Economists differ on how to value housing

One of the main reasons that I think economists can't seem to agree on how to value the appropriate price for housing is because they tend to take a 30,000-foot view, sort of what you might see when flying over an area. Then, taking out their magic pencils, they wave it over the area and proclaim that prices must fall by a certain amount in order to revert to a long-term relationship between prices and median incomes, or prices versus potential rents, or prices versus changes in interest rates.

Of course real estate agents will tell you that since real estate is local that the 30,000-foot view is inherently flawed, thus giving us one more reason that no one can seem to agree on a home's value -- other than comps, of course, which of course only tell you what a home in the same area recently sold for and may or may not have anything to do with your house.

So what's a home buyer or home seller to do? Fortunately, a story in the New York Times (hat tip: Patrick.net) lays out the various metrics economists use to value real estate markets and the pros and cons of each:

The New York Times asked economists across the country to share the data they use to figure out how much houses in regional markets are overvalued, a calculation that approximates where the bottom may be. Models built on these variables show that while some markets — such as California — are on a road to recovery, others — such as south Florida — have a way to go.

These signs cannot possibly tell the whole story, especially since they point more toward where prices should be valued than where they will be. But these measures are nonetheless helpful to anyone buying, selling or borrowing against their home sweet home...

One way to envision the bottom would be to look back at where prices were five or 10 years ago, before the current price run-up. There are some better ways, though.

Noting that home prices have outpaced inflation in the past, one can calculate how much houses appreciated annually in the decades before the bubble, and then figure out how far out of line prices are now. Edward E. Leamer, director of the U.C.L.A. Anderson Forecast, has crunched these numbers for various regional markets.

In Ocean City, N.J., for example, inflation-adjusted house prices rose about 1.6 percent a year from 1988 through 2002. Compared with what this rate would predict, the city’s houses in the first quarter of this year were overvalued by 51 percent. Over the previous year, they had fallen 0.6 percent; at this pace, Ocean City house prices will be at the right level in about 13 years. The model foretells eternal decline for some cities. It predicts that Kingston, N.Y., will not return to “normal” for almost four centuries.

So that's not very helpful, is it?

Many experts look to price-to-rent ratios to estimate where house prices should be in a region. Because renting is a direct alternative to buying, and because rents tend to be less volatile than prices, rents are often considered to be a good shorthand for figuring out the intrinsic value of a home.

In the past decade, the price-to-rent ratio in many markets has exploded, indicating that people have been paying much more for their homes than the property is actually worth. From 1994 to 2002, for example, Phoenix had an average ratio of 11, according to data from Moody’s Economy.com. After peaking in the last quarter of 2002 at 22.5, it cooled to about 17.3 in the first quarter of this year.

This measure is popular but problematic because some economists say many of the homes that people rent (apartments in multifamily buildings) may not be comparable to the types of homes that people buy (single-family houses).

This is why looking at the local market is key -- that way you'd have a much better chance of finding a comparable property for rent. Any economist who would compare the cost of renting an apartment with the cost of owning a single-family home to argue for lower home prices should give back his PhD.

Another ratio that housing economists watch is the ratio of home prices to per-capita income. This is telling because it shows whether Americans can actually afford the houses in their area.

Looking at previous peaks and troughs in the income ratio can provide an idea of where the housing market will bottom in a particular city. In Boston, for example, the housing market peaked in the late 1980s around 11, and then hovered around 7.5 when it bottomed in the late 1990s, according to Mr. Case. This time around, it peaked at over 12, and in the first quarter of this year, it was just over 10...

Some economists argue that the price to per-capita income ratio is misleading, because the price used in that model does not take into account the full cost for buyers. This full cost should include not just the price of the house but mortgage rates as well.

“As long as anyone can remember, as long as we have data, mortgage rates have been about 1.6 percent above the 10-year Treasury rate,” said Christopher J. Mayer, an economist and senior vice dean at Columbia Business School. “Today, it’s more like 2.5 percent above the 10-year Treasury. That’s a gigantic difference, literally reducing the amount of house someone could afford by 20 percent.”

He has put together, in a model that has not yet been published, a rough calculation of where house prices should be if mortgage markets were functioning the way they had been in the last few decades.

This model shows that big-bubble cities like Miami and Phoenix were still overvalued in the range of 13 percent in May. It also found that San Francisco and Boston homes were corrected to the right level, and that homes were actually undervalued in New York by 5 percent.

Still, Mr. Mayer says prices in these cities will probably continue to fall because of deteriorating mortgage markets and economic fundamentals.

Yet another ratio worth watching is the relationship of housing inventory to sales. This measures the imbalance between supply and demand, which is the economist’s holy grail of market behavior.

A recent International Monetary Fund paper argued this measure was the strongest determinant of housing prices in the short run. Booming areas were often overbuilt and have the most inventory to clear out before prices can recover. Inventory-to-sales ratio declines across California, for example, have given hope that the state is nearing recovery...

The wrench in all these models is that this is the first national housing bust since anybody started keeping track of many of these useful data points. It is hard to predict how the national trends will affect state and city housing markets, which are otherwise very local organisms...

...some experts argued that it was silly to try to build a mathematical model for the market’s overvaluation. Too much is unknown, they say, to make any predictions.