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Hierarchy and spatial autocorrelation effects in hedonic models


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  • Coro Chasco

    (Universidad Autónoma de Madrid)

  • Julie Le Gallo

    (Université de Franche-Comté)


Hedonic housing price models should deal with spatial autocorrelation in order to avoid bias and inconsistency in the coefficient estimates. Multilevel models have been presented as a way of properly considering the effects of neighbourhood amenities operating at different spatial hierarchies. In this paper, we test this feature by specifying a three-level model for a dataset on downtown Madrid, which includes spatially lagged explanatory variables. The results show that hierarchical models are not capable of fully capturing spatial autocorrelation so that more effort should be done in developing the appropriate spatial multilevel models.

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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 32 (2012)
Issue (Month): 2 ()
Pages: 1474-1480

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Handle: RePEc:ebl:ecbull:eb-11-00777

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Keywords: hedonic models; hierarchical data; multilevel models; spatial autocorrelation;

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  1. G�ran Therborn & K.C. Ho, 2009. "Introduction," City, Taylor & Francis Journals, Taylor & Francis Journals, vol. 13(1), pages 53-62, March.
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Cited by:
  1. Dennis Sánchez-Navarro, 2012. "Una propuesta metodológica para la definición de mercados geográficos relevantes," ESTUDIOS ECONÓMICOS SIC, SUPERINTENDENCIA DE INDUSTRIA Y COMERCIO 010492, SUPERINTENDENCIA DE INDUSTRIA Y COMERCIO.


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