© 2014

A Primer for Spatial Econometrics

With Applications in R

  • Authors

Part of the Palgrave Texts in Econometrics book series (PTEC)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Giuseppe Arbia
    Pages 1-25
  3. Giuseppe Arbia
    Pages 26-50
  4. Giuseppe Arbia
    Pages 51-98
  5. Giuseppe Arbia
    Pages 99-166
  6. Giuseppe Arbia
    Pages 202-206
  7. Back Matter
    Pages 207-230

About this book


This book aims at meeting the growing demand in the field by introducing the basic spatial econometrics methodologies to a wide variety of researchers. It provides a practical guide that illustrates the potential of spatial econometric modelling, discusses problems and solutions and interprets empirical results.


Spatial Econometrics spatial statistics econometrics Import modeling regression spatial econometrics

About the authors

Giuseppe Arbia (PhD Cantab) is Full Professor of Economic Statistics at the Università Cattolica del Sacro Cuore of Rome, Italy, and Lecturer of Statistics at the Università della Svizzera Italiana in Lugano, Switzerland. He was formerly Visiting Professor at New York University, USA, and at many other international universities. He has published five books and more than 100 articles on the topic of spatial statistics and econometrics and is currently the Chairman of the Spatial Econometrics Association and the Director of the Spatial Econometrics Advanced Institute.

Bibliographic information

Industry Sectors
Finance, Business & Banking


“The book is a very useful practical guide for applied researchers employing spatial econometrics tools. It could be adopted as the textbook for a first course in spatial economics/econometrics, and it comes as an easy-to-read book for students and researchers with a little knowledge in this field. … it presents both basic concepts and more advanced topics in a synthetic but clear and rigorous manner, and this approach makes it an useful reference for applied (spatial) econometricians.” (Roberto Ganau, Italian Journal of Regional Science, Vol. 16 (1), January, 2017)