## Home Buying Demand vs. Price Changes

In theory, there are two factors that affect the price of homes: supply and demand. We’ve looked extensively at the relationship between supply (inventory) and price in the past. Let’s take a look at the relationship between demand and price.

For the purpose of this post, we will measure demand by looking at the relationship between the number of closed sales in a month and the total population. For population, I’ll be using the “Civilian Labor Force” data from Workforce Explorer Washington, since it is reported monthly. Note that the number I’m using is not the number of people employed, but the total number of employable people. For the median price and total number of closed sales, I’ll be using the single-family home data released monthly by the NWMLS. All of the data will be for King County as a whole.

First, let’s have a look at a raw chart of all the data, which is available through early 1999:

In order to keep the graph from being an unintelligible mess, I’ve graphed the “1 Sale per X People” as a 12-month rolling average. This smooths out the large spikes that occur due to the highly seasonal nature of home sales. The YOY price change is also a rolling average, but only 6 months was necessary to smooth it out. You can see the raw data for both series in faint dashed lines.

Just by looking at this graph, you can see that there seems to be a relationship between the two—when the number of people per closed sale decreases, the price changes increase, and vice versa. Let’s take a closer look at this by graphing the two running averages on a scatter plot.

Clearly there’s some sort of relationship going on here, but with an R2 of just over 0.5, it’s not very strong. Let’s take a page out of Deejayoh’s playbook and see what it looks like if we compare each month’s rolling-average sales data with price change data sometime in the future. I looked at 3, 6, 9, and 12-month delays, and found that the strongest relationship was in a 9-month delay:

With an R2 of 0.81, now we’re talking. But what’s with that trail of dots (that I have highlighted in green) deviating so severely from the pattern of all the rest? Those represent the YOY price change data from the last 6 months, October through March. If we stop the series in September, the R2 jumps up to over 0.9.

So clearly there was a strong relationship between demand and home price changes, at least until late last year, when things began to fall apart.

But hold on a minute. Let’s go back to that first scatter plot again. I’ve highlighted the last six data points again in green, and given them their own trend line:

Whoa. Granted, 6 months of data isn’t much to go by, but still, R2 of nearly 1.0 is pretty hard to ignore. I think this is definitely a trend to keep an eye on. If we make the fairly reasonable assumptions that population will continue to grow at the average rate it has grown the last 12 months and YOY sales will continue to drop at the average rate of the last 6 months, this trend line would result in YOY median price drops approaching 20% by the end of 2008.

I am not saying that is what will happen, although it certainly could. I just find it interesting that the time-delay in the relationship between demand and prices seems to have all but vanished with the recent changes in the housing market. Who knows how long it will continue, and who knows what population and sales will really do. What I do know is that I will definitely be paying close attention to this relationship as the mess continues to unfold here in Seattle.

Sources:
Sales & Prices: NWMLS
Labor Force: Workforce Explorer Washington

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Tim Ellis is the founder of Seattle Bubble. His background in engineering and computer / internet technology, a fondness of data-based analysis of problems, and an addiction to spreadsheets all influence his perspective on the Seattle-area real estate market. Tim also hosts the weekly improv comedy sci-fi podcast Dispatches from the Multiverse.

1. 1
yeslerhill says:

I think the issue of people continuing to move here will become an issue as more nid to low end earning jobs in Seattle are lost as the economic depression hits Seattle.

So, if there are less low to mid earning people in the city, let alone moving to it, won’t this keep the prices for homes higher than if more low to moderate earners were avb for home buying in the city?

2. 2
jon says:

Linear regression, and all the related statistics such as R2, are only statistically valid when underlying process meets the requirements the undelying mathematics. The data here does not meet those requirements, so the statistically conclusions from the regression are not valid. Normally, we just ignore that and make our points anyway, what this being statistics and all, but this case is so bad it needs to be pointed out.

The first clue that something is awry is when the scatterplot of the regression does not look like a cloud. Having points in a cloud would be a result of meeting the statisical requirements of a collection of independent, identically distributed (IID) behavior for each item in the data set. In the first attempt, the data looks like a circle. That tells there there is some process that is driving the data that is quite different from what linear regression is able to generate valid results for. The term for this kind of data is autocorrelated, meaning that neighboring points in the data are highly correlated. Regression produces useless results for autocorrelated data.

