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.
Ugarte, M., Goicoa, T. and Militino, A. (2004), "SEARCHING FOR HOUSING SUBMARKETS USING MIXTURES OF LINEAR MODELS", Lesage, J. and Kelley Pace, R. (Ed.) Spatial and Spatiotemporal Econometrics (Advances in Econometrics, Vol. 18), Emerald Group Publishing Limited, Bingley, pp. 259-276. https://doi.org/10.1016/S0731-9053(04)18008-0Download as .RIS
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