Housing Bubble Bursting?

[moh malekpour]

Not even close, Moh. Try this from your own market.

As an appraiser, You should know that median is not the way to measure the housing price trend in a market like city of Los Angeles with huge variables and price spread. The housing price in the city of Los Angles is from $300,000 to $45,000,000.
Look at the below sample:
The median of the first column is $100,000 and the median of the second column is $110,000. The first column that has lower median sales price has higher sales prices below and above that median sales price than the second column that has higher median sales price.
The median for the housing price doesn’t prove anything. It is a center point where above it is higher prices and below it is lower prices. It doesn't prove anything

Price Price
$ 50,000.00 $ 20,000.00
$ 50,000.00 $ 30,000.00
$100,000.00 $ 30,000.00
$100,000.00 $ 30,000.00
$100,000.00 $110,000.00
$150,000.00 $110,000.00
$150,000.00 $150,000.00
$200,000.00 $150,000.00
$200,000.00 $150,000.00
Median $100,000.00 $110,000.00​

 

[George Hatch]

Mike,

If you'll Google "Japanese real estate trends" you'll find the same information repeated in different ways by multiple sources. If you didn't like seeing that data from the JREI, your're really not going to like the information from these other sources. Here's another blurb from a different (Japanese) source:

1. Real Estate Market Suffers Long Slump



According to "Officially Published Land Prices" released March 2004 by the Ministry of Land, Infrastructure and Transport (MLIT), the average price of land for all uses nationwide experienced a year-on-year drop of 6.2% in 2003, the 13th straight year of decline. Although this was slightly less than the 6.4% drop in the previous year, this outcome, coupled with falling stock prices, indicated that the country’s problem with asset deflation is not over yet.

Rents for private housing (consumer price index) and real estate leases (corporate services price index) both continued downward slides that started in around 2000. Overall, the Japanese real estate market does not appear to be pulling out of the long slumps in sales/purchases and leasing. ​

From the postwar period to the early 1990s, the market was supported by the myth of ever-increasing land prices1. Except for a brief period after the second oil crisis in the late 1970s, prices had almost exclusively headed in an upward direction. In the mid-1980s, a massive amount of capital was poured into the real estate market be cause of excess liquidity, brought on by an increased money supply resulting from a strong yen and extremely low interest rates. Later, however, speculative investment in real estate plunged sharply due to the money-tightening policies of the Bank of Japan, increased government oversight of transactions, strengthening of taxes on land transfers, and government regulation of transaction volume2. These measures were effective in curbing land prices, but they severely damaged the Japanese economy by devastating household finances and corporate balance sheets and causing financial institutions to accumulate bad debts. The wounds have yet to heal.

Then there's an article that was published with a Wall Street Journal tagline:​

Land prices in Japan continued to fall in 2005, but the pace of decline slowed for the third straight year and commercial-land prices in Tokyo and other big cities rose for the first time since 1990, in a sign that real-estate deflation is approaching an end, government data showed Thursday.

Overall land prices fell an average 2.8% last year, dropping for the 15th straight year, the Ministry of Land, Infrastructure and Transport said in its annual land-price report.

However, that was slower than a 5% fall in 2004 and a 6.2% drop in 2003, as land prices are showing signs of bottoming out or rising in some urban areas, according to the report.​

In the Tokyo area, commercial-land prices rose an average 1% in 2005, the first rise in 15 years, the data showed. Commercial-land prices in Osaka rose 0.8%, while those in Nagoya rose 0.9%, also the first rise since 1990. ​

"What's clear now is the worst for land prices is over, but real estate is and will continue to be a location-related business with some areas more attractive than others," said Jon Tanaka, director at RREEF, the real-estate investment arm of Deutsche Bank.​

Residential-land prices across Japan fell an average 2.7% in 2005, slower than a 4.6% drop in 2004 and a 5.7% fall in 2003, the report showed. Commercial-land prices also fell an average 2.7% last year, compared with a 5.6% decline in 2004 and a 7.4% decrease in 2003, according to the data.​

"This report shows that land prices are stabilizing or rising in some urban areas, reflecting economic conditions and higher earnings expectations for some property developments," a ministry official said.​

The ministry's report on land prices per square meter is measured as of Jan. 1 and is compiled annually. It serves as a benchmark for public and private land transactions and for government assessment of inheritance and property taxes. The latest report surveyed prices at 31,230 locations nationwide.​

 

[Couch Potato]

Any Reputable Sources?

Don't you have any reputable sources George? :rainfro: :rainfro:

A cousin in Osaka or something? :rainfro: :rainfro:

 

[Randolph Kinney]

Housing bubble arrives at its Dow 36,000 moment

On April 1, 2006, the New York Times ran an article by Damon Marlin entitled "Some new math on homes."