The usual remedy is to perform differences on the autocorrelated data in order to try to get IID data. That means to compute the monthly changes, and run the regression on that. In The Tim’s analysis, he smooths the data. That is the opposite of differencing and makes the problems even worse for regression. In this case it is possible that differencing the data might work, but the relationship between price and population at the monthly level is dubious, and there is a huge seasonal component, which creates a whole other set of problems for regression

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laxtosnoco says:

+ 1 to what jon said. To pile on, you also shouldn’t shorten the time period under study and then celebrate that you get a higher R^2.

I do think the first chart you posted is interesting. Clearly the peak bubble period was driven by a higher percentage of people buying houses, rather than a dramatic increase in population.

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Sniglet says:

Good work providing new ways to analyze the local real-estate trends. If I might suggest a subject for a future post, it would be to compare the pricing trends and inventory levels to the percentage of sales with little or no equity (e.g. 100% finance or negative amortization).

It would be fascinating to see how the perecentage of owners without equity have trended with the broader inventory and appreciation over time.

5. 5
Alan says:

That graph looks like it has a bifurcation. Sometimes it follows one relationship. Other times it follows another relationship. Is there some feature that is correlated to the split? Perhaps if the YOY change is rising or falling (2nd derivative?)

6. 6
The Tim says:

RE: statistical rigor

I’m aware that this isn’t a scientific analysis. I just thought it was interesting. I definitely agree with laxtosnoco’s comment that “you also shouldn’t shorten the time period under study and then celebrate that you get a higher R^2,” and said as much in the post.

I just thought it was interesting to point out. Seems unlikely to be a totally random coincidence. I don’t think anybody would try to claim that home buying demand and price changes are unrelated (not with a straight face anyway).

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jon says:

Tim, if you are interesting in using regression to study this kind of data, I recommend you do the following experiment. Take two sets of unrelated data and run a regression on them. It’s best if the data looks like the data here, in that it goes up and down gradually. Your R2 will be ok, but not great. Then give one a time lag to get the best fit. You will get a great looking R2 that means absolutely nothing. Now pick the best size subsample of 6 data points, and you will get an awesome R2.

That will give you a better appreciation of how sensitive regression is to the underlying assumptions.

I once took a class in finance and questioned the professor’s use of the central limit theorem to make claims about outlying data. The rest of the class laughed at me for making suching a nerdly point, but the prof chastised the class, saying my point was valid, but that he had considered it an deemed the situation ok in that case. Well, that prof was Robert Merton who went on to become the chief economist for Long Term Capital Management, which you may recall had a small problem with outlying data that the Federal Reserve had to spend 10s of billions of dollars bailing out. No doubt many of the students in that classroom can be found now at places like Drexel Burham trying to figure out what went wrong there as well.

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johnnybigspenda says:

thanks jon for the reality check… I find that too many people agreeing with eachother devalues the value of the information, so this is a fresh reminder to think before we agree

… if you hadn’t piped up, it may have gone on for 25 posts of congratulating the Tim on his ‘breakthrough’… “yet another confirmation of why I should continue rent / or SEE I wasn’t wrong about not buying a house”.

Lets start talking about the end game here… what are the conditions that need to be present before we:
1. have price stability in the housing market
2. can start to predict “the bottom” so that we can look to buy while the pendulum of fear swings too far in the price decline direction?

At this point, seattlebubble can declare victory… YES, there is a bubble…. you are all very smart.

Lets stop agreeing with eachother here and start stretching to figure out the next step in the bubble process…

How is a person (more specifically a prospective homeowner) supposed to capitalize on this?

I’m sure many will take this post the wrong way, since it is not congruent with mainstream bubble thinking. Or isn’t it?

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mike2 says:

To put this in perspective with the nationwide housing bubble, prices continued to increase rapidly as home buying was available to people of successively lower means.

Seattle was not unique in that job growth over the past several years was primarily focused on lower paying jobs.

For a time, low pay was not a barrier to buying a home, since credit availability took up the slack (and then some!). Job creation, at any income level lead to home buying demand.

Now that economic fundamentals have crept back into the picture, it’s to be expected that purchasing trends, along with prices, will converge with what real incomes can support.

In that context, Tim’s graphs appear to be very pertinent.

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Silver9 says:

Im no stats whiz but doesnt “people per sale” involve two variables not one? the # of people AND the # of sales are both changing.

But how much has the population change affected prices? My guess is that the population as you measured it has barely budged.

On the other hand, I would assume the buying behavior has changed a lot and it is the behavior change not population change that is influencing the graph.

