Can Geospatial Data Improve House Price Indexes? A Hedonic Imputation Approach with Splines

20 Pages Posted: 16 Nov 2018

See all articles by Robert J. Hill

Robert J. Hill

University of Graz

Michael Scholz

Goethe University Frankfurt

Date Written: December 2018

Abstract

Determining how and when to use geospatial data (i.e. longitudes and latitudes for each house) is probably the most pressing open question in the house price index literature. This issue is particularly timely for national statistical institutes (NSIs) in the European Union, which are now required by Eurostat to produce official house price indexes. Our solution combines the hedonic imputation method with a flexible hedonic model that captures geospatial data using a non‐parametric spline surface. For Sydney, Australia, we find that the extra precision provided by geospatial data as compared with postcode dummies has only a marginal impact on the resulting hedonic price index. This is good news for resource‐stretched NSIs. At least for Sydney, postcodes seem to be sufficient to control for locational effects in a hedonic house price index.

Keywords: housing market, house price measurement, geospatial spline surface, quality adjustment, semiparametric hedonic model

Suggested Citation

Hill, Robert J. and Scholz, Michael, Can Geospatial Data Improve House Price Indexes? A Hedonic Imputation Approach with Splines (December 2018). Review of Income and Wealth, Vol. 64, Issue 4, pp. 737-756, 2018. Available at SSRN: https://ssrn.com/abstract=3285384 or http://dx.doi.org/10.1111/roiw.12303

Robert J. Hill (Contact Author)

University of Graz ( email )

Universitaetsstrasse 15 / FE
A-8010 Graz, 8010
Austria

Michael Scholz

Goethe University Frankfurt ( email )

Theodor-W.-Adorno-Platz 4
Hauspostfach 64
Frankfurt, 60629
Germany

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