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Stephan Whitaker |

Research Economist

Stephan Whitaker

Stephan Whitaker is a research economist in the Research Department at the Federal Reserve Bank of Cleveland. His current work includes research on housing markets and studies of state and local public finance.

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01.19.2012

Economic Trends

Trends in Housing Prices per Square Foot

Stephan Whitaker

To attract job candidates and firms to a region like the Fourth District, recruiters routinely point out the affordability of living in their area, especially the cost of housing. The pitch that “you can get more house for your dollar here,” is aimed especially at growing families with mid-range incomes.

The large coastal metros have long had housing costs above those of inland cities. In 1997, the median price per square foot for a home in the San Francisco area was $158 and the figure for Boston was $104. That same year, homes sold at $76 per square foot in Columbus and $56 in Pittsburgh. These regional price differences widened over the next 10 years until a family’s housing budget in San Francisco bought them only a quarter of the square footage that it could buy in Columbus. Rapid appreciation took housing prices in the other “sand states” (Florida, Arizona, Nevada) up over 50 percent above those in the Fourth District.

Where are these trends heading in the wake of the housing bust? The states and metro areas of the Fourth District still enjoy an advantage over places like San Francisco and New York on a price-per-square-foot basis. However, the post-boom prices in formerly expensive cities like Tampa and Las Vegas are now below those of Columbus and Cleveland.

While median sale prices are the most commonly cited measure of housing costs, prices usually are not adjusted for differences in the housing stocks between regions. The median house sold on Long Island will be much smaller (and older, with fewer amenities) than the median home sold near Phoenix, even if their sale prices are similar. As a first step toward seeing how far a housing dollar goes in an area, one can look at the median price per square foot. Looking at trends in this measure also reveals if residential properties are maintaining their value, and if housing demand is high enough to support a normal level of construction activity. Both questions are important for economic growth prospects in a region.

The median sale price per square foot is charted below for the states of the Fourth District and the nation. The decline from the high of the housing market is clearly visible in the national trend. In the middle of the last decade, the Fourth District was not greatly affected by the run-up in housing prices, and therefore it enjoyed a competitive advantage on this measure. However, as prices have come down nationally, Pennsylvania is now just at the national average. Housing in Ohio is becoming more affordable. This may be good for attracting new residents from outside the state, but it is not good for the Ohio homeowners losing equity. West Virginia’s housing costs have remained among the most affordable in the nation on a per-square-foot basis.

Housing prices vary with the season, with higher prices during the spring and summer months, when more buyers are in the market. It is difficult to see past this seasonality at the metro level, so it helps to look at 12-month moving averages. The national figure’s recent lows are still above $105 per square foot, and the Fourth District metro area with the highest median, Columbus, is below that level. Prices per square foot are trending down in all the metro areas except Pittsburgh. Canton, Dayton, and Toledo all offer very affordable housing. Residential space in these areas costs around $30 less than the national median.

Where the Fourth District metro areas stand relative to other metro areas has changed since the height of the housing boom in 2006. The median cost of housing, on a per-square-foot basis, was more than twice as high in the expensive coastal metro areas in 2006 as in the Fourth District. The gap has narrowed considerably in the last five years. The Fourth District metro areas are on par with cities such as Atlanta, Charlotte, and Oklahoma City. Several boomtown metro areas, such as Phoenix, Orlando, and Tampa, had significantly higher costs per square foot in 2006. These markets now have inventories of new large homes coming out of foreclosure, which has lowered their price per square foot below that of Cleveland and Akron.

One of greatest economic challenges to come out of the recent recession was the dramatic decline in residential construction activity. Under normal conditions, residential construction is a substantial employer and a contributor to the gross regional product. But if existing homes are selling for low prices, it will be more difficult for builders to market new homes.

To shed some light on the relative costs of new and existing homes, we plot the costs for both against each other in the chart below. If the square footage of existing homes and new homes is similarly priced in a region, then it will show up near the red dashed line. In these areas, new construction should be able to compete with existing homes, especially because home buyers will pay extra for the latest amenities, greater efficiency, lower maintenance, and exclusive locations that new homes can provide. In Dayton, Canton, Toledo, and Cleveland, new construction may have difficulty competing with low-priced existing homes. Likewise, residential space is inexpensive relative to new construction in Phoenix, Orlando, and Tampa. New construction should be able to continue at a normal pace in Columbus and Pittsburgh.

The data we have used here have some limitations. The median price-per-square-foot (like the median price) can be pulled down by unusually frequent turnover of low-value properties. The flipping of foreclosed homes may have a strong influence on recent data in weak housing markets. Also, estimates are not available for all regions. Data are not available for the Cincinnati and Lexington metro areas and the last three months of West Virginia’s series.