This book is the definitive user’s guide to the spatial regression functionality in the software packages GeoDa and GeoDaSpace, as well as the spreg module in the PySAL library –-all developed at the GeoDa Center for Geospatial Analysis and Computation. The book provides the techniques to test for and estimate spatial effects in linear regression models, addressing both spatial dependence (spatial autoregressive models) as well as spatial heterogeneity (spatial regimes models). The book also serves as an introduction and a practical guide to spatial econometrics in that it covers the methodological principles and formal results that underlie the various estimation methods, test procedures and model characteristics computed by the software. While the classical maximum likelihood estimation is included, the book’s coverage emphasizes modern techniques based on the principle of generalized method of moments (GMM).

� propos de l?auteur:

Luc Anselin is Regents' Professor and holds the Walter Isard Chair in the School of Geographical Sciences and Urban Planning at Arizona State University, where he also directs the GeoDa Center for Geospatial Analysis and Computation. He has written widely on spatial data analysis and geographic information science, including the 1988 classic on Spatial Econometrics. He is the developer of the SpaceStat and GeoDa software packages, and of the spreg-GeoDaSpace module in the PySAL software. Sergio J. Rey is Professor in the School of Geographical Sciences and Urban Planning at Arizona State University, where he is also a member of the Executive Committee of the GeoDa Center for Geospatial Analysis and Computation. His research deals with the development, implementation, and application of advanced methods of spatial and space-time data analysis. He is the creator of the open source package STARS (Space-Time Analysis of Regional Systems) as well as the co-founder and lead developer of the PySAL library.

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Articles li�s � Modern Spatial Econometrics in Practice: A Guide to...

Modern Spatial Econometrics in Practice: A Guide to GeoDa, GeoDaSpace and PySAL

Rey, Sergio J.; Anselin, Luc

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