The Statistical Truth Nonrandom Thoughts and Data 

by Matt Carlson

May 14, 2009
Why Did Economists Miss the Housing Bubble?

A big question historians will ponder for decades if not centuries is why so few economists saw the crisis coming. What happened is more or less well understood. The bursting of the housing bubble caused a wave of defaults and foreclosures, which caused values of mortgage-backed securities to plummet, which meant many financial institutions were suddenly undercapitalized, which caused a contraction of borrowing and lending (a credit crisis). Compounding the problem were debt-to-equity ratios of some financial institutions now deemed unacceptable and the fact that efforts to deleverage, i.e., sell assets to replenish banks’ balance sheets, caused asset prices to fall further (the paradox of deleveraging).

So cause and effect are relatively clear. What’s unclear is why so many economists missed signs of the crisis. To be fair, interactions in a complex network of variables are hard to predict. So perhaps few should have anticipated the adverse effects the bursting of the housing bubble would have on the balance sheets of too-big-to-fail banks. But most economists also missed what should have been the most obvious point of fragility in the system, the housing bubble. Indeed, most economists who considered the possibility of a housing bubble seem to have actually rejected the idea. How could this be?

First, let’s consider why anybody should have thought there was a housing bubble in the first place. People should have thought there was a bubble because of conventional indicators of bubbles. These were (1) house prices rising faster than inflation over an extended period, not a common occurrence, (2) house price-to-income ratios rising well above historical norms, and (3) house price-to-rent ratios rising well above historical norms. Here’s an illustration of indicator (1): the CPI versus the Case-Shiller index of house prices during the bubble years:

And since housing bubbles are local, we should see even more pronounced price surges in densely-populated, high-prestige regions (note the comparison to lower-density, lesser-prestige locales):

Similarly shaped curves are found in plots of price-to-income and price-to-rent ratios.

So there was a surge in house prices. The question was why. As many observed, rising prices don’t necessarily mean there’s a bubble. Prices could rise because of changes in “fundamentals,” i.e., changes in income, employment, interest rates, demographics, etc., all of which relate to the desirability and affordability of houses and so are reasons why people might rationally pay more (or less) for houses.

In a bubble, by contrast, people buy because they believe prices will continue to rise. So they may buy as an investment, expecting their wealth to grow as their home appreciates, or they may intend to “flip” their house when its price rises. Or they may be anxious that rising prices will make a home unaffordable if they wait, so they buy now. Since mortgage debt in such a situation is undertaken not on the basis of expected income, but of expectations of continually rising house prices, when house prices start to fall, as they must, people will be stuck with unsupportable debt. The result is a crash, the sort of thing we’ve seen in the last three years.

So why did economists miss the housing bubble? Reasons are multiple. They include an ideological predilection to believe markets are efficient and a general obliviousness of the subprime phenomenon. But more curious is that many economists who considered the possibility of a bubble actually rejected it.

Two papers, one by Jonathan McCarthy and Richard W. Peach (2004) and one by Charles Himmelberg, Christopher Mayer and Todd Sinai (2005)—both influential in convincing many economists there was no bubble—rejected conventional bubble indicators in favor of a different formula, the “user cost of housing.” The latter, they argued, in contrast to the conventional indicators, captures the total annual cost of owning a home. “The key mistake committed by the conventional measures of overheating in housing markets,” wrote Himmelberg, Mayer and Sinai, “is that they erroneously treat the purchase price of a house as if it were the same as the annual cost of owning.” McCarthy and Peach similarly criticized the conventional indicators (price-to-income and price-to-rent ratios) on the grounds that “neither measure takes interest rates into account.”

