn’t separate it out enough.

– I can definitely show that different complexes sell for more or less, but
didn’t have enough data to make it work out with enough confidence for me to
include it in the model.

Technical notes for mathematicians:

This is an OLS regression. I whitewashed the results, though prior to that
heteroskedasticity wasn’t proven, with my Breusch-Pagan / Cook-Weisberg test
p value at 27%. Boxcox showed a theta of 1.8 reinforcing my choice of a
linear-linear model, which didn’t surprise me much since sqft to price
should be a somewhat linear relationship and sqft was the largest predictor.
Multicolinearity was weak – my VIFs were not exceeding 2, and I don’t see
any reason why my chosen variables should have high multi-colinearity. I
did have to filter out some weak predictors because I Felt they were likely
to have too much multi-colinearity.

Linear regression Number of obs = 61

F( 4, 56) = 79.56

Prob > F =0.0000

R-squared =0.7402

Root MSE =23976

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| Robust

————– soldprice | Coef. Std. Err. t P>|t| [95% Conf. Interval]

————-+————————————————————-

beds | 25448.56 6264.813 4.06 0.000 12898.63 7998.49

baths | 26872.12 13132.92 2.05 0.045 563.7275 53180.52

daysago | 334.447 73.30785 4.56 0.000 187.5937 481.3003

sqft | 143.1072 23.48726 6.09 0.000 96.05653 190.1578

_cons | 105957 22440.9 4.72 0.000 61002.43 150911.5

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One thing that jumped out at me was this statement:

Each additional square foot you add to a property in this band adds $134
to the price, holding all else equal.

To me this strongly implies that Ladera Ranch will bottom near $134/SF. If the incremental value is $134/SF, can the fundamental value be far behind?

What do you think?