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Introduction to Spatial Econometrics presents a variety of regression methods for analyzing spatial data samples that violate the traditional assumption of independence between observations. It explores a range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances. The authors clarify the often-mystifying phenomenon of simultaneous spatial dependence. By presenting new methods, they help with the interpretation of spatial regression models. MATLAB toolboxes useful for spatial econometric estimation are made available on the authors' websites.
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