Kling on the housing market and the mess

by Russ Roberts on September 29, 2008

in Government Intervention, Podcast

The latest EconTalk is a conversation with Arnold Kling, blogger extraordinaire and former Freddie Mac economist talking about the evolution of housing markets in the United States. We taped it a few weeks back so we added a postscript on the current situation as well.

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{ 19 comments }

Flash Gordon September 29, 2008 at 2:37 pm

I think some politicians just did something that we can be thankful for and that will in time prove to have been the right thing. They defeated the bailout of Wall Street. Right now, the stock market doesn't like it. I haven't listened to the podcast yet, but if I remember his previous comments correctly I think Arnold Kling would be pleased. I could be wrong about that. What do you all think?

BoscoH September 29, 2008 at 3:37 pm

Sure he's pleased. But the Dems could write their own bill and pass it on a party line vote and let the Senate Republicans play chicken with the future of the universe. Then McCain will have to lead the filibuster against it and go all in over whether the people are as against this dumb bailout as the calls to the Congressional offices indicate and whether the inevitable depression can wait until after Nov 4. Interesting times.

T L Holaday September 29, 2008 at 3:49 pm

In the interest of lighting a candle rather than cursing the darkness, here is one of the US Census Bureau's reports on New Housing 2005-2007 as a Google Doc:

Data, yes, data!

Anyone who is curious as to the number and proportion of new homes that sold for less than $125K or more than $750K or tastefully selected prices in between can find it right there.

Russ Roberts September 29, 2008 at 5:08 pm

T L,

Couldn't get to your spreadsheet. I'll try again. You seem to think Arnold or I blames this on poor people. It's not about poor people. It's about people who borrowed more than they could pay back when prices went down or other unpleasant surprises. A lot of them were poor. But not all of them. Why is that important?

Between 1994 and 2005, the home ownership rate rose from 64% to 69%. A lot of those new homeowners were low income. But a lot of defaults on mortgages were people who bought houses that were too big for their budgets. So it was a mix.

Chris O'Leary September 29, 2008 at 5:26 pm

"Between 1994 and 2005, the home ownership rate rose from 64% to 69%. A lot of those new homeowners were low income. But a lot of defaults on mortgages were people who bought houses that were too big for their budgets. So it was a mix."

Do we have data on default rates for fixed rates or ARMs?

I would assume that some of the problem was people getting cheaper ARMs and then not being able to handle the escalating payments. Was it the ARM that enabled them to buy more house than they could afford?

T L Holaday September 29, 2008 at 5:35 pm

Try this URL instead. I have tested that it works while I am logged out of all Google accounts. I regret the typo in the prior post.

T L Holaday September 29, 2008 at 5:49 pm

Maybe borrowers defaulted because of ARM escalations; maybe they defaulted because housing prices declined; maybe they defaulted because it was better to default on a mortgage loan than a credit card loan; maybe they defaulted because borrowers who put less than 20% down always default a lot.

We don't know.

What we do know is that more minorities were able to get loans, and we know that slamming minorities has been a winning albeit contemptible strategy for centuries, and we do know that it is a lot easier to yell "minority" than it is to look at data.

We strongly suspect that 1%-down interest-only mortgage loans were written for $1.5M properties, and each one of those loans that defaulted may have been more costly to the lender than a dozen defaults on low-income mortgage loans; and we know that the relative damages are calculable, but it's easier to yell Barney Frank is the Devil than to do arithmetic.

T L Holaday September 29, 2008 at 5:55 pm

It's about people who borrowed more than they could pay back when prices went down or other unpleasant surprises. A lot of them were poor. But not all of them. Why is that important?

The reason it's important is because it affects policy recommendations. If Donald Trump borrows more money than he could pay back when prices went down, and if the Coal Miners' Widows Association borrows more money than it could pay back when prices went down, and the Donald Trump loss is five thousand times greater than the Coal Miners' Widows Association, clamping down on those darn Coal Miners' Widows is not going to help much. It's just going to be easier to do, because the Coal Miners' Widows are weak.

Russ Roberts September 29, 2008 at 6:30 pm

T L.

