Semiparametric Estimation of Land Price Gradients Using Large Data Sets

FRB Richmond Economic Quarterly, Vol. 95, No. 1, Winter 2009, pp. 53-74

22 Pages Posted: 13 Dec 2012

See all articles by Kevin A. Bryan

Kevin A. Bryan

Virginia Commonwealth University (VCU)

Pierre-Daniel G. Sarte

Federal Reserve Bank of Richmond

Date Written: 2009

Abstract

The exact nature of land price gradients, the surface describing how land prices change with location, can be difficult to uncover. This is particularly true for cities with few vacant lots or in more rural regions where the number of land sales in a given area is limited. This article outlines a semiparametric method to construct the land price surface given a large set of residential property sales, and investigates properties of this surface in Richmond, Virginia, and three surrounding counties. Despite recent concentrations of housing in suburban areas, we find that Richmond remains largely a monocentric city. Nevertheless, the price surface that we estimate features a complex topography, and high prices near suburban interstates and lakes are clearly evident.

Suggested Citation

Bryan, Kevin A. and Sarte, Pierre-Daniel, Semiparametric Estimation of Land Price Gradients Using Large Data Sets (2009). FRB Richmond Economic Quarterly, Vol. 95, No. 1, Winter 2009, pp. 53-74. Available at SSRN: https://ssrn.com/abstract=2188501

Kevin A. Bryan

Virginia Commonwealth University (VCU) ( email )

1015 Floyd Avenue
Richmond, VA 23284
United States

Pierre-Daniel Sarte (Contact Author)

Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

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