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Alan says:

How to determine the bottom of the bubble:

1. Find a long term inflation adjusted price for renting housing.
3. Figure out the rate of return that the economy is currently accepting. Dividend stocks might be a good way to judge this.

That amount will be slightly higher than the bottom. Rents will be depressed when housing sales are at the bottom. If you just use the current rental rate then you won’t be able to spot the bottom.

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dogwood says:

If the two data sets correlate best with a 9-month delay (with the exception of the data from since September), then this would suggest that the bifurcation in the original scatter plot is simply due to not having taken this delay into account. This would also suggest that, under ‘normal’ market conditions we would have to wait 9 months to see a change in the direction of the YOY price change after we see an inflection point in the # of people per closed sale data.

If this is true, and since the # people/sale data haven’t changed direction yet, then we are at least 9 months away from when the YOY price declines stop increasing in magnitude, and even farther away from the point at which they break back into positive territory.

But this is in a ‘normal’ market. The slope describing the correlation of the green dots (post-Sept. ’07), without the 9 month delay is similar to that of the other data (pre-Sept ’07) with the 9 month delay. This could suggest that YOY price changes have become more immediately sensitive to the number of people per closed sale (and vice-versa).

This indicates that the 9 month window of irrational exuberance was abruptly wrung out of the market last fall, and that we are on our way to a more predictable market in which the number of sales correlates with price (provided the total number of people doesn’t change). It could also reflect a sudden restriction in access to credit that quickly reduced the effective home-buying population.

This also seems to suggest a continuing drop in prices (with a stable population) will correlate with a decreasing number of sales, and this irrational pessimism could lead to decreases in prices that overshoot historical norms of price/rent and income/housing expenditure.

I’m not saying that I think this is the case (lots of ifs), but it’s interesting to build models, make predictions, and see how things actually play out.

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deejayoh says:

Tim –
I think if you ran the change in prices against the change in population it would probably meet Jon’s test (two series normalized for the time series).

While I don’t agree that the correlation for two trended series is always invalid because of autocorrelation, it’s also the case that correlation certainly doesn’t equal causation. Checking the normalized series against each other is a good test to check. whether there really is a relationship

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Joel says:

At this point, seattlebubble can declare victory… YES, there is a bubble…. you are all very smart.

While I’m sure there a lot of smart people here, I wouldn’t say that you had to be very smart to notice the housing bubble.

If you want to know how detect the bottom, look no further than equivalent rent. Housing has been so inflated for so long that it might seem strange to think that monthly rent should be about as much as the monthly carrying cost of buying, but it truly represents the “mean” in “reversion to the mean”.

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JayB says:

+1 on Joel’s point.

I think the bottom will come when someone can plug their rent into an online calculator and have it tell them that the mortgage payment on a particular home is equal to or less than what they’re paying to rent a particular property, e.g. when the tax adjusted cost of renting at least *looks* like the cost of owning, barring taxes, maintenance, etc…

Whether or not the person in question is going to have the downpayment available, the credit rating necessary to get a loan with the rate that their online calculation was based on, etc is another question.

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mike2 says:

johnnybigspenda, let me clue you in on what I’m seeing in my local market (DC – NoVa) that is well ahead of Seattle in the whole bubble burst.

I’m renting a place, that after the income tax deduction, assuming 6.5% interest rates, is closing in on break-even with renting. Our next door neighbors just bought, and they’re paying slightly less (after taxes) to own than we are paying to rent.

We earn considerably more income than they do – 60%+ more in fact (why they were so eager to tell us what they earn is beyond me) , so the payment itself is a non-issue. We could buy the place we live in and spend less than 20% of gross income on PITI.

Problem is, prices are unstable, and monthly payment feels nearly irrelevant when values are falling and sales volume continues to cliff-dive. In these conditions, I’d need to buy well under the break even rental value (Non-owner occupied) with a reasonable expectation that rents won’t decrease as well.

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jon says:

The reason the last 6 months have such a great fit is because he is regressing a 12 month rolling average against a 6 month rolling average. In only six months of such data there really aren’t any degrees of freedom at all left, but the computer doesn’t know that when it spits out an R2 number with 3 significant digits.

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b says:

yeslerhill –

No, that will add to price pressure pushing real estate down. Residential RE is built on a “pyramid scheme” type of structure. If the low end home sales evaporate because buyers have disappeared, then prices will fall until there are buyers in that category. Since most RE sellers go on to buy again, generally in the next tier, they will have less to spend and the next tier will have to lower their prices to find buyers. Rinse and repeat. The only areas that get to be immune to this is the very very top of the market where the players don’t care what they got for the old house because they are incredibly rich.