A paper presented at the Brookings Institution by Margaret Hwang Smith entitled "Bubble, bubble, where's the housing bubble?" , Smith's anti-bubble and "screaming buy" contention is a purported "new" methodology of valuing housing using a well known financial function called net present value (NPV). NPV is the difference between the present value of cash inflows (rent) and the present value of cash outflows (mortgage, maintenance, taxes, catastrophe insurance, etc.).

Smith inputs the rent paid on the rental home as the cash inflow while estimating cash outflows (mortgage, maintenance, taxes, insurance) at 2% of the owned home's value into her NPV calculator. Ergo out comes the calculation and conclusion: no bubble and screaming buy.

Smith's research -- a personal decision to buy a 1922 Craftsman home for $950,000 in Claremont, Southern California, that is according to the article "a real estate market that has been described as overpriced by most and a bubble by some." According to the article, the owner asked the Smith's to come up with a price, which is when they hit upon their magic formula to determine housing prices. Their first bid was not accepted but their calculations suggested that they could bid up to 30% more than the value of their current home and still generate an after tax return of 8%.

But looking at their decision making objectively, without the rose tinted glasses of a real estate bubble, its clear what the Smith's have done. First, they found a home they loved. Next, they conveniently happen upon a calculation and assumptions that would justify their purchase. However, as anyone that deals in real estate knows, this type of calculation is a chimera. What this is, is a case of pattern fitting (finding a model to justify one's decision) and data mining (finding assumptions to fit one's decision). Having made the decision to buy an expensive home, the Smith's have found a calculation and a set of assumptions that justifies their decision to buy their new home. The fact that they had to find this "new" and novel means to compute their home's value is a giant red flag of the inherent bias in their conclusions.

Looking up our college era text book "Fundamentals of real estate investment for decision makers" (Author: Deborah Ann Ford, Publisher: West Publishing, 1994 Edition) we find Smith's purported "new" methodology listed in chapter 9 entitled "Real estate investing under uncertainty." In Ford's introduction we find sagacious words that are as applicable then as now: "Too often in the past...real property have been approached with what amounts to emotional and sometimes mystical investment techniques...wishful thinking has sometimes substituted for clear analysis. Many investors in the 1980s believed that if a property 'paid for itself' it was worth the price. There is...no sure investment method that guarantees making the right decision all of the time."

Financial investors use a probabilistic, scenario analysis varying inputs like cash flow, financing terms and risk assumptions. Financial investors are highly sensitive to variations in these inputs and understand that cashflow estimates are exactly that, estimates. There are always a range of possible cash flow outcomes and in this variation lie risks that can cause one to overvalue or undervalue a real estate investment.

Individual home owners are much more simplistic in their analysis. For example the current bubble was triggered initially by funds escaping the stock market bubble and then later by the gusher of liquidity provided by Greenspan's decision to lower interest rates to 1%. Low mortgage payments resulting from these very low interest rates, combined with non-existent credit standards (no doc loans, zero down loans) have stimulated a giant bubble. The 1980s real estate bubble was driven by changes to the tax code leading to a bubble that finally bottomed in the early 1990s.

Belying Smith's analysis, real estate prices have appreciated significantly even as rents have declined substantially in many markets. If individual home buyers were financial investors and operated in a world of rational expectations, they would perform the arbitrage to realize the difference between rental payments and the costs of owning a home. Instead as Marlin writes in the New York Times "few people do that math when they buy a house. They look at what other houses are selling for and base their bid on some expectation of what the house may be worth in the future."

In other words, home buyers do not operate in a world of rational expectations. They are easily swayed by low interest payments, low down payments, tax code changes and perhaps most importantly by the emotional tug of being left behind or not getting their fair share of wealth that others are receiving. This last factor is the founding basis for behavioral finance and Capuchinomics. We then fully understand that such behavior is emotionally normal, but financially destructive.

The fallacy in Smith's logic like the falsity of the Dow 36,000 logic will emerge, in time. As always, the veracity of our prognostications can only be confirmed through the passage of time. Nonetheless, we wager that home prices will track the performance of the Dow 36,000 prediction, and that home prices will stagnate or decline for years to come even if Smith and others find emotional justifications for current values.

 

[George Hatch]

The problem with using the median is that it assumes that the distribution of data between the two datasets is the same or very similar. We had an article in our local newspaper that concluded that prices were still rising quickly based on the medians, only this author was dumb enough to use a couple zip code areas as examples. That turned out to be a big mistake because it enabled me to gauge the credibility of the conclusion by checking up the work that went into it.

I looked the data up for both years and, being familiar with the composition of the areas, started parsing the datasets to see if there was any difference in the distribution of the data. In other words, were the datasets reasonably similar in composition?

