Real Estate: Where Do We Live, Part Two
The national debate regarding real estate bubbles continues. While the counties in Wisconsin on the Illinois Stateline are not in the forefront of this debate, families and individual express interest in the impact the growing real estate prices have on their wealth. The question of rising real estate prices centers around the fundamental ideas of Economics 101: the determinants of supply and demand.
It could be argued that rising prices are a reflection of stagnant supply. This, however, is clearly not accurate. As has been seen throughout the county and the region, the supply of new housing continues to grow. The second question would be: is the market competitive, or are their non-competitive forces in play. This is a question worth examining.
The consideration of perfect competition opens with the idea that there exist many buyers and sellers. This appears to be the case in real estate. It also requires perfect information. While information may not be perfect, it is reasonable to expect that information regarding comparative values and the benefits offered to the consumer is reasonably accessible. The third determinant of the competitive market requires that there is easy entry and exit of firms from the market. While some markets and areas are less open than others, it is not unreasonable to believe that a new builder can enter the market and build homes.
The final requirement of perfect competition is the challenging notion: the anticipation that housing is a homogeneous product. It is here where we can argue that real estate is actually a segmented market in terms are geography (lake homes are more valuable than city homes). It is also segmented in terms of the hedonic characteristics of a home (numbers and quality of bathrooms differ). These segmented markets may explain some of the dramatic appreciation of homes. For example, it is possible that brick homes with four bathrooms on a lake appreciated more than city homes and thus brought up the average of all homes in the region. It is possible that some of the aggregate price appreciation is the result of some types of homes raising the price of the average.
In regards to the supply demand analysis, it is difficult to argue that the supply of housing is not growing. The more accurate question is, does the supply of housing grow faster than the demand? While the housing stock is growing, it is possible that the supply is not increases as fast as demand. Since an initial determinant of a change in demand (for housing) is population, we would expect that the demand curve for housing would shift. This shift would cause a price increase. A second cause for a price increase would be income. Since housing is a normal good (as we earn more money, we buy more housing), we would expect that housing prices would rise during an economic expansion.
The other two determinants of demand, taste and consumer expectations, may contribute to a bubble. If expectations lead to a philosophy that price is irrelevant due to anticipated appreciation, there may be inertia to price increases. The second bubble determinant may be taste. In a fashion, this may be related to the segmented market: some homes face greater potential for appreciation than others due to the segmented demand. As a result, these houses (more in fashion or taste) may be rising faster than others, thus raising the average price level.
The primary culprit of the increase in housing prices comes from the growing population in both the United States and the state of Wisconsin. Returning to the previous issue of the Stateline Economic Report, the theory would be that if the population increased by 100 persons and the average density for each new home was 3 persons, the community would need to build 33 homes. It is here where the argument of a bubble can be challenged. Couple with the heterogeneous nature of housing (houses differ significantly from each other), it is possible that through data aggregation, we are finding that certain types of houses are growing quite a bit faster than others. For example, if we look at Walworth County, it is possible that the appreciation of unique real estate on waterfront properties is causing a distortion in the average price of all real estate in Walworth County.
A second factor is a continuing increase in homeownership in Wisconsin. According to the United States Census Bureau, homeownership rates in Wisconsin have risen from 66.7% of householders in 1990 to 68.4% in 2000 to 72.9% in 2003. Apart from the simple growth in population, there has been a shift in the demand for owner-occupied housing.
The result is a need for organic growth in the real estate market. If housing were to grow at a rate lower than the population growth, prices would rise more quickly due to the shortage. The issue of segmented markets also argues that certain types of houses (some of which offer highly desirable and non homogeneous qualities) rise faster than others. A housing bubble argument that remains is that low interest rates fueled the bubble, and that rising rates will pop the bubble.
This theory is predicated on the idea that high interest rates will force leveraged, adjustable interest rate homeowners to flood the market with houses once their payments begin to rise. However, this ignores the fact that 35% of all homeowners own their home free and clear. In addition, another 51% have fixed rate mortgages (National Association of Realtors). As a result, rising rates will not affect their ability to make payments on their current homes. While it may affect the ability of new buyers to afford a home, this is not necessarily accurate.
According to the fact that the United States requires new homes to house our growing adult population, rising rates may force builders to build smaller and less expensive homes. Data from the 2000 census showed a rather interesting fact: As population growth soared, housing production dropped. During the 1990s, U.S. population grew by 32.7 million people. That figure is 10 million more than growth in the 1980s, and exceeds the total national population before the Civil War. Population expanded by 13.2 percent in the 1990s, the biggest gain since the 1960s' 13.4 percent growth and way ahead of the 1980s' 9.8 percent growth.
By contrast, new housing slipped during the 1990s, compared with the 1970s and 1980s. “New housing in the 1990s totaled 13.3 million units. During the 1970s, when the nation added just 23.2 million people, more than 17 million new housing units were added. In the 1980s, housing grew by 14.8 million units. Thus, the two decades just prior to the 1990s had much slower population gains but registered significantly more new housing units.” (From the Fannie Mae Foundation: Is the United States Undersupplying Housing? By Robert E. Lang). While other demographic influences (such as the emergence of the baby boomers) led to increases in housing in the 1970’s, this is a consideration regarding the supply of housing.
It is possible that there will be some retrenchment in the prices of houses to compensate for the higher interest rates. However, the fears of panic selling (a contributor to the collapse of any bubble) are extreme. Since homes serve a practical function as a place to live, as well as a speculative function as an investment, the practical function differentiates that product from non functional investments. The question that exists along the Stateline is: how much has housing growth outstripped population growth and the rise in owner-occupied housing?
The initial measure in this bubble debate, home sales prices, has witnessed robust appreciation. Walworth County leads the region in overall valuation. The average purchase price of a home in Walworth County in the first two quarters of 2005 rose by 9.68% to $179,100 (see Figure H1). Overall the sales prices in Walworth County have risen by 56% between 1997 and 2005. While sales prices in Green County have appreciated faster, 71% over this period, the base value of these properties was considerably lower.
Rock County's real estate continues their steady level of price appreciation, while Jefferson County's appreciation slowed a bit during the first two quarters of 2005. This could be due to the lack of unique amenities offered in these counties. Whereas Walworth County may witness an aggregate increase in real estate that is pumped up by lake homes, the real estate in Jefferson and Rock Counties are more comparable and homogeneous. As a result they may be gravitating towards an equilibrium price. This would imply that Rock County's prices will continue to rise as their homes serve as an alternative to Jefferson County's.
This sense of substitution is not as prevalent in Green and Lafayette Counties. While Rock and Jefferson have extensive borders and transportation routes with Dane County, Green and Lafayette are more remote. This, as well as the lack of growth through population induced demand, may explain their less expensive housing. One additional explanation may be the differences in housing stock between the five counties. The aggregation of sales figures does not provide insight into the hedonic variables that contribute to the demander’s willingness to pay.
In terms of population growth and housing permits, it appears that housing permits (see Figure H2) continue to vastly outpace the estimated population growth. In the five communities examined, every one saw an increase in housing stock that outpaces the population growth. This calculation considered that most of these communities have household density of 2.3 persons per unit. While this is an important issue to consider, it does not take into account three important issues. The first is abandonment and destruction which is not measured in the current data. The second is the fact that these five counties all have housing densities that exceed the state of Wisconsin as a whole. If the occupancy density simply resembles the rest of Wisconsin, this estimate of oversupply will decline by over 16%. Finally, it ignores the dramatic rise in homeownership rates that produced new buyers into the market that did not exist in the recent past.
