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Understanding Economic Data: New-Home Construction

Every day, new information comes along to help investors make financial decisions. And as previous articles in this ongoing "Understanding Economic Data" series have discussed, releases of economic data on topics such as the U.S. current account and the Producer Price Index not only affect the financial markets those investors are involved in but also provide keys to understanding the overall economy. Today, we'll take a look at economic data as it relates to the housing industry. We'll help you understand how the numbers are calculated and what they mean to the economy.

With the boom in the real estate market over the past several years, the health of the economy has become increasingly dependent on business activity related to housing. Conversely, homebuilders such as Pulte (NYSE: PHM  ) , Toll Brothers (NYSE: TOL  ) , and Centex (NYSE: CTX  ) rely on a healthy housing market to sell their products. However, the reach of the housing industry extends well beyond just the builders. Suppliers such as Home Depot (NYSE: HD  ) and Lowe's (NYSE: LOW  ) depend on homeowners seeking to make improvements to their property. Mortgage brokers such as ABN Amro (NYSE: ABN  ) and the E-Loan subsidiary Popular count on a constant flow of homebuyers who need financing to buy the houses they want. And construction-materials producers such as USG and International Paper (NYSE: IP  ) derive a substantial amount of their business from homebuilders. In addition to these large companies, a huge number of small businesses provide housing-related services, too, such as plumbing, heating, landscaping, and painting.

The basic concept
To track the health of the housing market, the Census Bureau provides monthly statistics about new-home construction. Yesterday's release (link opens a PDF), which showed falling numbers in all three of the categories that the bureau tracks, supports the view that a slowdown in the housing sector is under way.

Let's look at those three categories. First, the bureau contacts government agencies to find out how many permits have been issued allowing construction of new homes. Second, Census field representatives look at public information and building sites to determine the number of homes that began construction, also known as the number of housing starts. And third, data is collected on how many new homes were finished being constructed.

These three categories have an obvious relationship. Changes in the number of building permits in a given month will usually have an impact on housing starts soon thereafter and will affect housing completions after a few months. Census Bureau figures show that the average lag between issuance of a permit and beginning of construction is about a month, and the average time to complete a single-family residence is about six months.

Because home-construction activity varies greatly from season to season, housing data is seasonally adjusted. Construction generally has its strongest period in the spring and summer and then slows down in the fall and winter months. Although seasonal adjustments help to make month-to-month comparisons more accurate, even the Census Bureau itself warns against drawing strong conclusions from changes between months; it argues that one needs four to six months of data before one can establish a trend over time.

One way to lessen the impact of seasonal adjustment is to compare a given month's numbers with the same month in previous years. However, even using year-to-year comparisons cannot fully account for important differences that may have a substantial impact on the numbers, such as weather.

What's more, the work the Census Bureau performs does not involve contacting every single agency issuing permits or counting every single worksite. Instead, the Census Bureau uses statistical sampling to draw a representative group of permit issuers and worksites and then draws conclusions from analyzing the sample. Although this is necessary to keep the cost and scope of the work manageable, the conclusions drawn from such data are susceptible to statistical error.

In looking at the August report, for example, housing completions are listed as having fallen 3.2% from July and 4.4% from August 2005. However, the report then gives statistical confidence levels of 10.4% and 7.4%, respectively. This means that while the month-to-month decline actually seen in the sampled data was 3.2%, the true overall number likely lies between a decline of 13.6% and an increase of 7.2%. This is an example of a challenge that all statisticians face: collecting enough data to draw firm conclusions while remaining within the confines of the limited resources available to them.

Economic implications of new-housing data
Since hitting highs in late 2005 and early 2006, all three categories of housing data have shown pronounced drops. Building permits hit a high in September 2005 and have dropped by nearly a quarter since then. Housing starts peaked in January and are down by more than a quarter. Housing completions reached their high in March and have fallen by about 15%. It's evident that homebuilders are adjusting their new-construction plans in response to, or in anticipation of, decreasing demand.

It's important to understand, however, that a drop in the number of new homes built does not necessarily mean that housing prices will fall. Choosing to reduce supply is a natural and economically appropriate response to the threat of decreasing demand for housing and should theoretically act as a balance against falling prices. The important question is whether the boom in new-home construction over the past several years has built up inventories to the point of creating a glut of houses on the market, a situation that would cause prices to fall. The Census Bureau's new-home-construction data gives part of the picture, but to draw overall conclusions, you need to have additional information, including data on sales prices and on already existing homes on the market.

In summary, the housing industry makes a major contribution to the overall economy. By looking at data on new-home construction, you can learn how homebuilders are reacting to changing conditions in the real estate market and draw valuable conclusions that can assist you in making your own decisions about housing.

For further Foolishness:

The Motley Fool has great resources about all aspects of buying and owning a home in its Home Center. Take a look and get some great tips you can use to save money.

Home Depot is a Motley Fool Inside Value recommendation.

Fool contributor Dan Caplinger has been waiting for a real estate crash for a long time now, but he doesn't hold positions in any of the companies mentioned in this article. The Fool's disclosure policy will never leave you without shelter.


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  • Report this Comment On September 02, 2008, at 2:06 PM, ilyabro wrote:

    I am not sure I undestand how the author is explaining the concept of statistical significance here. It seems that he is adding subtracting the 10% significance to/from the 3% mean to get to the range (at least that's how I'm reading - am i wrong?).

    Furthermore, usually a confidence interval is mentioned, at a certain level of statistical significance. Since there is no interval, only a point estimate, then I'm guessing that 10% is the p-value, i.e. probability that the mean is actually zero (if that's the null hypothesis).

    let me know if you agree.

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Dan Caplinger
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Dan Caplinger has been a contract writer for the Motley Fool since 2006. As the Fool's Director of Investment Planning, Dan oversees much of the personal-finance and investment-planning content published daily on Fool.com. With a background as an estate-planning attorney and independent financial consultant, Dan's articles are based on more than 20 years of experience from all angles of the financial world.

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