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Semi-Parametric Tools for Spatial Hedonic Models: An Introduction to Mixed Geographically Weighted Regression and Geoadditive Models

In: Hedonic Methods in Housing Markets

Author

Listed:
  • Ghislain Geniaux

    (INRA Ecodeveloppement)

  • Claude Napoléone

    (INRA Ecodeveloppement)

Abstract

This chapter focuses on the contribution of semi-parametric tools such as Mixed Geographically Weighted Regression (MGWR) (Fotheringham et al. 1997) and Geoadditive Models (Hastie and Tibshirani 1993; Kammann and Wand 2003) that belong to the General Additive Models family (GAM), to explore the effects of distance regressors on price and/or spatial nonstationarity of implicit house price coefficient in hedonic functions. These tools have become essential with: Growing evidence in the economic literature of the multiplicity of amenity sources linked to space and location of houses. Amenity sources can be related to the distance to different public services, commercial facilities, noteworthy landmarks, tourist area, etc. Using monocentric models based on the single distance to Central Business District (CBD) is not sufficient to assess the effect of urban sprawl on land prices. Dominant models in economy fail to account for amenity values, congestion cost or social expenditure for public infrastructure (Brueckner 2001). The specification of hedonic OLS models may be quite difficult when numerous distance measures are candidate regressors, especially with respect to the colinearity issue. GAM is a powerful and flexible tool to explore distance effects with large samples. The upscale and downscale extension of available spatial descriptors provided by many public and private organizations has resulted in an explosion in the use of GIS in the last five years. This increased use of GIS by public administrations facilitates the introduction of finer descriptors of landscape, public services and social neighbourhoods in hedonic models. Working on large samples with a lot of finer descriptors of the environment and neighborhood involves dealing with numerous local effects. In this case it is necessary to use multiple scales to analyze the structure of house prices (Quigley 1995). Locally weighted regressions such as Geographically Weighted Regressions (GWR) or MGWR, and GAM, enable estimation of spatially varying and invariant implicit prices in hedonic analysis.

Suggested Citation

  • Ghislain Geniaux & Claude Napoléone, 2008. "Semi-Parametric Tools for Spatial Hedonic Models: An Introduction to Mixed Geographically Weighted Regression and Geoadditive Models," Springer Books, in: Andrea Baranzini & José Ramirez & Caroline Schaerer & Philippe Thalmann (ed.), Hedonic Methods in Housing Markets, chapter 5, pages 101-127, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-76815-1_6
    DOI: 10.1007/978-0-387-76815-1_6
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    Citations

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    Cited by:

    1. Kathrine von Graevenitz & Toke Emil Panduro, 2015. "An Alternative to the Standard Spatial Econometric Approaches in Hedonic House Price Models," Land Economics, University of Wisconsin Press, vol. 91(2), pages 386-409.
    2. Maria J. Barcena & Patricia Mendez & Maria B. Palacios & Fernando Tusell, 2013. "Measuring the effect of the real estate bubble: a house price index for Bilbao," Chapters from NBP Conference Publications, in: Hanna Augustyniak & Jacek Łaszek & Krzysztof Olszewski (ed.), Papers presented during the Narodowy Bank Polski Workshop: Recent trends in the real estate market and its analysis, 2013, chapter 15, pages 127-156, Narodowy Bank Polski.
    3. Jeanne Dachary-Bernard & Frédéric Gaschet & Sandrine Lyser & Guillaume Pouyanne & Stéphane Virol, 2011. "L'impact de la littoralisation sur les marchés fonciers : une approche comparative des côtes basque et charentaise," Post-Print hal-00688634, HAL.
    4. Nakamura, Shohei, 2017. "Tenure Security Premium in Informal Housing Markets: A Spatial Hedonic Analysis," World Development, Elsevier, vol. 89(C), pages 184-198.
    5. Cathrine Ulla Jensen & Toke Emil Panduro, 2016. "PanJen: A test for functional form with continuous variables," IFRO Working Paper 2016/08, University of Copenhagen, Department of Food and Resource Economics.
    6. Stéphane Virol & Guillaume Pouyanne & Sandrine Lyser & Frédéric Gaschet & Jeanne Dachary-Bernard, 2011. "L’impact de la littoralisation sur les marchés fonciers. Une approche comparative des côtes basque et charentaise," Économie et Statistique, Programme National Persée, vol. 444(1), pages 127-154.

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