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wreckingbull says:

yet another confirmation of why I should continue rent / or SEE I wasn’t wrong about not buying a house

This is a reasonable and fair statement from the Big Spenda. With that in mind, I prefer to use 3rd grade math to decide when to buy again. All I needs to know is my divides-by-symbol to calculate P/E. People on the cusp could really do themselves a financial favor by taking Joel’s and Alan’s posts to heart.

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mike2 says:

JayBI think the bottom will come when someone can plug their rent into an online calculator and have it tell them that the mortgage payment on a particular home is equal to or less than what they’re paying to rent a particular property, e.g. when the tax adjusted cost of renting at least *looks* like the cost of owning, barring taxes, maintenance, etc…>/i>

No, it’s even lower than that.

You have to think ahead. Will you be able to sell the place and at least break even, or rent it out to break even, after 5 years?

How do you factor in a \$20K, \$40K, \$60K, \$80K, \$100K+ loss in principal value with the cost of renting? Along with transaction costs, whatever deposit you pay to rent pales in comparison to a principal loss of that magnitude.

Sure, I’d like to own, but if it costs \$50K extra, I’ll stick with renting.

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Joel says:

How do you factor in a \$20K, \$40K, \$60K, \$80K, \$100K+ loss in principal value with the cost of renting?

That doesn’t really matter as long as you can rent it out at a profit. Why take a loss and sell if the thing cash flows? Just hold onto it and the money it makes, until you break even.
The only problem, like others have already pointed out, is that rents are likely to go down (eventually) with prices meaning you could cash flow at first, but then later be renting out at a loss.
So I guess cashflow is just one criteria. I think the next most important criteria would be MOS or AR. Once MOS starts trending down for several months and gets well below 6 MOS that might be a sign that prices are approaching a bottom.

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Scotsman says:

Interesting graphs, and a new and different perspective on the issue. But I would be very careful in suggesting you’ve captured any causality here. My sense is that sales prices drive all of the data, and population/sales ratios are just along for the ride as a series of data points that really have little to do with why prices have declined independent of population changes.

23. 23
Garth says:

Where are these lower rents at? The two couples I know who are looking for a rental are having a hard time. All I have read about recently is increases.

Seattle is either different, or it will track with other markets. If we track with other markets rents are going up for another couple of years. Condos are the potential wildcard. I don’t understand condos at all.

The small investors with short term loans are not able to continue their level of leverage as that financing is no longer available to them, and the people / companies who are buying properties now to rent are looking to raise rates.

24. 24
george says:

Garth,

If Seattle follows the trend in other places, the rental market will first get tighter and then start to drop, like in Phoenix, Miami, or Austin.

Sure some landlords are looking to raise rents to cover their asses, but nobody with a brain is buying a property at these prices to rent it out. Everyone with even half a brain is selling.

25. 25
AMS says:

jon-

“Linear regression, and all the related statistics such as R2, are only statistically valid when underlying process meets the requirements the undelying mathematics.”

Starting with the sigma-field, what are the underlying mathematical requirements?

26. 26
Sniglet says:

I notice that there continue to be good rental deals for Bellevue 3 bed 2 bath SFH places on Craiglist for under \$1600.

Come over the to Microsoft Redmond campus area. There are plenty of SFH rentals around here, and some of them stay unoccupied for a year or more. I negotiated the landlord of my 3 bed 2 bath SFH down a year ago. I wouldn’t be surprised if many of the places that finally do get renters have to accept lower terms (considering how long some of these places stay vacant).

27. 27
Garth says:

George,

I have not seen alot of data for Austin , but I don’t think it is thought to have participated much in the real estate bubble

Phoenix and Miami are much more overbuilt than Seattle, at one point I read there was a 30 month supply of condos in Miami.

I have seen nothing that has compared the level of building and real estate activity in those cities to Seattle. If you have that info I would like to see it.

28. 28

TIM, YOUR GRAPHS PROVE WE CAN’T “GROW” OUR WAY OUT BY DOUBLING SEATTLE’S POPULATION

Its making it far worse with wage competition driving real estate buyers’ wages down, conjestion on our roads driving what’s left of local manufacturing out and even the local upper middle class [especially retirees] are getting sick of Washington being the 5th highest taxed state in the nation too; many of them are getting the Hades out as the cesspool worsens.

The answer is toll all the roads [make it even worse], add more even more insane growth and recycle more…lol

29. 29
Chris says:

I’m familiar with in-city Seattle rentals and I’m also working for an apartment developer. That said, I’m no pollyanna about rents and am, in fact, quite a bear with respect to the national econcomy…. What I’m seeing here is that rents have been generally afforable (as % of income, by HUD standards at least) and have trailed increases in incomes in Seattle since 2000. (median HH income up 3% or so annually over that time period v. a decline nationally). With the first time homebuyer market eviscerated, owners have some pricing power and can raise rents. While there are more condos on the market than in past years, there are not enough of them coming on via the shadow market to seriously slow growth in rental rates at this time. It could be a different story in 2009-2010 when a lot of new rental product is projected to arrive online.

30. 30
b says:

Garth –

This has been discussed before, I expect rents to increase for about the next year until rentals start to come online in much more force. Seattle, just like every other area in the bubble, has had a severe lack of rental creation during the bubble times. Condo conversions, apartments not being built in favor of condos and landlords selling their properties for top dollar and getting out of the game are all factors in this. The only reason rentals stayed reasonable is that the amount of people renting also decreased. We are now at the inflection point where rental demand is increasing but the supply is lagging. It will take another year or so before supply catches up, but when it does it will in a very big way. The new condos in SLU and downtown which are complete are already being rented out and many of them on the market waiting for sellers instead, just wait for the 5000+ other units to be finished. And no developer in their right mind is creating new condo projects right now, if they have just started them I expect it will be like many other areas and they will become apartments instead.

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alex says:

Here’s a suggestion for a new chart: I’d like to see the distribution of homes’ asking prices within 10k price bands (e.g., # of homes for sale @300-310k, then @310-320k, and so forth).

Why? if we watch that progression over time, we’ll get a grip of price resistence at cetain psychological limits (kinda like the Dow’s 12000).

Reason for suggestion: I’ve anecdotally noticed that asking prices will drop more easily from 550k to 500k than under 500k. Somehow, that “500” number is etched into seller’s minds as “fair” – that’s my impression, so I’d like to quantify that.. maybe other people would like that data quantified too?

32. 32
Buceri says:

This is where I disagree with most. Miami is NOT a good comparable town. They do have over 30 month supply of condos, prices were much lower which allowed for ANYONE to be a flipper; there are a lot of “players”, scam artists; and it’s an exotic location. Finally, the area of greater Miami has expanded all the way to Ft. Lauderdale and miles inland. There was nothing that could stop builders. Anything north of the Everglades, all the way to Orlando and Tampa is fair game. Now, of course, they realized they overbuilt.

33. 33
Ray Pepper says:

PRICE ALERTS!! Non Scientific but my personal 500 Realty buyers for April stats:

Ballard Townhouse asking 389k…Sold 389k 1 week on mkt
Snohomish Home asking 704k Sold 679k 1 month on mkt
North Tacoma asking 300k sold 300k 2 days on mkt
South Tacoma 210k (Foreclosure) sold 200k 3 months on mkt
Gig Harbor 299k sold 250 with seller carry 2nd 3 months on mkt
Gig Harbor 489k sold 450k seller concessions
Bellevue 740k foreclosure sold 678k 30 days on mkt.

What do we take from this…?? Absolutely nothing…The numbers are all over the
place…

I need Agents in Seattle/Lynnwood. Anyone looking for P/T please let me know!! I assure you it will be the best (and most profitable PT job you ever found!)

Ray Pepper
Broker
http://www.500Realty.net

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35. 35
Buceri says:

CNBC

Nobel Winner Stiglitz: US Facing Long Recession
Friday April 25, 12:16 pm ET

The U.S. economy is already in recession — and may echo the 1930s, Nobel Laureate Joseph Stiglitz said Friday.

“The big question is: how will the government respond?” said Stiglitz, in an interview with CNBC. Stiglitz, a Columbia University professor and 2001 winner of the Nobel prize, detailed his bleak outlook for the American economy.

“This is going to be one of the worst economic downturns since the Great Depression,” said Stiglitz.

He explained that main cause of the current situation is historically unique — and thus is befuddling those charged with creating solutions.

Other downturns were primarily caused by excesses in inventories or inflation; but this slowdown is due to the condition of “badly impaired” banks and financial entities, which are unwilling and/or unable to lend capital — stymieing the very borrowers who usually drive the country back to vitality, Stiglitz said. And the Federal Reserve may have used up its ammunition — and the faith investors and planners have put in it.

