The supply or level of production and provision of housing is shaped by a number of factors. When considering whether to invest in new or renovated housing, developers weigh the risks and costs of an investment against its potential return. The macroeconomic environment and the security of property rights play a major role in determining the risks of an investment, as the availability and affordability of serviced land, land use regulation and construction costs set production costs. Housing will be supplied only when these costs and risks are exceeded by its anticipated market price. These factors determine not only the quantity of housing supplied, but where and for whom it is built.[1]
That supply, not just demand, is critical to understanding housing markets is self-evident to economists. High prices always reflect the intersection of strong demand and limited supply. If demand in a market is weak, prices cannot be high, no matter what the supply. And, if supply is unrestricted, then prices cannot rise much above production costs, no matter what the demand. That supply-side conditions actually matter in practice is clear from the strong negative correlation between housing permits and the level of house prices within a market.[2] The highest price markets tend to have the least permitting.
[1] See Bertaud (1988) on this relationship and Bertaud (2004) for some of its implications.
[2] See Figure 2-11 in Glaeser and Gyourko (2008) for a graph of this relationship.
There long has been an imbalance in what we know about the demand side versus the supply side of housing markets, with our understanding of housing demand being much greater. Partly, this has been driven by policy interests, although data availability has played a big role, too. Fortunately, this knowledge gap has begun to narrow in recent years, allowing for a much better understanding of housing markets in general.
Theory and the data indicate that the supply side of housing markets mediates urban growth and decline. Whether housing supply is elastic or inelastic plays a huge role in defining what urban success looks like.[1] If supply is elastic, then strong demand shows up in growing populations amid much home building. If supply is inelastic, population growth is relatively low and very few net new housing units are built. Growing demand is then reflected in high land prices in this version of urban success. This may have important social and economic implications that clearly are worthy of further study. Effectively restricting entry into the most productive urban agglomerations by not allowing much housing production necessarily pushes growth to other markets that may not be as productive.[2] To the extent that binding local land use controls raise house prices, financial constraints also exacerbate spatial sorting along income lines.
Restrictive supply also helps define the nature of urban decline. The durable nature of housing, combined with the fact that the supply schedule is inelastic when demand falls below fundamental production costs, largely accounts for the fact that urban decline is so long and steady in nature.[3] The negative demand shocks experienced by markets such as Detroit lead to very low house prices that discourage people from selling their homes. The very durability of housing makes population loss a very slow process. Cheap housing is relatively more attractive to the poor, which helps account for the high poverty concentrations in declining markets.
Understanding the supply side of housing markets also is helpful in making sense of housing bubbles. Bubbles are more difficult to start and sustain in less constrained markets with elastic housing supplies, according to a simple model of housing bubbles proposed in a recent paper with Edward Glaeser and Albert Saiz. The best indicator of a bubble is a wide and growing gap between house prices and fundamental production costs[4] in a market with elastic supply. The state of demand, not supply, will largely determine what happens to prices in the most inelastically supplied markets.
Local regulation may act as a “zoning tax” that raises the price of housing above what it would be in the absence of supply restrictions.[5] The research approach to gauging the size of the zoning tax was to estimate the marginal cost of producing a home and then compare that cost with the house’s actual market value. More specifically, standard neoclassical economics indicates that the price households are willing to pay for an extra square foot of lot size (the intensive margin) should equal the price of land underlying existing homes (the extensive margin). If this was not the case, and homeowners did not value the land on their plots very much, they could subdivide and sell off part of their plot to someone else. Effective zoning tax rates are quite high in many high price U.S. markets, sometimes reaching over 50 percent, as actual market prices far exceed the hedonic estimates of the value of an extra square foot of land.[6]
[1] See Glaeser, Gyourko and Saks (2006) for more on this.
[2] Glaeser and Tobio (2008) argue that the rise of the southern sunbelt markets is largely the result of allowing plentiful, cheap housing, not because of a better amenity set or fundamentally higher productivity.
[3] See Glaeser and Gyourko (2005b).