I broke the datasets for the one zip area into four components, separating the sales by the age of the homes. There were construction booms during the late 70s, mid-80s, and then the recent boom since 1996 divided into pre-2000 and post-2000 homes. Each period features different sized homes and different price ranges to go with those different attributes. I had to break the newer boom up because the post 2000 homes are on average larger and even more expensive than the homes from prior to yr2000. There was almost nothing built during the interim periods, so I wasn't surprised to find that neither dataset had any units that were built during the odd years.

I suppose that only some of you would be surprised to find out that the composition of the yr2004 dataset was a lot different from the yr2005 dataset. The yr2004 dataset had twice as many of the older homes (which are much smaller on average), and the yr2005 dataset had twice as many newer homes. Needless to say, when comparing the averages of each component to its apple in 2005 the results were far different than the conclusion drawn by the author of the "prices continue to increase" article. Yes, the medians had increased substantially, but the prices on the older units had no discernible increases and the only segment with significant increases were the homes in the newest segments.

Q: How many new $1,400,000 tract homes does it take to influence a dataset that includes $700k tract homes from the late-70s and $750k homes from the mid-80s?

A: Not very many.

I saw the same trends in the other zip areas he cited, the lower end homes weren't selling as fast even though they comprise more than 50% of the listings, and the only price ranges that were continuing to move significantly were the new home resales and the new homes. When a developer releases 12 new units at a time it plays havoc with the medians for that period.

Needless to say, I came to a very different conclusion even though I was looking at the same data.

That was 2005 vs 2004. Since the beginning of this year we're starting to see bank-owned foreclosure sales, short sales, and the developers are starting to discount their inventories (another story in itself). I anticipate the 2005 v 2006 datasets will tell a very different story.

By way of clarification, I've also come to change my opinion about how the market would unwind as a result of these and other little exercises I've been running on the different datasets. I started off back in 2002/2003 thinking the lower end would hold up better and even continue to improve as the upper ends stagnated and declined. I figured the price ranges would compress like an accordion just as it did the last time. But when I see the opposite occur in 2005 I am compelled to rethink that and try and figure out the reasons for what is actually happening.

Whether you guys choose to believe me when I say this or not, my opinions are following the information, not the other way around. That's why I'm looking for the information and that's why I'm being sincere about wanting to see something of substance from you guys, because it might help me to better understand what's going on in my market. So by all means, if you've got it, bring it. There is much to be learned here yet.

 

[George Hatch]

Hey, I read the original analysis by Ms. Smith in the form of a 45-page paper that was posted somewhere (I forget where). As I recall, it wasn't just her working on this, it was also her husband who is also a professor at Claremont.

They ended up making a number of recommendations about which markets are undervalued. I think Indianapolis was their favorite right now. The main reason they were working on the Claremont house was because it was located close to their work and that seller reportedly didn't have a sale price in mind.

As an analytical method the idea of approaching an SFR purchase as an income-investment isn't a bad idea at all. What they did was conduct rent surveys on properties in different cities and then valuations on those properties to establish the relationships between rents and sale prices. Then they went through an income/expense analysis on a DCF basis over a holding term and even included the value upon resale.

Any appraiser who performs DCF analyses knows that the assumptions have a huge impact. The Smiths used some doozies in their analysis. For the one involving their home, they used a 3% average rate of increase over the life of the holding term, that 3% being applied to their initial sale price. Whoa, says I, that's a pretty agressive rate of increase considering where they're starting from. Now if the average rate of increase in the LA basin over the last 50 years is in the 2% to 2.5% range (depending on which index is being used) then that rate of increase would apply to the trendline itself, not necessarily to any specific point that contributes to that trendline. If you caught the trend at a low spot you would forecast more increase, but if you caught it at a high spot you would forecast a lower increase or even a loss.

Now if a person believes that the trends for the next 10 years will include an average increase of 3% that's really saying something when considering where we are right now. I daresay some RE investors would use a much lower rate of return right about now.

Using a 3% average rate of increase on their $950k home over the next 10 years would net a future value (before discounting for inflation) of $1,281,885 or $331,885 increase. Using a 2% average rate of increase would net a FV of only $1,160,139, or $210,139 increase. That's a significant difference over a relatively short holding period.

The other thing they did was make assumptions about mortgages interest rates. They used a 20% downpayment and a relatively low mortgage rate of less than 6%. Just since they published the interest rates have exceeded that rate and many economists think the rates will continue to increase. It's not a given by any means.

The assumptions they used in their analysis are already proving to be problematic. If the trends for interest rates and property values continues the way it has been for the last 6 months, the assumptions they used will be obsolete by the end of the year.

 

[Randolph Kinney]

George - here's the paper & link

Bubble, Bubble, Where’s the Housing Bubble?

