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A while back, the National Association of Realtors, or NAR, released a series of so-called Anti-Bubble Reports with the intent to, and I quote from the NAR website, “show that the facts simply do not support the possibility of a housing bust.”
The reports were city-specific, so I felt compelled to have a look at what they’d put together for San Diego. I expected the usual flawed arguments from the bullish arsenal: the housing shortage and the robust job market, which are both myths. In perpetuating them, NAR did not disappoint.
I was surprised to find something else, though: a claimthat was, depending on how you interpret it, either wildly inaccurate or deceptive.
Why does that matter? Because NAR is the most vocal member of the “no-housing-bubble” crowd. Their analysis is propagated far and wide and is lent a lot of credence by the press.
These reports in specific appear to be intended primarily as a resource for real estate agents who are getting some difficult questions from would-be homebuyers. As such, the information in the reports will be used by people to make life-changing decisions. It’s obviously important to get the major arguments correct.
It’s also important to care whether the major arguments are correct – but we’ll get to that issue below. First I want to explain the problem I found in NAR’s report. This is a bit technical, so bear with me.
The report’s statement in question is the second bullet below (I include the first bullet only because it is referenced by the second):
– ARMS accounted for 67 percent [of loans] in 2004 across the region, one of the highest rates in the country. Furthermore, the interest-only loans accounted for nearly half of all loans in 2004. Therefore, some homeowners will feel the pinch of higher rates over time.
– However, only 3 percent of the loans have loan-to-value ratios above 90 percent, so the foreclosure risk is rather minimal. (That is, prices would have to decline by more than 10 percent to have a measurable impact on foreclosure rates.)
Alright, let’s pause and do a little translation. When someone borrows money to purchase a house, the ratio of the amount of the loan divided by the price of the house is referred to as the “loan-to-value ratio,” or LTV for short. The purpose of this figure is to quantify how much equity the borrower has in relation to how much he or she owes.
To give a quick example, if someone takes out a loan of $400,000 to buy a $500,000 home, the LTV on that loan is 80 percent. Another way of putting this is that the buyer made a 20 percent down payment. A different buyer who put down 10 percent would have a 90 percent LTV. And so on.
With the definitions behind us, let’s look back at the first sentence in the second bullet. The writing is unfortunately rather vague, so I can think of two possible ways to interpret that sentence.
One: that 3 percent of 2004 home sale transactions had LTV ratios above 90 percent. And the second: that 3 percent of loans taken out in 2004 had LTV ratios above 90 percent
Let’s go through each one.
The first statement, translated to English, effectively says, “The vast majority of 2004 San Diego hombuyers made significant down payments.” As a matter of fact, according to DataQuick, 38 percent of San Diego homebuyers in 2004 made down payments of less than 10 percent. Twenty-seven percent of buyers made no down payment at all. Anyone involved in real estate could tell you that down payments aren’t very popular in San Diego.
So statement No. 1 is categorically untrue. How about No. 2?
The second statement is saying that only 3 percent of loans, not homebuyers, have high LTVs. What’s the difference?
It’s very common for homebuyers to take out a second “piggyback” loan to supplement their primary loan, thus enabling them to make a smaller down payment without paying mortgage insurance. For example, a buyer may take out an 80 percent LTV first loan along with a 20 percent LTV piggyback loan.
Statement No. 2 maintains that only a very small percentage of individual loans had high LTVs. This may well be true, but it is completely irrelevant. If the intent is to surmise how much equity people have in their homes, then it is the number of homeowners, not individual loans, that matters.
You’ll note that the highest LTV in our example two paragraphs up was 80 percent. So, technically speaking, no loans had an LTV of greater than 80 percent. But the single homeowner involved had two loans totaling 100 percent LTV. Clearly the latter is the important statistic, and the former is absolutely useless.
But the report doesn’t quote a useless statistic and leave it at that – it goes on to imply that the statistic is quite significant.
The second sentence in the offending bullet says, “That is, prices would have to decline by more than 10 percent to have a measurable impact on foreclosure rates.”
What this sentence implies is that if prices fell by less than 10 percent, most homebuyers would still have equity left. This statement is very clearly predicated on the assumption that the large majority of homebuyers made down payments of more than 10 percent. But, as we saw above, this assumption is completely false.
As far as I can tell, NAR has either published data that is off by an order of magnitude, or is trying to make a statistic seem like something that it is not. If any reader of this column has a better explanation, please send us an email and let us know.
Meanwhile, I have repeatedly attempted to contact NAR in order to get more information and to make them aware of the discrepancy. My communications have been pretty well brushed off, and the last thing I heard was, “We will look into it.”
However, before sending me on my way they did let slip that the data came from a company called LoanPerformance. I contacted the folks at LoanPerformance and found them quite a bit more helpful. They said that the data they supply is based on individual loans, not on home sales, and that once they hand the data over to NAR they don’t really keep tabs on what NAR does with it. They felt that NAR had quoted the statistics on individual loans, per interpretation No. 2 above.
While the report’s statement is very deceptive, I suspect that it is not purposefully so. I just don’t think NAR would open themselves up to the kind of liability entailed in printing such an obvious misinterpretation of the situation. I think this is more likely a mistake.
It’s surprising that the research department of an organization as influential and well-funded as NAR could commit such a blunder, but mistakes do happen. If this is indeed an error, though, NAR is clearly uninterested in rectifying the problem. And that’s too bad because, as I said, people may be making big decisions based on this information. It matters.