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Restricting Residential Construction

Edward L. Glaeser

May 2007, English

In this paper, Edward L. Glaeser analyzes how land use regulations have affected housing costs in selected U.S. cities, and he looks at the welfare effects of zoning on the economy and nonpropertied groups. He concludes that land use regulations have increased housing values in many U.S. cities.

Based on his analysis of U.S. data between 2000 and 2005, Glaeser argues that overly restrictive zoning has probably limited the supply of development rights and driven property prices up. He bases his argument on five facts about the relation between permitting and property prices. First, low levels of permitting are found in high-price areas. For example, the cities of San Francisco and New York issued very few permits for new construction between 2000 and 2005, and yet their median housing prices were (and still are) among the highest in the United States. Second, the dearth of permitting did not result from a shortage of land. The number of permits per acre between 2000 and 2005 is strongly correlated with housing density in 2000. In other words, places with initially high density levels typically issued more permits for new development relative to their total land area than did low-density areas. Putting the two pieces of information together, Glaeser asserts that high densities are not the major cause of high housing prices. Third, the median lot size of American homes has increased. In Greater Boston, for example, it grew from 0.76 to 0.91 acre between 1990 and 1998. Because the income elasticity of demand for land in Boston is estimated to be between 0.1 and 0.25, this growth did not flow solely from the rise in real incomes, which only increased by 13 percent during this period. Fourth, neither construction costs nor land prices fully explain high property prices. Glaeser and Gyourko (2003) estimate what they call the “zoning tax” (the payment for the right to develop a lot) and found it to be about 34 percent of the house value for Los Angeles and 19 percent for Boston in 1999. In Manhattan, it was as much as 50 percent of the value of a condominium in 2002 (Glaeser, Gyourko, and Saks 2005). Although Glaeser admits that the direct impacts of zoning on prices are difficult to measure because of spillovers, these estimates are so large that it is hard to refute the significance of land use regulations. Finally, according to his formal measures, he concludes that land use controls are negatively associated with permitting and positively associated with housing prices.

Meanwhile, Glaeser agrees that zoning often serves the purpose of internalizing externalities, and thus establishing a reasonable level of land use restriction is paramount. He suggests that for New York City the optimal zoning tax needed to deal with “structure-related externalities” is about 20 percent of the property value. However, he estimates that the tax is actually as much as five times that amount. More important, in setting up zoning taxes policy makers should consider the marginal social costs of new development across regions. If those costs are the same everywhere, imposing varied zoning taxes on similar communities would distort resource allocation, thereby creating inefficiency.

According to Glaeser, nonstructure-related zoning is the most troubling kind of regulation. For example, limiting construction in inner cities to avoid traffic congestion may only push housing development outward, thereby generating additional traffic from commuter work trips. Restricting the supply of low-cost housing to maintain the homogeneity of the income and ethnic composition of a town contravenes the social goals for greater integration. And constraining the design and size of new houses to internalize fiscal externalities may not be as effective as directly charging the new homeowners a user (or impact) fee.

What are the effects of nonoptimal zoning on the economy? As Glaeser points out, high housing prices are, in effect, a transfer from home buyers to sellers (or from renters to propertied groups). Depending on the consumption patterns of these different segments of the population, aggregate consumption may be lower, thereby dampening growth of the gross domestic product (GDP). At the very least, restrictions on the development of new houses may force more people to live in older homes and lower the utility of housing consumption because of the reduction in the flow of housing services consumed. Zoning also may create price rigidity in the property markets and make housing prices more volatile. Finally, because the population size and employment rate of a region are determined in part by its housing supply, high housing prices may lead to a smaller flow of people into the high-price area and later to higher wages. For example, Glaeser estimates that the economy of the San Francisco Bay Area may be losing $2 billion a year and have a population smaller by 200,000 because its housing costs are on average $20,000 higher than those of other regions.

This paper was presented at the Lincoln Institute’s annual Land Policy Conference in 2006 and is Chapter 2 of the book Land Policies and Their Outcomes.