Good observation, T L. And the magnitudes matter. I look forward to reading the data you linked to.

But please stop bringing up "minorities." I have posted numerous times in the last two weeks and have made no mention of minorities or race in this issue. So please keep those ugly implications to yourself.

muirgeo September 29, 2008 at 6:51 pm

"But a lot of defaults on mortgages were people who bought houses that were too big for their budgets."

And a lot of banks took out loans (over leveraged) that were too big for their budgets. The implication that the government made them do is not suportted by the facts.

Borrowers have some responsibility but lenders and finaciers should take the burden of responsibility because "it's their business to know the drugs they are offering their patients". This is at best a case of serious malpractice at worst criminal conspiracy to defraud.

T L Holaday September 29, 2008 at 9:34 pm

Russ,

Don calls this "great good sense:"

The pressure to make more loans to minorities (read: to borrowers with weak credit histories) became relentless.

Don thus approves of the equation of weak credit history and minority. This is how dog whistles are created. Jacoby writes that "minority" should be read as "weak credit history", Don applauds, and henceforth for this group, "people with weak credit histories" is an encoding of "minority."

Don is a very smart man and he knows exactly what he is doing with this endorsement.

Sam Grove September 30, 2008 at 1:09 am

Borrowers have some responsibility but lenders and finaciers should take the burden of responsibility because "it's their business to know the drugs they are offering their patients".

Of course, and, sans a government bailout, the market is delivering to them their just rewards.

Given that doctors are human and not all-knowing beings, it's a good idea for patients to learn about the drugs their doctors are prescribing, for a number of reasons.

Martin Brock September 30, 2008 at 3:59 am

Kling says, "The mortgages can default, but the bonds cannot, so we (Freddie Mac) are in the middle taking the default risk."

He doesn't continue "until we can't bear the risk anymore, whereupon we transfer the risk to taxpayers."

Freddie Mac sells rents to rent seekers. That's its business in reality. That was always its business, even before the subprime debacle. If it doesn't sell rents to rent seekers, it needn't sell bonds at all.

GSEs could simply create money to lend and then remove this money from circulation as it's repaid, or (equivalently) it could be endowed with funds that it lends and then relends as loans are repaid, charging enough interest to keep its funds stable or growing rapidly enough to meet a growing demand for credit. It's only function then would be to police the credit. It would never pass yields to anyone except the growing pool of home sellers.

If the buyers of bonds don't stand to lose when credit is poorly policed, then they play no role in the policing of credit, so they're pure rent seekers; therefore, selling rents to rent seekers is the primary motive of Freddie Mac's business definitively.

Referring to mortgage back securies, Russ say, "The law of large numbers is such that it's going to be more predicable …"

The law of large numbers need not apply in this context at all and presumably does not apply. This point is crucial.

First, "Law of Large Numbers" technically doesn't refer to a statistical average (like the yield of a package of many mortgages); however, this usage apparently is common. Here is Wikipedia's page on the subject.

Techinically, Wikipedia doesn't describe the Law of Large Numbers at all. It describes a result involving a statistical average when a distribution has a well defined mean. This result is a consequence of the Law of Large Numbers, but it's not the Law of Large Numbers. At least, it's not what I learned to call "the Law of Large Numbers". The Law of Large Numbers does not involve a statistical average or assume a distribution with a well defined mean.

The Law of Large Numbers says that the proportion of outcomes with a particular characteristic approaches the probability of this characteristic, so for example, the proportion of heads approaches one half in a sequence of fair coin tosses. You can verify this usage of "Law of Large Numbers" by googling. Here's a page at Berkley for example.

This Law of Large Numbers (not the result described at Wikipedia) is always true for any probability distribution, because it's essentially axiomatic. It's true because of what we mean by "probability". As such, it's more of like a "law", i.e. it's true without exception.

The result described at Wikipedia is what Russ means by "Law of Large Numbers", but this result involves an assumption about the distribution of values, so it's not true in general. The Wikipedia article states this assumption when it says, "Given a random variable with a finite expected value …" "Expected value" is a property of a statistical distribution, but some distributions don't have a well defined (finite) expected value. A fat tailed distribution doesn't have a finite expected value.

