Bulls have opinions; bears have opinions. How do can you tell who’s opinion is more likely to become future reality? What characteristics are exhibited by an analysis with good predictive power versus those without? How do you tell the difference between an opinion based on emotion, fantasy and wishful thinking from an opinion based on a rigorous, unbiased examination of the facts? These are the questions I wish to explore today.
As part of my job, I obtain market studies to evaluate various land uses for specific pieces of property. Based on the quality of the information in these reports, I make and implement recommendations on the purchase and development of multi-million dollar properties. If my analysis is faulty, or if I fail to recognize a faulty analysis in a report upon which my actions are based, the project’s investors will not meet their financial objectives. In short, if I mess up my analysis, people lose money.
The easiest way to demonstrate a good analysis from a bad one is to directly compare a good one to a bad one and note the key differences. For an example of a good analysis, I will use The Anatomy of a Credit Bubble, not because it is so great, but because I know it very well. For an example of a bad analysis I will use Gary Watts Real Estate Outlook 2007 because he has achieved local fame, and because his analysis is terrible.
The first thing an analysis must contain is accurate data which is verifiable. Garbage in, garbage out. For The Anatomy of a Credit Bubble I used data from the US census bureau, the local MLS, Newsweek magazine, US department o labor, and a variety of websites which used official government data sources. Basically, if you want to challenge the accuracy of the data presented in the analysis, you could go the source and verify it. I don’t have any problems with the accuracy of the data presented in the Gary Watts report, so he makes it past the first hurdle.
Once you have accurate data, the analysis of this data must focus on cause and effect. There must be direct causation linking a specific set of conditions to the outcomes these conditions will produce. A good analysis demonstrates this direct causal link in a clear and unambiguous manner. When an analysis relies on indirect causation, it is weak; when an analysis relies on implied causation, it is worthless.
In The Anatomy of a Credit Bubble, I demonstrated a number of direct causal links which impact how much people pay for houses:
- House prices are directly correlated with amounts borrowed.
- Amounts borrowed are directly correlated with the interest rate offered.
- Amounts borrowed are directly correlated with the borrowers debt-to-income ratio.
- Artificially low interest rates (reset issue) and exotic financing cause foreclosures.
- Foreclosures cause higher interest rates.
- Foreclosures above a certain threshold cause house prices to decline.
- Declining house prices causes more foreclosures. (note the causally related downward spiral)
- Declining house prices and increasing foreclosures cause lenders to lower debt-to-income ratios and raise interest rates.
- Lower debt-to-income ratios and rising interest rates cause amounts borrowed to decline.
- Less amounts borrowed (in conjunction with foreclosures) causes house prices to decline.
Notice the focus is always on correlation and causation forming a chain of events leading to an inevitable conclusion. A good analysis centers the debate around the premises. If the premises are true and accurate, the conclusions cannot be denied.
In contrast, a bad analysis states a conclusion and offers support through indirect or implied causation. When you read through the Gary Watts Real Estate Outlook 2007 you find yourself asking, “How does that impact house prices?” It is a question that is never answered.
Straw Man Arguments
“So Why Do You Feel So Bad? . . . Could It Be The Media? Remember all the fuss over Y2K? How about Killer Bees, West Nile Virus and the Mad Cow disease? What happened with 2005’s “serious” lack of vaccines for one of the “worst” flu seasons? Where did SARS and the Bird Flu. . . fly to?”
He left out crop circles, UFOs, Kennedy conspiracy theories, and the prophesies of Nostradamus. This is an effort to make all dissenters look like raving maniacs with no credibility. The implication is that people who believe there is a housing bubble must also have believed in these other erroneous predictions. This is a feeble attempt to increase his own credibility through linking his opponents to false predictions.
Gary Watts Real Estate Analysis
When he finally gets to real estate, he pulls out these gems:
“Housing Prices Continue to Decline!
Only the rate of appreciation is declining; home prices are still rising. The median profit earned for Orange County was $291,000 for 4 years of ownership!”
Here he conflates a rising median with rising prices for individual homes. We all know the prices of individual properties are declining. We have documented it in many, many posts. The median holds up only because sales at the bottom of the market are nearly zero and incentives and discounts are not reflected in the reported sales prices. The comment about the median profit is completely superfluous information which only documents that we had a bubble. It makes no statement as to whether house prices are currently rising or falling.
Next Mr. Watts comments on the decline in sales:
“Home Sales Decline By ____30___%!
They are measuring against 2005’s almost record year. Since 1996, the yearly average of all sales in Orange County has been 42,716. Last year our sales decline will be only 15% off our 10 year average.”
Sales are below the 10 year average, but only by 15%. Notice the attempt to make this seem insignificant? Bear markets in real estate begin with a dramatic drop in sales. This is the leading indicator everyone anticipates. He makes no mention of what this means. A good argument would have at least attempted to address the bearish argument of declining sales signaling the top of the market.
