Dealing with Unobserved Heterogeneity in Hedonic Price Models

41 Pages Posted: 1 Oct 2018 Last revised: 18 Dec 2018

See all articles by Marc Francke

Marc Francke

University of Amsterdam - Faculty of Economics and Business (FEB); Ortec Finance

Alex Van de Minne

University of Connecticut - Department of Finance

Date Written: September 13, 2018

Abstract

This paper deals with unobserved heterogeneity in hedonic price models, arising from missing property and locational characteristics. In specific, commercial real estate is very heterogeneous, and data on detailed property characteristics are often lacking. We show that adding mutually independent property random effects to a hedonic price model results in more precise out-of-sample price predictions, both for commercial multifamily housing in Los Angeles and owner-occupied single family housing in Heemstede, the Netherlands. The standard hedonic price model does not take advantage of the fact that some properties sell more than once. We subsequently show that adding spatial random effects leads to an additional increase in prediction accuracy. The increase is highest for properties without prior sales.

Keywords: Bayesian Inference, Besag model, Commercial real estate, INLA, Leave-on-out-cross validation, Travelings Salesperson Problem

JEL Classification: R32, C01

Suggested Citation

Francke, Marc and Van de Minne, Alex, Dealing with Unobserved Heterogeneity in Hedonic Price Models (September 13, 2018). Available at SSRN: https://ssrn.com/abstract=3249256 or http://dx.doi.org/10.2139/ssrn.3249256

Marc Francke

University of Amsterdam - Faculty of Economics and Business (FEB) ( email )

Plantage Muidergracht 12
Amsterdam, 1018 TV
Netherlands

HOME PAGE: http://www.uva.nl/en/contact/staff/item/m.k.francke.html?f=francke

Ortec Finance ( email )

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Amsterdam, 1043 CP
Netherlands
+ 31 20 7009 700 (Phone)
+ 31 20 7009 701 (Fax)

HOME PAGE: http://www.ortec-finance.com

Alex Van de Minne (Contact Author)

University of Connecticut - Department of Finance ( email )

School of Business
2100 Hillside Road
Storrs, CT 06269
United States

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