[4] Fundamental production costs are defined as the sum of the physical costs of construction for a basic, modest quality home, plus a 20 percent land share, plus a 17 percent gross profit margin on structure and land costs for the builder. In the United States, in the 1970s there was no metropolitan area in which average house prices exceeded fundamental production costs by more than 20 percent. See Glaeser, Gyourko and Saks (2005a, b) for more detail on the time pattern of house prices relative to production costs.
[5] This was the term that Edward Glaeser and I used in our 2003 paper, but it should be interpreted as applying to any local land use restriction, not just those related to zoning.
[6] See Glaeser and Gyourko (2003) for a more detailed discussion of how to implement this type of analysis.
While much has been learned about housing supply in recent years, much remains to be done. First, data collection involving measurement of the local regulatory environment should be at the top of the “to do” list. Anita Summers and Albert Saiz of the Zell/Lurie Real Estate Center at the Wharton School at the University of Pennsylvania created the Wharton Residential Land Use Regulation Index.[1] This involves a national data collection effort for the United States. The data covers more than 2,000 communities across all major metropolitan areas. The alternative is to collect details on the regulatory environment in selected local environment.
Second, better estimates of local supply elasticities are needed. Supply heterogeneity clearly is important, so we need to carefully measure its variation[2] and fully integrate heterogeneous supply into a well-specified model of housing market dynamics. We need to better understand why constraints on supply develop in some markets, but not in others. There is interesting work on the political economy of this issue[3], but much remains to be done.
It remains very difficult to measure the impact of local regulation on prices with precision. The increasing complexity of the local regulatory environment makes it hard to measure accurately and knowledge of land prices is required for an accurate comparison, but is seldom available. [4] More specifically, one needs to be able to compare the “free market” price of land with existing values. The problem is that there are virtually no observed trades of residential land parcels and the most sensible conclusion one can make in the absence of existing data is that only very wide gaps between prices on the intensive and extensive margins represent the impact of supply constraints on home building. Another is to study a market in which no additional land is required to produce an extra housing unit. Edward Glaeser, Raven Saks and I did just this in our analysis of the condominium market in Manhattan.[5]
[1] See Gyourko, Summers and Saiz (2008).
[2] See Saiz (2008) for a current effort.
[3] See Ortalo-Magne and Prat (2007), for example.
[4] Haughwout, Orr and Bedell (2008) are one exception with their data on land values in the New York City market.
[5] See Glaeser, Gyourko, and Saks (2005b)
Glaeser, Edward and Joseph Gyourko. June 2003. The Impact of Zoning on Housing Affordability, Economic Policy Review, Vol. 9, No. 2, pp. 21-39.
Glaeser, Edward and Joseph Gyourko. December 2006. Housing Dynamics, NBER Working Paper 12787.
Glaeser, Edward and Joseph Gyourko. 2008. Rethinking Federal Housing Policy. Washington DC: The AEI Press.
Glaeser, Edward and Bryce Ward. 2009. The Causes and Consequences of Land Use Regulation: Evidence from Greater Boston, Journal of Urban Economics, Vol. 65, No. 3, pp. 265-278.
Glaeser, Edward, Joseph Gyourko and Albert Saiz. 2008. Housing Supply and Housing Bubbles, Journal of Urban Economics, Vol. 64, No. 2, pp. 693-729.
Glaeser, Edward, Joseph Gyourko and Raven Saks. May 2005a. Why Have House Prices Gone Up? American Economic Review, Vol. 95, No. 2, pp. 329-333.
Glaeser, Edward, Joseph Gyourko and Raven Saks. October 2005b. Why Is Manhattan So Expensive? Regulation and the Rise in House Prices, Journal of Law & Economics, Vol. 48, No. 2, pp. 331-370.
Glaeser, Edward, Joseph Gyourko and Raven Saks. January 2006. Urban Growth and Housing Supply, Journal of Economic Geography, Vol. 6, No. 1, pp. 71-89.
Joseph Gyourko is the Martin Bucksbaum Professor of Real Estate, Finance and Business and Public Policy; Chairperson of the Real Estate Department; and Director of the Samuel Zell and Robert Lurie Real Estate Center at the Wharton School of the University of Pennsylvania.