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

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).

• Introduction to Spatial Econometrics (Statistics: A Series of Textbooks and Monographs)
• Analyzing Social Networks
• Geospatial Analysis: A Comprehensive Guide
• GIS Tutorial 1: Basic Workbook
• Spatial Econometrics
• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
• Applied Spatial Data Analysis with R (Use R!)
• GIS Tutorial for Health: Fifth Edition (GIS Tutorials)
• A Primer for Spatial Econometrics: With Applications in R (Palgrave Texts in Econometrics)
• An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS)