期刊
REGIONAL SCIENCE AND URBAN ECONOMICS
卷 43, 期 4, 页码 617-634出版社
ELSEVIER
DOI: 10.1016/j.regsciurbeco.2013.03.005
关键词
Spatial econometrics; Spatial autocorrelation; Spatial weights matrix; Spatial error model; Partial identification; Housing demand; Gradient projection
While estimates of models with spatial interaction are very sensitive to the choice of spatial weights, considerable uncertainty surrounds the definition of spatial weights in most studies with cross-section dependence. We show that, in the spatial error model, the spatial weights matrix is only partially identified, and is fully identified under the structural constraint of symmetry. For the spatial error model, we propose a new methodology for estimation of spatial weights under the assumption of symmetric spatial weights, with extensions to other important spatial models. The methodology is applied to regional housing markets in the UK, providing an estimated spatial weights matrix that generates several new hypotheses about the economic and socio-cultural drivers of spatial diffusion in housing demand. (C) 2013 Elsevier B.V. All rights reserved.
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