The user cost of housing, by contrast, includes not just the price of the house, but also less obvious costs and benefits of owning a home. These include the risk-free rate of interest (an opportunity cost, since it’s a return one could have earned had one invested in Treasury securities instead), property taxes, maintenance costs, a “risk premium” (i.e., a “cost” implicitly incurred in purchasing a house rather than renting because of the greater financial risk of home ownership), plus benefits like tax deductions (for mortgage interest and property taxes) and capital gains from the appreciation of home value. The formula is then

     P[irf + tP - tD(iM + tP) + M + RCG]                 (1)

where P is the price of the house, irf is the risk-free rate of interest, tP is the annual property tax rate, tD is the tax deduction rate (deducting for mortgage interest iM and property taxes tP), M is the fraction of home value spent on maintenance, R is the risk premium, and CG is capital gains (or losses) from appreciation (or depreciation) of the house. (Readers needn’t strain their eyes or their brains trying to understand this formula. It’s enough to know that “user cost” is an attempt to include everything that might affect the true “cost” of a house in one formula.)

Another expression for this formula is “imputed rent,” since it’s the effective cost of living in a property for one year. And in equilibrium the imputed rent should equal the actual rent R on comparable housing:

     RP[irf + tP - tD(iM + tP) + M + RCG]           (2)

Both groups of researchers found that in the early 2000s through 2004, in every major metropolitan area, the imputed rent was lower than the actual rent on comparable housing. This means that house prices, far from being too high, were too low!

How did the researchers explain the dramatic rise in nominal house prices? The formula can be rearranged to give the equilibrium price-to-rent ratio:

     P/R = 1/[irf + tP - tD(iM + tP) + M + RCG]       (3)

So in equilibrium the price-to-rent ratio would be the inverse of the user cost of housing And thus if, say, interest rates (irf) were to fall, the equilibrium price-to-rent ratio would rise. And this, these researchers argued, is what happened in the early 2000s. Low interest rates (and so also low mortgage rates and a lower opportunity cost of capital) made houses much more affordable during this period in terms of “user cost.” Homebuyer decisions were thus rational, based on affordability. No bubble.

But here’s the problem. The formula assumes fixed interest rates. And of course what precipitated the bursting of the housing bubble were resets, i.e., upward shifts in variable interest rates that made many subprime mortgages suddenly unaffordable. House prices then started falling. The rest is history.

Thus the user cost concept had an Achilles’ Heel. The more general problem, however, is that the user-cost formula is an attempt to include everything in one formula. The reason for its supposed superiority to conventional bubble indicators is that it represents the total cost of home ownership. But the resulting formula is brittle. If something should go wrong in the parameterization, e.g., that a basic feature of the subprime mortgage market (variable interest rates) was left out, the model would likely blow up. And that’s what happened.*

Had economists stuck with conventional indicators of bubbles—and to be fair, some, like Dean Baker, Robert Shiller, and Paul Krugman, did—the bubble would have been widely recognized for what it was. And concerted action against it—perhaps in the form of “a robust denunciation of speculators and speculation by someone in high authority,” as John Kenneth Galbraith suggested may have prevented the 1929 crash—might have been taken. But economists fell victim partly to the scientific pretensions of their discipline—which values sophisticated, seemingly precise, general formulae—and partly to an ideological predilection to regard markets as efficient. Most humiliating, however, is that economists, like the direct victims of the subprime meltdown, were snookered into believing that houses were more affordable than they were. The fact that interest rates on subprime mortgages were often variable rather than fixed wasn’t widely advertised and was even deliberately hidden. Economists should have been less enamored of the invisible hand of the market and more attentive to that of the subprime lenders who hid the true costs of housing.

*It should also be noted that both studies used biased data. Data for the studies came from the Office of Federal Housing Enterprise Oversight (OFHEO) index, which covers only houses with “conventional,” i.e., prime, mortgages purchased by Fannie Mae and Freddie Mac. The analyses were thus confined to houses purchased with low, fixed-rate mortgages of no more than $359,650. Also, condominiums were excluded. Obviously, if you’re considering only prime mortgages, not subprime or alt-A, etc., and excluding condominiums, which were a major problem in some locales, e.g., Miami, the real problem could be entirely missed.

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