The Price Elasticity of the Demand for Residential Land

The paper presents new estimates of the price and income elasticities for residential land which overcome serious econometric problems associated with earlier analyses. Our estimates are based on a unique data set spanning 28 years of home sales which provides repeated observations on the Montgomery County, PA, housing market. The data allow us to employ the two-stage least squares techniques recommended by Bartik (1987) and Epple (1987) to overcome the central problem associated with estimating demand functions for bundled goods—namely, that consumers simultaneously choose both the price and quantity of the bundled good. Our results suggest that the price elasticity of demand for residential land is around -1 and the income elasticity is near 1.5. Our findings further suggest that ordinary least squares (OLS) estimates are substantially upwardly biased.

The importance of these estimates for understanding the impacts of public policy on the pattern of development is illustrated by examining the potential effects of the U.S. tax treatment of housing on the demand for residential land. Given the price elasticity estimate and tax code-related subsidies to user costs in the 15-percent range, calculations using the assumptions of a traditional monocentric city model suggest that the radius of the occupied area can be as much as seven-percent longer than in the absence of the subsidy.