SEARCHING FOR HOUSING SUBMARKETS USING MIXTURES OF LINEAR MODELS

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Advances in Econometrics

ISSN: 0731-9053
Series editor(s): Thomas B. Fomby, R. Carter Hill, Ivan Jeliazkov, Juan Carlos Escanciano and Eric Hillebrand

Subject Area: Economics

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Document Information:
Title:	SEARCHING FOR HOUSING SUBMARKETS USING MIXTURES OF LINEAR MODELS
Author(s):	M.D. Ugarte, T. Goicoa, A.F. Militino
Volume:	18 Editor(s): James P. Lesage and R. Kelley Pace ISBN: 978-0-76231-148-4 eISBN: 978-1-84950-301-3
Citation:	M.D. Ugarte, T. Goicoa, A.F. Militino (2004), SEARCHING FOR HOUSING SUBMARKETS USING MIXTURES OF LINEAR MODELS, in James P. Lesage and R. Kelley Pace (ed.) Spatial and Spatiotemporal Econometrics (Advances in Econometrics, Volume 18), Emerald Group Publishing Limited, pp.259-276
DOI:	10.1016/S0731-9053(04)18008-0 (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	This paper presents a mixture of linear models (or hedonic regressions) for defining housing submarkets. Two different mixture models are considered: the first model allows all the regression coefficients to vary among the clusters (random coefficients); and the second model allows only the intercept term to change (random intercept). The model with a random intercept can be seen as a linear mixed model where the random effects distribution is estimated via non-parametric maximum likelihood (NPML). The models are illustrated using a real data set of 293 properties in Pamplona, Spain. These mixture models provide a classification of the dwellings into homogeneous groups that determine the structure of the submarkets.