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The (Literally) Steepest Slope: Spatial, Temporal, and Elevation Variance Gradients in Urban Spatial Modelling

54 Pages Posted: 23 Dec 2015 Last revised: 19 Jan 2017

Charles Becker

Duke University - Department of Economics

Victor Yifan Ye

Duke University, Department of Economics, Students

Date Written: October 15, 2016

Abstract

This paper presents an analysis of elevation gradient and temporal future-station effects in urban real estate markets. Using an extraordinary dataset from the Hong Kong publicly-constructed housing sector, we find enormous housing price effects caused by levels of terrain incline between apartments and subway stations. Ceteris paribus, two similar apartments with closest metro stations of the same walking distance may sell at a difference of up to 20% because of differences in the apartment-station slope alone. Anticipatory effects are similarly robust: apartment buyers regard a future, closer metro station as being 60% present when making purchases two years prior to its opening.

Keywords: Housing, Public Transit, Metro, Elevation, Anticipatory Effects, Hong Kong

JEL Classification: R31, R41, R53

Suggested Citation

Becker, Charles and Ye, Victor Yifan, The (Literally) Steepest Slope: Spatial, Temporal, and Elevation Variance Gradients in Urban Spatial Modelling (October 15, 2016). Economic Research Initiatives at Duke (ERID) Working Paper No. 202. Available at SSRN: https://ssrn.com/abstract=2706709 or http://dx.doi.org/10.2139/ssrn.2706709

Charles Becker (Contact Author)

Duke University - Department of Economics ( email )

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

Victor Ye

Duke University, Department of Economics, Students ( email )

Durham, NC
United States

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