Metro-Area Differences in House Price Indexes
Home price indexes have been providing homeowners with nothing but bad news for the better part of two years now. On the last Tuesday of every month, when the monthly S&P/Case-Shiller housing price indexes are released, newspapers fill up with dour headlines about another new record drop in home prices. While these headlines may be factually correct, it’s important to realize that the numbers being quoted are almost always the composite figures. Since real estate markets are local, national or composite figures should have only limited meaning to homeowners concerned about their home’s value.
As the picture below shows, home price appreciation patterns vary tremendously by metro area. Cities like Miami, Los Angeles, San Diego, and Washington, D.C. all saw tremendous growth in home prices during the boom and have all subsequently seen massive declines in values. On the other hand, cities like Denver and Charlotte saw little to no unusual home price appreciation during the boom and have seen home prices decline only modestly during the bust. For simplicity’s sake, the 20 metro areas that the S&P/Case–Shiller indexes measure can be arranged into three groups of similar appreciation rates: high–appreciation cities, mid–appreciation cities and low–appreciation cities.
These aggregates are not weighted in any way, so what they are actually showing is the average index value in the cities included. This information, while still an aggregate measure, is potentially more useful to homeowners living in a city that is not directly measured by the indexes. These measures show pretty clearly that the size of the decline in home prices in a given metro area is directly related to the size of the run up in prices during the boom.
Another factor that the aggregate home price indexes tend to hide is that not all homes in a metro area experience the same price patterns. Homes in different price ranges have different demand and supply curves and, as a result, appreciate and depreciate in different ways. A significant portion of the housing boom was driven by a loosening in lending standards, which one might expect to disproportionately affect lower–priced homes. When credit standards loosen, a whole new group of people who previously were unable to afford homes are suddenly capable of buying a home. The majority of the people in this group are naturally going to demand lower-priced homes. All else equal, the increase in demand is going to push prices for these types of homes upward. Mid– and high–priced homes are affected by these developments, too. More readily available credit may mean that a person previously able to afford only a low-priced home can now afford a mid–priced home. In addition, the increase in home prices creates positive feedback such that people who already owned homes are now able to sell their homes at higher prices and buy a more expensive home.
Again creating some unweighted aggregates gives a better view of how homes in specific price tiers have changed in value. S&P breaks the Case–Shiller metro area indexes down into price tiers. Each price tier is unique to a specific area, meaning that the maximum value of low-tier homes in Cleveland is different than that of low–tier homes in Miami. Each tier in each metro area represents one–third of the sales in a given period that are used to formulate an area’s overall index. The averages shown below ignore the differences in price level between metro areas and instead show the average index value of the respective price tiers across metros. The least expensive third of homes clearly has the largest appreciation and subsequent depreciation in value, while the most expensive third of homes has seen the smallest run up and decline in home prices. This pattern holds true in all but two of the 17 metro areas that the index breaks down into tiers.
What does all this mean to homeowners wondering what their home is worth? Not as much they might like. Ultimately, the value of a home is what a buyer is willing to pay for it, and that is determined by the individual characteristics of a home as well as many economic factors. But in the absence of a pending offer, these different breakdowns of the data provide some insight into how home prices in different areas and different price tiers have behaved on average. Given the data, it seems safe to assume that those homes that experienced the largest price increases during the boom have likely given a great deal, if not all of that gain back. Homes whose prices held pretty steady during the good times likely have experienced only modest declines to date.