FRBSF Economic Letter
2006-15; June 30, 2006
Residential Investment over the Real Estate Cycle
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Much attention recently has been given to the possibility of
a slowdown in the U.S. residential real estate market. While
real residential investment has continued to grow and existing
house prices have held up through the first quarter of 2006,
analysts have pointed to other signs of slowing. Two commonly
cited indicators are an apparent slowing of sales of new and existing homes
and a buildup of inventories of new homes in many markets. In this Economic
Letter, I characterize past episodes of residential investment downturns
and evaluate how specific housing market variables, such as sales volumes and
inventories, perform as predictors of downturns.
Measuring real estate market activity
 The main indicator of the quantity of new housing supplied to
the economy is the residential fixed investment series from the
national income and product accounts. Residential investment
is made up of new construction put in place, expenditures on
maintenance and home improvement, equipment purchased for use
in residential structures (e.g., washers and dryers purchased
by landlords and rented out to tenants), and brokerage commissions.
Over the past 25 years residential investment has accounted for
approximately 30% of gross private investment and approximately
5% of total domestic output. As a share of total investment,
residential investment has been in decline since the 1960s, mainly
due to the surge in investment in business equipment and software
starting around that same time. As a share of total output, however,
residential investment is currently at its highest share since
the mid-1980s: In 2006:Q1, real residential investment grew by
3.1%, contributing about two-tenths of a percentage point to
real GDP growth.
Residential investment is a highly volatile component of GDP.
Yet as shown in Figure 1, the volatility has decreased markedly
in recent years. Indeed, this series is one of the most frequently
cited pieces of evidence when describing the overall decline
in macroeconomic volatility (see Dynan, Elmendorf, and Sichel
(2006) and Peek and Wilcox (2006)). Before the mid-1980s, residential
investment was characterized by periods of extreme boom and then
bust. The response of residential investment to the strong economy
and robust house price appreciation since 1996 has been much
more gradual, by comparison.
 If we characterize an investment slowdown as two consecutive
quarters of declining real spending, there have been eight downturns
since 1976. The shaded recession bars in Figure 1 indicate that
when the overall economy tips into recession, invariably residential
investment turns down as well; however, the timing of these downturns
does not always track the recession dates perfectly, and some
downturns even occur during overall economic expansions. This
leads to a natural classification of residential investment downturns. Recession-related downturns
last an average of seven quarters and are characterized by large
declines in investment; on average, real residential investment
falls by about 50% from the previous peak (see Figure 2). These
averages are strongly influenced by the downturns occurring before
the 1980s, when the depth and duration of recessions were also
severe. On the other hand, non-recession-related downturns
are relatively shorter, lasting an average of two to three quarters,
and relatively milder, resulting in an average dip in investment
of roughly 10%.
Forecasting residential investment downturns
Residential investment should be thought of as the quantity
of new housing supplied to the economy, and, in the long run,
it should satisfy the overall demand for new housing. Thus, residential
investment depends on supply factors, such as construction materials
costs, as well as demand factors, such as demographics, interest
rates (or the cost of capital), prices, and the stock of household
wealth. These demand-side factors are particularly important
in helping to explain why residential downturns tend to accompany
economic downturns. In this spirit, a standard macro model of
residential investment will typically posit that investment depends
on variables like aggregate consumption, interest rates, and
prices (see Brayton and Tinsley (1996)). Notably absent from
this specification are the variables most cited in the press
as evidence of a slowing housing market: sales volumes and growing
inventories.
At any point in time, however, the new supply brought to market
may not exactly equal the amount of new housing demanded. In
particular, negative shocks to demand can result in there being
too much supply on the market. If these changes in demand are
not expected to be transitory, then developers will slow the
pace of new construction and a downturn will occur. To forecast
these turning points, we need to know what variables developers
use to learn about changes in demand. It is possible that variables
that do not enter into the model sketched out above, such as
sales volumes and inventory levels, are related to the information
that developers use to make, or alter, their plans.
In this type of framework, variables that speak to selling conditions
for finished projects seem to be fairly useful in predicting
downturns; for example, sales volumes dip one quarter before
the average downturn in investment. For recession-related downturns,
sales drop very quickly (by about 10%) once the downturn has
started. For non-recession-related downturns, however, there
is no clear signal, on average, from sales volumes data either
before or during the downturn.
