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Robust hedonic price indexes

Steven C Bourassa (School of Urban and Regional Planning, Florida Atlantic University, Boca Raton, Florida, USA)
Eva Cantoni (Research Center for Statistics and Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland)
Martin Hoesli (Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland AND University of Aberdeen, Aberdeen, UK AND Kedge Business School, Bordeaux, France)

International Journal of Housing Markets and Analysis

ISSN: 1753-8270

Article publication date: 7 March 2016

391

Abstract

Purpose

The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes.

Design/methodology/approach

The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated.

Findings

Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes.

Practical implications

Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes.

Originality/value

This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.

Keywords

Citation

Bourassa, S.C., Cantoni, E. and Hoesli, M. (2016), "Robust hedonic price indexes", International Journal of Housing Markets and Analysis, Vol. 9 No. 1, pp. 47-65. https://doi.org/10.1108/IJHMA-11-2014-0050

Publisher

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Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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