More nonsense, this time on foreclosures:
“Foreclosure Activity Rises!
They have to be up after hitting a record low! The truth is that 99% of all loans in the U.S. are not in foreclosure. The remaining 1% that were foreclosed upon had the following breakdown:
* 80% were classified by federal lenders as Professional Thieves and were turned over to the FBI.
* 20% were classified by lenders as Fraud for Property that resulted in unethical lending practices.
* Ca. Defaults: Historical 32,762 – Low: 12,145- 3Q’04 High: 59,987 – 1Q’96 Current: 37,273
* For all of ‘06, foreclosures accounted for only 1.81% of all Orange County sales, with lenders reselling those homes at an average discount of only 3.8%!”
Here he tries to make it sound as if borrowers are making their payments, and the foreclosure problem has nothing to do with the exotic loan terms. According to Gary Watts breakdown 100% of the foreclosures can be attributed to theft or fraud. Does anyone believe that? Somebody provide me a link to his supporting material concerning the breakdown of foreclosures — if it exists. I would like to see it. I suspect this is a rectal extraction. Plus, he completely ignores the implications of the trend in foreclosures which is increasing at an increasing rate. It isn’t the number of foreclosures today that is the problem, it is the number forecast for the next 5 to 7 years that is alarming.
Then Mr. Watts really pulls out all the stops,
“Affordability Index at Record Low – So Few Can Afford to Buy! Home ownership is at a record high of 70%, while the baby boomers ownership percentage is 80%! This index is archaic and does not account for how dramatically the world changed in 1979.”
Affordability is the central issue of the bubble. His drawn out attempt to make light of this problem is ridiculous. First, what does his statement about ownership percentages have to do with anything? Affordability is so low because this increase in home ownership (caused by loose lending standards) has driven up prices as buyers outbid one another for properties.
He tries to bridge to his analysis about the changing world in 1979… Basically, he says baby boomers are rich, and they will buy so much real estate that the market demand is limitless. This is silly. Baby boomers were big participants in the bubble, that is clear; however, now that these second homes are burning a financial hole in their pockets, they are not buying more, but instead selling what they have. Also, baby boomers are all moving toward the empty nest stage and into retirement. Their demand for housing space is going to decline as they downsize and abandon their McMansions.
Plus, I just have to wonder why this market altering event in 1979 didn’t prevent the last bear market from 1990 to 1996 — a bear market Gary Watts accurately predicted?
I don’t want to rehash his entire analysis, but when you read it you see numerous examples of indirect or implied causation. Each of the facts he mentions could in some way contribute to increased buying or decreased supply, but each of them also could amount to nothing. It is the shotgun approach: maybe one or two items out of the list of 20 will have an impact, so he just lists them all hoping the cumulative impact will convince the reader prices will increase. He plays on the inability of most people to sort through the details. He doesn’t dazzle them with brilliance, he baffles them with BS.
Give yourself an out
In the final paragraph, Gary Watts does give himself an out which makes the inaccuracies of his forecast look beyond his control.
“What to Watch:
1. If the Fed sees things it does not like and raises interest rates.
2. If increases in our housing inventory push the supply past 5.5 months.
3. Un-motivated sellers still entering the market in large numbers.”
This is an obvious tactic as explained by Rich Toscano,
“This is the type of permabull revisionism that we can expect a lot more of in the months and years ahead. It goes something like this: “We were right to predict infinitely rising home prices, but who could have foreseen Factor X?” Factor X might be further mortgage defaults, employment weakness, a consumer slowdown, outmigration, or any number of other problems. It will be discussed as if it was some entirely unpredictable exogenous shock, and that the bullish analysts’ predictions would have been spot on had the X-Factor not come into play. The truth is that the X-Factor will not be some external shock as they’d have us believe, but a likely if not inevitable result of the excesses of the housing bubble.”
At the time Gary Watts wrote his analysis, there was more than 5.5 months of inventory on the market. It has only gotten worse. He built in the excuse for the failure of his analysis.
A good analysis uses direct causation with verifiable data, clear premises and easy to understand conclusions. A bad analysis has faulty data and utilizes indirect or implied causation to support a hazy conclusion.
People in the industry who really want a market analysis employ companies like John Burns Consulting to get something with real predictive power. Nobody who makes multi-million dollar investment decisions uses Gary Watts. Quite honestly, if a consultant I used gave me a report like Gary’s, I probably wouldn’t pay them, and I certainly wouldn’t use them again.
Gary Watts analysis is nothing to take very seriously, but it doesn’t need to be. Gary’s place in the REIC is not that of a paid analyst, he is a paid shill of local realtors. His analysis is not intended to actually forecast anything, he merely needs to make it plausible enough to help realtors convince people to buy homes. If you want to rely on him to guide you for making the purchase of a home, do so at your own risk and with the full knowledge you are a sheeple being guided to the slaughterhouse.