“[The Fed] will be between a rock and hard place. And we’re not over-worrying about credit. But [simultaneously], we need to start worrying about the real sector,” he said.

And if inflation wasn’t the prime recession cause, it’s still a menace. The professor points to the two-pronged danger of high oil prices joined by climbing food prices, harming businesses and scaring consumers.

“Oil is particularly bad,” as it means that more U.S. dollars “will be going abroad,” he said.

The housing downturn is an even worse economic factor than casual observers realized, Stiglitz said. He explained that during the real estate boom, Americans were able to withdraw billions of dollars from their home equity.

“[But] with housing prices coming down, it’s going to be difficult to do that anymore,” he said — drying up a spending source. And within that problem, still another complication: people typically spent the money they drew off their home equity on consumption, rather than investment — garnering no return on the spending.

“The savings rate as we go into the recession is zero. Which means [savings] will go up, ” he said — decreasing consumer spending and weakening retail further.

What about the government stimulus package?

“The Bush Administration’s response is too little, too late — and very badly designed,” he declared. The amount ostensibly being infused into the economy by tax rebate checks will be a “drop in the bucket” compared to the money being held back and siphoned out by the factors he mentioned.

“If you really wanted to stimulate the economy, increase unemployment insurance,” he suggested.

“The president is telling people to go out and get jobs — and there are no jobs for them,” he said.

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37. 37
biliruben says:

This just reinforced my view that one really good way to help would be to get a WPA-style program going. Our infrastructure is crumbling, and we need to get all these out of work or under-employed builders and contractors busy so they don’t lose their homes.

Toss a half trillion at that.

38. 38
deejayoh says:

I’m seeing the radarlogic \$/sqft figure for seattle trending back up. Now at \$214 off a low of \$210 – and the 1 day figures are much higher than the 28, indicating the trend is very positive

39. 39
40. 40
shawn says:

> At this point, seattlebubble can declare victory… YES, there is a bubble
> …. you are all very smart.

Webster: 4 a: mentally alert : bright b: knowledgeable c: shrewd “a smart investment”

Sounds good to me. Listen, the vast majority of the press said there was no bubble. So, why come here (where the truth was spoken) and argue with the other premises? My suggestion is to listen to those who have not lied and who have nothing to gain from your taking their advice.

41. 41
Scotsman says:

Here’s news of a big commercial project being put on hold in downtown Seattle- probably had a condo component. From todays WSJ:

Economy, Credit Woes
Foil Cities’ Big Projects
By JENNIFER S. FORSYTH
April 25, 2008; Page A1

A proposed \$7 billion downtown Seattle project has become the latest major urban development to be scotched or delayed because of the credit crisis and a faltering economy.

Seattle’s Clise family is pulling a 13-acre property for sale for at least \$600 million off the market, at least temporarily. The property was intended to be the catalyst for a project that would have totaled the square footage of as many as five Empire State Buildings, putting it on the scale of London’s Canary Wharf or the former World Trade Center in New York.

The Seattle project joins other projects in New York, Phoenix, Atlanta and Las Vegas that have been shelved, scaled back or beset by financial problems in recent months. Many city officials hoped they would provide jobs and economic activity that could help make up for a housing-market downturn that still hasn’t reached bottom.

42. 42
Michael says:

I am confused about Wall Street. It is obvious that main street is a depression but stocks are not getting hit the way that I expected. I would expect commercial real estate and finance to be hit the hardest. There have been some downturn in stocks such as WAMU and Bear but other banks seem to be plugging along just fine. It is bizarre when a bank can have multi-billiion dollar write downs daily and the stock goes up. Any idea? Their have been some setbacks but nothing like I was expecting. The Fed has given away 300,000 Billion so far. Is it just that Wall Street expects the fed to keep haing them money? Bush really is a socialist. Bank losses are public property while bank profits are private property.

43. 43
b says:

Michael –

Yes, it is a the Fed floor, especially for financials. The Fed is swapping out treasuries to these investment banks in exchange for their garbage mortgages. The investment banks turn around and pump the market with that money and the charade continues. One day it will end, most likely in a very spectacular manner. The question is when.

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Garth says:

Tim has a few months left on this prediction:

https://seattlebubble.com/blog/2007/07/16/rent-increases-likely-to-taper-off-soon/

But it is not looking good right now.

45. 45

[…] interesting. The graph below is an updated version of something I presented originally in the post Home Buying Demand vs. Price Changes back in […]