 The so-called "month's supply of housing" ratio, or
the number of new housing units for sale in a given month divided
by the number of new units sold, is also fairly useful for predicting
investment downturns. For recession-related downturns, the ratio
(shown in Figure 3) starts to rise on average six quarters before
the actual downturn, and continues to rise for six quarters into
the downturn. For the average non-recession-related downturn,
the inventory ratio turns up just one quarter before the downturn
and then eases back down after two quarters (which is also the
average duration of a non-recession-related downturn).
This exercise indicates that prices seem to be considerably
less useful predictors of downturns than quantity-type measures.
This might seem surprising because, unlike sales volumes and
inventories, prices have a forward-looking aspect and thus
would seem to be good predictors of the future state of the housing
market. Figure 4 shows the average behavior of real new house
prices leading up to and then following a peak in residential
investment. The focus here is on new house prices because,
presumably, they, rather than existing house prices, are most
relevant for real estate developers' decisionmaking. Additionally,
new house prices are likely to be more sensitive to market weakness
than existing house prices. Developers are always "motivated
sellers." If demand is soft, they generally do not have
the option of withdrawing the house from the market and simply
living in it. For recession-related downturns, the real price
of new houses declines about four quarters after the peak,
on average. Real new house prices register no detectable declines
surrounding the average non-recession-related downturn. This
basic stylized fact is even more apparent when using prices
of existing homes. Only in the severest downturns do we witness
real price declines, and never do these price declines come
in advance of a downturn in investment.
 One caveat to this analysis is that it is based on the comparison
of the average behavior of a housing market series leading up
to two different types of downturns in residential investment.
Obviously, averaging in the figures masks a fair degree of variation
across the different downturns. However, more formal statistical
modeling supports the notion that variables such as sales volumes
and inventory ratios yield earlier and more reliable signals
when the downturn is recession-related. This is natural; recession-related
downturns have tended to be more severe than the non-recession-related
episodes.
It is also interesting to note that the recent behavior of the
month's supply ratio bears more resemblance to the typical behavior
before a recession-related downturn than to a non-recession-related
downturn. Yet economists, such as those sampled in surveys of
professional forecasters, are generally predicting only a moderation
in overall economic growth in coming quarters. Given these conflicting
observations, it is natural to wonder how much stand-alone information
for predicting residential investment is contained in the housing
market data. The answer, based on the last 30 years of data is
mixed. If we estimate a model of the event that a residential
downturn occurs using lagged values of the housing market variables
mentioned above, we can generally improve the model prediction
error by adding in forecasts of output growth. This suggests
that it is best to consider economy-wide factors in addition
to specific housing market variables when evaluating the real
estate market.
Conclusion
Housing market statistics, such as sales volumes and months
of supply on the market, can provide some useful information
about turning points for residential investment. Much of this
early warning, however, comes in advance of severe, recession-related
downturns. Before non-recession-related downturns, which are
typically relatively shorter and milder, these variables are
less reliable. The analysis suggests that incoming information
from the housing market should be evaluated in the context of
the overall economy's performance. To the extent that forecasts
for solid output and employment growth are realized, this would
not preclude slower growth in residential investment, but it
should provide support for the real estate market and residential
investment.
John Krainer
Economist
References
[URLs accessed June 2006.]
Brayton, F., and P. Tinsley, eds. 1996. "A
Guide to FRB/US: A Macroeconomic Model of the United States." Federal
Reserve Board Finance and Economics Discussion Series.
Dynan, K., D. Elmendorf, and D. Sichel. 2006. "Can Financial
Innovation Help to Explain the Reduced Volatility of Economic
Activity?" Journal of Monetary Economics 53(1),
pp. 123-150.
Peek, J., and J. Wilcox. 2006. "Housing, Credit Constraints,
and Macro Stability: The Secondary Mortgage Market and Reduced
Cyclicality of Residential Investment." American Economic
Review 96(2) (May), pp. 135-140.
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do not necessarily reflect the views of the management
of the Federal Reserve Bank of San Francisco or of the
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