This property of a distribution (no expected value) is essentially what "fat tailed distribution" means. In a fat tailed distribution, rare values contribute significantly to statistical samples, so that larger and larger sample averages don't converge to a well defined mean value. The standard example is Cauchy's distribution. You can google for it.

We typically study thin tailed distributions in elementary statistics, the standard example being the Gaussian (or Normal) distribution, but fat tailed distributions may be the rule rather than the exception in Economics. See the EconTalk with Nicholas Taleb.

The yield of a mortgage backed security essentially is an average of the yields of mortgages backing the security. If the distribution of the underlying yields is fat tailed, the yield of the security need not be more predictable than the yield of a single mortgage.

So why might the underlying distribution be fat tailed? Can we simply blame politicians encouraging subprime mortgages? I don't think so. The problems we're seeing with mortgage backed securities are not limited to these political influences or to these securities.

Similar problems exist with all CDOs and also with large corporations, since the yield of a corporation essentially is the average of yields of its factors of production. The underlying distribution of yields is fat tailed. Black Swans are everywhere.

A particular political influence is only one example. We can't point to one Black Swan and say that we've explained the problem. The next Black Swan may be red.

Kling said, "The creativity of mortgage bankers in delivering fraudulent loans is tremendous …"

Basically, that's an indictment of the "unregulated" market, but it's also a mistake to blame criminal "fraud", as opposed to legal "politics". The "fraud" is just another Black Swan.

Kling said, "I'm not sure what made investors willing to buy these securities …"

That's the right question. It's not about the sellers. It's about the buyers. We have too many buyers. When so many people seek rents, riskier lending is an inevitable outcome, because too many rent seekers exhaust the less risky lending.

And fundamentally we're exploring a fat tailed distribution of yields including many negative yields.

No political influence is required. So what if politicians persuade their cronies in a GSE to package many risky mortgages into still risky "securities"? If less risky securities exist with acceptable yields, who buys them?

Kling said, "Why not subsidize the downpayment?"

I guess he hasn't heard of the $7500 tax credit for "first time home buyers" enacted earlier this year. "First time" means that you haven't owned a house in three years.

http://www.federalhousingtaxcredit.com/

Of course, this credit is a pass-thru benefit for rent seekers and has little to do with helping home buyers. It's like the teaser rate on an ARM.

Martin Brock September 30, 2008 at 4:02 am

It was a great show, very thought provoking. Trust your audience to swim in the deeper waters with you.

Martin Brock September 30, 2008 at 7:54 am

Clarification: So what if politicians persuade their cronies in a GSE to package many risky mortgages into still risky "securities"? If less risky securities exist with acceptable yields, who buys the GSE's paper? We (our pension funds and other institutions) bought the GSE's paper, because we couldn't buy enough of anything else. Just look at the yield on ten year Treasuries. Can you retire on three and a half percent, with inflation at five percent?

Martin Brock September 30, 2008 at 7:56 am

Workers Per Retiree

Why aren't we discussing these facts?

Hammer September 30, 2008 at 9:38 am

TL, you are reading what you want to read, not what is actually written. The CRA specifically requires lendors to lend to minority groups in areas of questionable value, such as inner cities etc. Jacoby is pointing out "don't take that as minority (as the CRA specifies) but rather as people with poor credit history." The point is that banks have no problem lending to minorities with fine credit histories, despite what the CRA implies. It is people with poor credit history the CRA needs to compel lenders to do business with, regardless of race.

So really, you need to get over this oppression chip off your shoulder. Neither Don nor Russ is advocating anything so silly.

Sam Grove September 30, 2008 at 9:20 pm

Workers Per Retiree

Why aren't we discussing these facts?

Who's going to admit we need more immigration to bailout these entitlement programs?

Dennis Cardinale October 1, 2008 at 11:35 pm

If one bought a house with 0 down payment and the value of the house dropped 25% chances are that loan would become a forclosure- regardless of economic status of the borrower of the geopraphic location.
Especially if the decision to buy was to "flip" the property.
Require a substantial (20%) down payment the forclosure risk drops to nearly nill

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