Highly Disaggregated Land Unavailability

44 Pages Posted: 11 Nov 2019 Last revised: 4 Apr 2022

See all articles by Chandler Lutz

Chandler Lutz

Securities and Exchange Commission

Ben Sand

York University

Date Written: April 22, 2022

Abstract

We combine high-resolution satellite imagery with modern machine learning techniques to construct novel datasets that capture the geographic determinants of U.S. housing supply. This Land Unavailability (LU) measure is a markedly more accurate house price predictor than the popular proxy of \citet{Saiz2010}. LU is also uncorrelated with housing demand proxies, supporting its use as an instrument for house prices. We apply LU to fundamental housing finance problems to provide substantially more precise housing wealth elasticity estimates; novel empirical tests of the supply-side speculation theory; and new evidence on the relationship between house prices and self-employment during COVID-19.

Keywords: Land Unavailability, Buildable Land, Real Estate, Housing Market

JEL Classification: R30, R31, R20

Suggested Citation

Lutz, Chandler and Sand, Ben, Highly Disaggregated Land Unavailability (April 22, 2022). Available at SSRN: https://ssrn.com/abstract=3478900 or http://dx.doi.org/10.2139/ssrn.3478900

Chandler Lutz (Contact Author)

Securities and Exchange Commission ( email )

100 F Street, NE
Washington, DC 20549
United States

Ben Sand

York University ( email )

4700 Keele St.
Toronto, Ontario M3J 1P3
Canada

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