Margaret Hwang Smith
Department of Economics
Pomona College
Claremont CA 91711
909-607-7897
msmith@pomona.edu
Gary Smith
Department of Economics
Pomona College
Claremont CA 91711
909-607-3135
fax: 909-621-8576
gsmith@pomona.edu
Preliminary draft prepared for the Brookings Panel on Economic Activity, March 30-31, 2006
Corresponding author: Gary Smith
This research was supported by the John Randolph Haynes and Dora Haynes Foundation. We
are also grateful for the assistance of Brian Chew, Jay Daigle, Daniel Harding, Edmund Helmer,
Jesse Licht, Tom Renkert, John Romeo, and Sam Ross.​

http://www.brookings.edu/es/commentary/journals/bpea_macro/forum/bpea200603_smith.pdf​

 

[Randolph Kinney]

George, I can appreciate the assumptions and modeling that was done. To me, this is just an academic exercise in applying DCF of various types and assumptions. Although they attempt to show it is relevant to the housing market, only time will tell. Just like predicting the value of a stock based upon P/E ratios and earnings model, they do it with rents and it looks great on paper and may even produce results in the short run. Static models do not hold over multi-year periods.

Real estate is most likely not an efficient market. They make use of that by saying, "In an inefficient market, prices can be above or below fundamental value." They ignore the efficient market theory as it was applied to financial instruments and the bubble markets they had. They over simply with the following statement:

Housing prices and rents are tied together by the fact that the fundamental value of a house
depends on the anticipated rents, in the same way that the fundamental value of bonds and
stocks depends on the present value of the cash flow from these assets. However, just as bond
and stock prices are not a constant multiple of coupons and dividends, we should not expect the
fundamental value of a house to be a constant multiple of rents. Among the many factors that
affect the price-rent ratio are interest rates, risk premiums, growth rates, and tax laws (including
property, income, and capital gains taxes). Thus, just as with price-earnings ratios in the stock
market, price-rent ratios in the housing market can rise without signaling a bubble if, for example,
interest rates fall or there is an increase in the anticipated rate of growth of rents.​

The problem with the above, homes are worth what people will pay for them, not some calculated value based upon future assumptions.

Edit: I should qualify homes are worth what people pay for them, assuming they meet the definition of market value. In a pure market without financing, 100% cash purchase, a house is worth exactly what the buyer paid and the seller accepted at that moment in time.

 

[JSmith43]

Oh my, what would Milton do?

I am seeing an uptick of people coming to me for a solution to their own personal liquidity trap they find themselves in, usually job related. They used an income stream in their life's assumptions based upon a job that disappeared. They have landed on their feet, for the most part, but are a bit short.

I scheme with them and counsel them. Most want to save their homes & it is usually possible. Some want to down size. This is a very dynamic situation and people will make changes. Predicting what will happen.....it is not written at this point, IMO.

If we go negative on jobs and productivity, hello stagflation It won't be a bubble, however. It will be more like someone pulled the plug in a life raft in the middle of the ocean, for those in the life raft, but most boats will stay a float. I offer absolutely nothing to back up my opinion

 

[Randolph Kinney]

Oh my, what would Milton do?

Milton Friedman proved that it was changes in the money supply that impacted the economy, not changes in interest rates. When money growth accelerates, the economy accelerates, when money growth slows, so does the economy.

One reason Friedman’s teachings have been forgotten is that changes in the money supply immediately impact interest rates, but there is a lag of 6 to 9 months before the economy responds. As a result, it looks like interest rates impact growth when, in fact, both rates and the economy are responding to money - rates first, the economy second.

Unfortunately, two factors (bank deregulation and globalization) have undermined the usefulness of the money supply data as a forecasting tool. The old relationships between money and the economy just don’t work anymore.

As a result, economists who believe in Freidman (including the authors of this piece) are forced to watch interest rates. But we do not watch nominal rates. We watch real (or inflation adjusted) interest rates. When the Fed is not supplying enough money to the banking system, real rates tend to be high. When the Fed is adding excess liquidity, real rates are low.

In 2002 and 2003, the real federal funds rate was negative - a rare and clearly accommodative Fed policy. Today, overall inflation is running near 4%, while “core” inflation rates are near 2%. Using either measure, the real federal funds rate remains low by historical standards, as are interest rates across the entire yield curve.

Because the Fed has hiked rates at 14 consecutive meetings (from 1% to 4.5%), many analysts fret the Fed has tightened too much. But with real rates still low, the evidence suggests that the money supply is growing at a rate that will continue to lift growth, not hinder it. Elevated commodity prices and a relatively weak dollar are confirming signals of this accommodative Fed policy, which make us more bullish on economic growth in 2006.