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An Anisotropic Model for Spatial Processes
Author(s) -
Deng Minfeng
Publication year - 2008
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/j.0016-7363.2007.00712.x
Subject(s) - isotropy , spatial econometrics , monte carlo method , anisotropy , spatial dependence , flexibility (engineering) , spatial analysis , computer science , econometrics , process (computing) , interpretation (philosophy) , statistical physics , lag , mathematics , statistics , physics , computer network , quantum mechanics , programming language , operating system
One of the key assumptions in spatial econometric modeling is that the spatial process is isotropic, which means that direction is irrelevant in the specification of the spatial structure. On the one hand, this assumption largely reduces the complexity of the spatial models and facilitates estimation and interpretation; on the other hand, it appears rather restrictive and hard to justify in many empirical applications. In this article a very general anisotropic spatial model, which allows for a high level of flexibility in the spatial structure, is proposed. This new model can be estimated using maximum likelihood and its asymptotic properties are derived at length. When the model is applied to the well‐known 1970 Boston housing prices data, it significantly outperforms the isotropic spatial lag model. It also provides interesting additional insights into the price determination process in the properties market. Finally, a Monte Carlo simulation study is used to confirm the optimal properties of the model.